Life in BIOINFORMATICS......

STUDY INDIA Contd (PART 3)

2010-06-04T07:55:00.000-07:00

ANDHRA UNIVERSITY :Offers M.Tech BIOINFORMATICS

More info regarding the pro gramme refer to the following site:

http://www.andhrauniversity.info/engg/csse/syllabus.html

BANASTHALI UNIVERSITY: M.Sc. (2 years) and P.G. diploma course (1 year) in bioinformatics,Refer to the link below

http://www.banasthali.org/banasthali/wcms/en/home/lower-menu/faculties/maths-app-comp-tech/maths-app-comp-tech_top/bio_info/index.html

INSTITUTE OF BIOINFORMATICS & APPLIED BIOTECHNOLOGY(IBAB):

PG DIPLOMA IN BIOINFORMATICS

INDIAN INSTITUE OF INFORMATION TECHNOLOGY(Allahabad):Offers M.Tech in BIOINFORMATICS

http://bi.iiita.ac.in/

INDIAN INSTITUTE OF CHEMICAL TECHNOLOGY,tarnaka HYD

ADVANCED COURSE IN BIOINFORMATICS

http://www.iictindia.org/zacb/

INSTITUTE OF GENOMICS & INTEGRATIVE BIOLOGY,Delhi

Offers PhD Prrogramme in Bioinformatics

MAHARAJA SAYAJIRAO UNIVERSITY,BARODA

Offers MS in Bioinformatics.

STUDY INDIA Contd,...

2010-05-31T00:04:00.000-07:00

Helpful tips for students who are in their Final and Pre-final year of their bachelors degree and wish to continue education into Masters level in India:
The information provided is strictly for students who want to get into MSc/M.Tech BIOINFORMATICS:
Well first of all lets sort out the list of universities taht we have in hand providing the Masters level course I will start with the most reknowned universities and go in the descending order:

1.UNIVERSITY OF PUNE: http://bioinfo.ernet.in/courses/IndexMSC.html
Is renowned amongst us for being one of the first in India DBT (Dept of Biotechnology) approved Bioinformatics centre.

BIOINFORMATICS CENTRE (D.I.C.)
University of Pune,
Pune – 411007
Tel: 5690195/5692039
Website: http//www.bioinfo.ernet.in/www/center.html

2
JAWHARLAL NEHRU UNIVERSITY (JNU)
New Delhi – 110067
Phone: 26165886/ 26167557
Website: http://www.jnu.ac.in/cbt/cbt.html
There is an Advanced (Graduate) Diploma in Bioinformatics offered by the Bioinformatics Centre at the Jawaharlal Nehru University.The University itself conducts M.Tech entrance examination every yr for student enrollment into M.Tech Bioinformatics,Biotechnology.

3. INDIAN INSTITUTE OF TECHNOLOGY DELHI
Haus Khas, New Delhi –110016
Tel: 26582222/ 26581696
Website: http://www.iitd.ernet.in

4.Madurai Kamaraj University in Madurai, claims to have been the first in the country to initiate a bioinformatics programme and advanced diploma in bioinformatics at its School of Biotechnology.

5.IIIT Hyderabad : Offers M.Tech BIOINFORMATICS course and they conduct and entrance cum interview based examination.

6.UNIVERSITY OF PONDICHERRY : MSc BIOINFORMATICS Entrance examination is conducted.

7.UNIVERSITY OF HYDERABAD: M.Tech BIOINFORMATICS as seen this year they have introduced merit basis selection of candidates including your GATE score in Biotechnology,shortlisted candidates are called for Interview in later phase.

8.CENTRE FOR BIOTECHNOLOGY
Anna University, Chennai- 600025, INDIA
Phone: 2350772, 2350299
Email: arunb@annauniv.edu
Website: http://www.annauniv.edu/biotech/btch.html

9. BIOINFORMATICS CENTRE
SCHOOL OF BIOTECHNOLOGY
Madurai Kamraj University
Madurai – 625021
Tel: 452-459105
Email: kdharmalingam@vsnl.com

10.BHARATHIAR UNIVERSITY
Coimbatore – 46
Website: http//www.bharathiaruni.org

The universities mentioned above are one of the top notch universities and students getting enrolled have bright future seen as for getting Phds as well as for future jobs.

Once we have shortlisted our universities lets just review what exactly do we have to prepare for? as most of these universities involve enrollment via entrance examination!!! goshhh yes yes and the syllabi is definitely very vast even I got shocked when i saw my old BOTANY book of 11std in front to study for Pune entrance(:o)..so students BE PREPARED!!! and the earlier you strt the better your opportunities in getting into these courses.

Most of these examinations actually look out for your basics you must be strong in your BIOPHYSICS BIOCHEMISTRY STATISTICS and ofcourse your MOLECULAR BIOLOGY as you can see thses subjects are mostly concentrate din your SECOND Yr.. So be through with your second yr syllabus.

More on Bioinformatics

2010-04-07T00:10:00.000-07:00

Bio informatics is a subject that has extraordinary promise not just in the design of drugs and therapies but also in the basic understanding of life itself. It is the application of information technology to the management of biological data and is a rapidly evolving scientific discipline.

It encompasses research, development and application of computational tools and aims at expanding the use of biological, medical, behavioural, or health data. Hence data is acquired, stored, organized, archived and then analysed. Bio informatics relies on statistical methods.

Specialized work is carried on in drugs research, agrochemicals, hybridization, plastics and petroleum derivatives, environmental remediation etc.

Nature of Work

Bio informatics performs two critical roles : develops IT tools embodying novel algorithms and analytical techniques, or applies existing tools to achieve new insights into molecular biology in testing, documentation, running operating procedures and database administration, programming, software development, algorithm creation and scientific visualization. Bio informatics can be applied to all areas of life sciences and other fields like energy and textiles, pharmaceuticals and agriculture. Bio informatics is used for treatment of genetic diseases. Knowledge about the method in which drugs work at the genetic level finds applications in the treatment of cancer as well as infectious diseases like AIDS. Bio-informatics also throws light on toxicogenomics, a speciality that tries to find an answer as to why drugs work better on some patients than on others. Using bio informatics, drugs can be developed much faster to facilitate as well as accelerate the treatment of diseases.

The experiment on cloning is also an area of bio-informatics.

Study & Training

Bio informatics course covers : Introduction to genetics, molecular and cell biology, biochemistry, biotechnology, microbiology, evolutionary biology ; fundamentals of bio informatics ; branches and application areas of bio informatics ; use of software tools and databases available on the web ; Sequence analysis ; Protein modeling.

In addition to the above, depending on the standards of the institution, some introduction is also made in areas that influence the bio informatics :

Deoxyribose Nucleic Acid (DNA) Fingerprinting and computer science, MS Office, Linux, HTML and Perl. Students of bio informatics are expected to be proficient with knowledge of Java, Unix, C, C++, RDBMS such as Oracle and Sybase, CORBA, Perl, CGI and web scripting is required at the IT end.

Graduates in Computer Science, genetics, biochemistry, molecular biology, mathematics, physical chemistry, pharmaceuticals, floriculture, statistics, electrical engineering, biotechnology or organic chemistry are suitable for this programme.

The Government of India through the Department of Biotechnology is also taking up certain initial steps with regard to bio informatics education in India. The Department has drafted a National Bio informatics Policy 2002 and has collaborated with IIT Delhi to launch a two-year M Tech. Course. More than 70 universities are connected through a network for a first ever supercomputing facility in the country for Bio informatics and computational biology.

Centre for Bio technical Technology in collaboration with a private computer-training institute has launched a one-year postgraduate diploma course with an assurance that fifty per cent of the students would be absorbed in various projects. The qualifications for eligibility are M.Sc. in life science, MBBS, B.Tech or MCA.

INSTITUTES IN INDIA OFFERING BIOINFORMATICS

2009-11-15T21:06:00.000-08:00

BIC at Jawaharlal Nehru University, New Delhi :

Is among the pioneers of bioinformatics education in the nation.

BIC was set up in 1989 funded under the Biotechnology Information Systems Programme (BTIS) of DBT.

The center, which was functioning at the School of Computer Systems Sciences building from its inception in 1988, shifted to its present location in 1995.

The centre is well equipped with all the necessary facilities in terms of hardware, software, networking, etc.

BIC-JNU is offering :

one-year post MSc Diploma in Bioinformatics
PhD program in bioinformatics.

Computational genomics is the thrust area of BIC.

Bioinformatics Institute of India, Noida UP:

This institute is engaged in education and training services in bioinformatic sciences.

· It offers three PG Diploma courses via distance learning program to graduates, biologists, software professionals and professionals in other related fields.

These courses are provided through local study centers in cheminformatics, bioinformatics and biomedical informatics all over the country.

The total number of students enrolled in BII’s regular and distant learning programs has reached up to 5,000.

The courseware and methodologies of BII have been developed on par with international standards in consultation with industry experts and academicians.

It plans to set up of a state-of-the-art development center to provide a world class R&D facility to budding scientists.

The R&D areas of the organization are wide ranging from biotech to pharmaceuticals and medicine.

The institute assists in technology outsourcing, identification of joint ventures and marketing tie-ups for various products and services of pharmaceutical and other product organizations.

CBT at Anna University, Chennai:

The Center for Biotechnology (CBT) at Anna University, Chennai is one of the oldest biotech education institutions in the country.

Started in 1987 with funds from the University Grants Commission, Department of Biotechnology and Anna Univesity, CBT has played a pioneering role in biotech education.

In 1992, the center started a B Tech program in industrial biotechnology. It is supported by a large consortium of industries who have set up a corpus fund to the run the program. Recently, CBT got a boost with more funds donated by a well-known biotech company, Amersham Biosciences.

Two more positions of lecturers were created using these funds.

· CBT also offers a two-year M Tech (biotech) and PhD programs in biotechnology. Students are admitted through an entrance examination.

Anna University is the largest Technology University in the country with 222 engineering colleges in Tamil Nadu affiliated to it.

Center for DNA Fingerprinting and Diagnostics:

This is an autonomous institution supported by the Department of Biotechnology (DBT). It is India’s premier center providing services in the areas of DNA fingerprinting, molecular diagnostics, and bioinformatics.

CDFD is now poised to initiate basic research in fields relevant to its objectives.

CDFD is also the bioinformatics national node for the European Molecular Biology network (EMBnet).

The node currently provides bioinformatics services in the form of browsing biomolecular sequence databanks, macromolecular structure databank, genome and other useful databases.

Indraprastha University, Delhi:

Guru Gobind Singh Indraprastha University (GGSIU) is offering BTech course in bioinformatics.

It has some unique features in its course curriculum. This special academic program is a result of successful alliance between School of Information Technology and School of Biotechnology at GGSIU. The four-year B Tech program in Bioinformatics was first started in 1999 with 30 students. Recently, a fourth year student of School of Biotechnology, Amit Aggarwal, was selected for the PhD program in neuro sciences at Cottingham University, Germany. The university is also offering an integrated five-and-half year M Tech program in biotechnology.

University of Pune (MBA Biotechnology):

University of Pune has taken a path-breaking initiative to catalyze the biotechnology revolution. It has launched a two-year full-time MBA program in biotechnology in the academic year 2002-03. This is the first such program by any Indian university or institute. This is probably the first in Asia too. The course has been envisaged to create managers with domain specific knowledge for the biotech industry. The syllabus is based on the requirements of the industry. Sixty percent of the syllabus covers the managerial aspects and 40 percent biotechnology. The institute received overwhelming response for the course during the first year. The program admits 60 students each year. There will be a provision to admit international students also. The fee per year is Rs 18,500.

VG Vaze college, Mumbai:

Kelkar Education Trust’s VG Vaze College offers degree-level courses in biotechnology. The college has a state-of-the-art biotechnology lab and a scientific research center. The center under takes research in areas relating to medical, aromatics, cosmetics and environmental biotechnology. DST and University of Mumbai have bestowed the center as a recognized institution for research. Students will be admitted at the center for MSc (by research) and PhD in life sciences. The center is focusing on the development and mass propagation of medicinal and aromatic plants. The college, in collaboration with the research center and industry, has plans to offer certificate and diploma courses and training in perfumery, cosmetics, horticulture and tissue culture techniques, agricultural applications, etc. These courses are expected to commence from this academic year 2003-04. They will be offered to the science stream students. These diploma courses will be simultaneously offered to the students pursuing other degree.

Rai University, Bangalore:

Founded by Rai Foundation, this group has spread its educational arms across the nation with campuses in Bangalore, Behror, Bhopal, Dehradun, Gurgaon, Hyderabad, Kolkatta, Kosi, Lucknow, Mumbai, New Delhi, Pathankot and Pune. It is offering BSc in biotechnology, BSc( Hons) in environment management studies, Graduate Diploma (Hons) in biotechnology and patent laws and GPD (Hon) in forensic sciences. It also offers post graduate diploma in bioinformatics and in industrial microbiology.

RGCB, Kerala:

Rajiv Gandhi Centre for Biotechnology ( RGCB ) is an autonomous research institute that functions under the umbrella of Science, Technology and Environment department of the Government of Kerala. Established in its present form in 1994, RGCB has come to occupy an important position among the research institutes of the country devoted to research in the cutting edge areas of modern biology and biotechnology. It occupied a new building in January 2002. With the support of the DBT it has established research facilities required for carrying out modern biological research. Currently, the research activities are being carried out in seven major divisions: infectious diseases, plant molecular biology, environmental biotechnology, molecular human genetics, neurobiology, cancer biology and molecular endocrinology.

East West Institute of Technology:

Recognized by the Government of Karnataka, affiliated to Vishwe-shwaraiah Technological University and approved by All India Council for Technical Education (AICTE), New Delhi, the East-West institutions have been functioning in Bangalore for over three decades catering to the needs of quality and integrated system of education. All the institutions are having their own buildings and are centrally located.

The East West Educational institutions have earned very good reputation for providing meaningful education and for maintaining high standards—both in professional and nonprofessional courses.

East West offers Bachelor of Engineering courses in biotechnology engineering. This is an eight-semester course, affiliated to Vishweshwaraiah Technological University. It also offers graduate and postgraduate courses in biotechnology.

Edubiotech:

Edubiotech is a technology driven organization, providing world-class biotech technical support to educational institutions and corporate sectors. Edubiotech accelerates innovative ideas by providing good quality R&D and lab facilities. Each one has a place and is given the opportunity to excel in their field of interest.

Oxford Group, Bangalore:

The Oxford Group of Educational Institutions is a group that yearns at strengthening the concept of value based education. There are 22 educational institutions in all the branches of this institution. The Group has a separate College of Engineering as well as a college of Science in Bangalore. Today the Group is offering engineering as well as graduate and postgraduate programs in biotechnology. The Oxford College of Engineering is affiliated to Vishweshwaraiah Technological University and approved by AICTE, New Delhi and offers four-year BE in biotechnology engineering. The Oxford College of Science offers BSc in biotechnology and related fields such as microbiology, genetics and biochemistry. It also offers postgraduate courses in microbiology, biotechnology, and biochemistry.

RK Institute of Management and Computer Science

RK Institute of Management and Computer Science, recognized by the Government of Karnataka, affiliated to Bangalore University and approved by AICTE is offering courses in biotechnology at both under graduate and post graduate levels. The institute has a highly sophisticated research lab. The lab meets the requirements of the Bangalore University curriculum. The labs are well equipped with air conditioned tissue culture chamber and advanced models of laminar flow bench, UV-Vis Spectro photometer, incubators, autoclave, microscopes, electrophoretic units, optical instruments charts, models and other useful instrument to impart and enhance the practical aspects. Such progressive instruments and equipment contribute to the richness and variety of the courses offered by the institute.

Wageningen, Bangalore

Europe’s premier institution, Wageningen University, recently launched its educational module for biotechnology in Bangalore for the first time. Wageningen University in the Netherlands was established in 1918 and had over 10,000 students emerging from its portals annually. As one of the leading centers of education and research in plant, animal, environmental, agro-technological, food and social sciences, Wageningen had been offering quality programs in Asia. The mission statement of the university is to develop and disseminate scientific knowledge needed to sustain and supply society’s demands for sufficient healthy food and a good environment for humans, animals, and plants. Wageningen had tied up with two service providers in India—Bioinfraa and C-Lift, both Bangalore-based companies.

SS Infotech, Bangalore

SS Infotech started in the year 1999 as a non-profitable organization to provide high quality education to less fortunate students at an economical cost. Started with MSc (IT), BSc (IT), MBA and BBA courses, presently it is offering one year PG diploma in bioinformatics through Bioinformatics Institute of India, Noida. The objective of the course is to provide adequate knowledge and training to the student with hands on experience in the field of bio-informatics. The institute has developed a course keeping in mind the requirements of the industries and to equip the students with the latest advances in the field of bioinformatics. The institute also offers correspondence courses in biomedical-informatics, bioinformatics and cheminformatics.

Biotech Education Services &Training (BEST), Bangalore

BEST was started as a company incorporated to undertake activities in imparting quality research and training in biotechnology. The objective of BEST is to promote quality hands on training program in biotech education. Besides training the company has successfully forged into contract research services, protocol development, water analysis and waster water management. BEST is equipped with state of art facilities, competent and dedicated technical manpower. Its network has helps the students in placements and career counseling. It offers one-year PG diploma, short-term course of 10-50 days and advanced diploma courses of three months duration in biotechnology.

BIOINFORMATICS TOOLS IN LINUX

2009-11-15T21:02:00.000-08:00

Sure have to try it...!!!!!!!!!

QLUCORE

2009-11-11T00:52:00.000-08:00

ELECTRONIC PCR

2009-11-08T21:19:00.000-08:00

e-PCR identifies sequence tagged sites(STSs)within DNA sequences. Using e-PCR, you can search for sub-sequences that closely match the PCR primers and have the correct order, orientation, and spacing.

BLAST

2009-11-08T21:16:00.000-08:00

The Basic Local Alignment Search Tool (BLAST) for comparing gene and protein sequences against others in public databases, now comes in several types including PSI-BLAST, PHI-BLAST, and BLAST 2 sequences. Specialized BLASTs are also available for human, microbial, malaria, and other genomes, as well as for vector contamination, immunoglobulins, and tentative human consensus sequences.

Masters programes in various Bioinfo fields(United States)

2009-11-03T16:28:00.000-08:00

Arizona State University Tempe, Arizona

•MS in Computational Biosciences

Boston University Boston, Massachusetts

•Bioinformatics Graduate Program; MS, PhD

Brandeis University's Rabb School of Summer and Continuing Studies Waltham, Massachusetts

•MS in Bioinformatics

•Graduate Certificate in Bioinformatics

Carnegie Mellon University Pittsburgh, Pennsylvania

•Merck Computational Biology and Chemistry Program; BS, MS, PhD tracks

Columbia University New York, New York

•Medical Informatics; MS, PhD

Duke University Durham, North Carolina

•Center for Bioinformatics and Computational Biology; Postdoctoral, Certificate, PhD

Florida State University Tallahassee, FL

•Biomedical Mathematics; MS, PhD

George Mason University Fairfax, Virginia

•PhD in Computational Sciences and Informatics

•PhD in Bioinformatics

•MS in Bioinformatics

•MNPS in Bioinformatics, Biotechnology, and Forensic Biosciences

Georgetown University Washington, D.C.

•Biotechnology and Bioinformatics; MS track

Georgia Institute of Technology Atlanta, Georgia

•Bioinformatics; BS, MS, PhD tracks

•MS in Bioinformatics

•PhD in Bioinformatics

Harvard-MIT Division of Health Sciences and Technology Cambridge, Massachusetts

•Bioinformatics and Integrative Genomics; PhD track

Indiana University School of Informatics Bloomington, Indiana

•BS in Informatics

•MS in Bioinformatics

•MS in Chemical Informatics

International Bioinformatics and Computational Biology Programs From the Web site of the International Society for Computational Biology, a listing of universities worldwide that offer degrees in bioinformatics and computational biology.

Iowa State University Ames, Iowa

•Interdisciplinary PhD Program in Bioinformatics and Computational Biology; MS, PhD

Johns Hopkins University Baltimore, Maryland

•Program in Computational Biology; PhD track

Keck Graduate School Claremont, Southern California

•MS in Bioscience

Marquette University Milwaukee, Wisconsin

•Special Interdisciplinary Major/Minor (Dept. of Mathematics, Statistics, and Computer Science); BS

•Bioinformatics Graduate Program (with the Medical College of Wisconsin and UW Parkside); MS

McGill University Montreal, Canada

•Centre for Bioinformatics; BS minor; proposed MS and PhD

Medical College of Wisconsin Milwaukee, Wisconsin

•Bioinformatics Graduate Program; MS

Montana State University Bozeman, Montana

•Center for Computational Biology; MS, PhD track

New Jersey Institute of Technology Newark, New Jersey

•MS in Computational Biology

•PhD in Computational Biology

North Carolina State University Raleigh, North Carolina

•Statistical Genetics and Bioinformatics

•PhD in Bioinformatics

•Master of Bioinformatics

•Program in Statistical Genetics

Northeastern University Boston, Massachusetts

•Bioinformatics Essentials Graduate Certificate

•Graduate Certificate in Pharmacogenetics

Northern Illinois University DeKalb, Illinois

•Bioinformatics Specialization and Certificate; MS, Certificate

Oregon Health & Science University Portland, Oregon

•Medical Informatics; MS

Rensselaer Polytechnic Institute Troy, New York

•Interdisciplinary Program in Bioinformatics and Molecular Biology; BS, MS, PhD

Rice University’s Keck Center for Computational Biology Houston, Texas

•An Integrated Training Program: Bioinformatics and Computational Biology Training Program, and Computational Biology Research Training Program; PhD track

Rochester Institute of Technology Rochester, New York

•Bioinformatics and Biotechnology Programs; BS, MS

Rutgers University Camden, New Jersey

•Graduate Studies in Computational Molecular Biology; PhD

Stanford University Stanford, California

•Biomedical Informatics; MS, PhD

•Bioinformatics Certificate

University of California, Davis Davis, California

•Graduate Program in Medical Informatics; MS

•Designated Emphasis in Biotechnology; PhD

•Summer Short Courses in Bioinformatics and Proteomics

University of California, Irvine Irvine, California

•Informatics in Biology and Medicine; MS and PhD track

University of California, San Diego San Diego, California

•Interdisciplinary Bioinformatics Program; PhD

•Certificate in Bioinformatics

University of California, San Francisco San Franciso, California

•Graduate Program in Biological and Medical Informatics; MS, PhD

University of California, Santa Cruz Santa Cruz, California

•Program in Bioinformatics; BS; Proposed MS and PhD

University of Colorado at Denver Denver, Colorado

•Center for Computational Biology; Certificate, MS, PhD

University of Illinois, Chicago Chicago, Illinois

•Bioinformatics; BS, MS, PhD

University of Massachusetts, Lowell Lowell, Massachusetts

•Bioinformatics; BS, MS, PhD

University of Medicine and Dentistry of New Jersey Newark, New Jersey

• Graduate Programs in Biomedical Informatics; PhD, MS, MSN, certificate

University of Memphis Memphis, Tennessee

•Masters Degree Concentration in Bioinformatics

University of Michigan Ann Arbor, Michigan

•Bioinformatics; MS, PhD

University of Minnesota Twin Cities, Minnesota

•Graduate Program in Bioinformatics; MS and PhD minor

University of Nebraska, Omaha Omaha, Nebraska

•Bioinformatics; MS and PhD track

University of New South Wales Sydney, Australia

•BS in Engineering (Bioinformatics)

University of Pennsylvania Philadelphia, Pennsylvania

•Computational Biology; BS, MS, PhD track

University of Southern California Los Angeles, California

•MS in Computational Molecular Biology

•Computational Biology and Bioinformatics; PhD track

University of Texas, Austin Austin, Texas

•Graduate Program in Cell & Molecular Biology, with specialized track in Bioinformatics; PhD track

University of Texas, El Paso El Paso, Texas

•Bioinformatics; MS

University of the Sciences in Philadelphia Philadelphia, Pennsylvania

•Bioinformatics; BS, MS

University of Washington Seattle, Washington

•Biomedical and Health Informatics; MS; PhD and certificates proposed

•Computational Molecular Biology; PhD track

University of Waterloo Ontario, Canada

•Bioinformatics; BS, MS, PhD

University of Wisconsin Madison, Wisconsin

•Biostatistics and Medical Informatics; MS, PhD

•Graduate Certificate/Capstone Certificate in Bioinformatics; Certificate programs for graduate and post-doctoral students

Vanderbilt University Nashville, Tennessee

•Graduate Program in Biomedical Informatics; MS, PhD

Virginia Polytechnic Institute and State University Blacksburg, Virginia

•Graduate Options in Bioinformatics; MS and PhD track

Washington University in Saint Louis

Saint Louis, Missouri

•Computational Biology; PhD

Masters programes in various Bioinfo fields

2009-11-03T16:19:00.000-08:00

California State University Channel Islands Camarillo,

CA Programs in Biotechnology

George Mason University Fairfax,
VA College of Science
The George Washington University Washington, DC Program in Genomics, Proteomics, and Bioinformatics
Georgia Institute of Technology Atlanta, GA School of Biology
Iowa State University of Science and Technology Ames, IA Bioinformatics and Computational Biology Program
The Johns Hopkins University Baltimore, MD Part-time Program in Bioinformatics
The Johns Hopkins University Baltimore, MD Program in Computer Science
North Carolina State University Raleigh, NC Program in Bioinformatics
Oregon Health & Science University Portland, OR Department of Medical Informatics and Clinical Epidemiology
Polytechnic Institute of NYU Brooklyn, NY Major in Bioinformatics University of California, Santa Cruz Santa Cruz, CA Program in Bioinformatics
University of Illinois at Urbana–Champaign Urbana,
IL Graduate School of Library and Information Science
University of Southern California Los Angeles, CA Programs in Molecular Biology
The University of Toledo Toledo, OH Program in Bioinformatics and Proteomics/Genomics
University of Utah Salt Lake City, UT Department of Biomedical Informatics
Virginia Commonwealth University Richmond, VA Centre for the Study of Biological Complexity
Clemson University Clemson, SC School of Computing Clemson University Clemson, SC Program in Biochemistry and Molecular Biology Clemson University Clemson,SC Program in Genetics
Columbia University New York, NY Graduate School of Arts and Sciences at the College of Physicians and Surgeons
New York Medical College Valhalla, NY Program in Health Informatics Stony Brook University,
State University of New York Stony Brook, NY Department of Biomedical Engineering

Stony Brook University, State University of New York Stony Brook, NY Department of Computer Science Stony Brook University,

State University of New York Stony Brook, NY Department of Electrical and Computer Engineering

The University of Toledo Toledo, OH Department of Bioengineering The University of Toledo Toledo, OH Department of Chemistry

Boston University Boston, MA Intercollegiate Program in Bioinformatics
Brandeis University Waltham, MA Bioinformatics Program
California State University, Dominguez Hills Carson, CA Department of Biology

Classes in Bioinformatics and Computational Biology

2009-11-03T16:05:00.000-08:00

Africa:

South Afica

South African National Bioinformatics Institute, Honours Bioinformatics Course

Asia

Israel

Technion, Algorithms for Computational Biology (236606)

Tel Aviv University, Algorithms in Molecular Biology

Australia

Australian National Genomic Information Service courses in Bioinformatics

University of Melbourne, Macromolecular Structure ∓ Bioinformatics (521-203)

Europe

France

Pasteur Institute, Bioinformatics

Norway

Bergen University, Bioinformatics

United Kingdom

University of Nottingham, Bioinformatics Tools

Oxford University, Bioinformatics Centre Courses

North America

Canada

Ontario

University of Waterloo, Computational Biology (CS798)

United States

Arizona

University of Arizona, Bioinformatics and Genomic Analysis (MCB 416/516)

California

University of California-Santa Cruz, Bioinformatics (CMP 243)

University of California-Santa Cruz, Bioinformatics Research Seminar (CMP 280)

University of California-San Diego, Computational Biology (CSE 290)

Stanford Center for Professional Development, Academic Courses

Connecticut

Yale University, Bioinformatics(MB∓B 447b/747b)

Delaware

University of Delaware, Bioinformatics (ANSC 667)

Indiana

Indiana University Purdue University Indianapolis, Introduction to Bioinformatics (CSCI 590)

Purdue University, Topics in Bioinformatics (CS 690B)

Massachusetts

Boston University, BF 527: Bioinformatic Applications

Harvard University, Biophysics 101: Genomics and Computational Biology

MIT, 18.417 Introduction to Computational Molecular Biology

Missouri

University of Missouri, Bioinformatics (CECS 401)

Washington University at St. Louis

Computational Molecular Bioinformatics (Bio 5495/BME 537)

Biology 560, Introduction to Bioinformatics

New Mexico

New Mexico State University, Bioinformatics and Genome Analysis (MOLB 550)

Pennsylvania

Carnegie Mellon University, Computational Biology (CB03-510)

Washington

University of Washington, CSE 527: Computational Biology

Washington, D.C.

Howard University: Computational Biology

LIST OF UNIVERSITIES OFFERING DEGREES IN BIOINFORMATICS

2009-11-03T15:50:00.000-08:00

Australia
- South Australia
  - Bachelor's Program in Bioinformatics at Flinders University
  - The International Office
    Flinders University, GPO Box 2100, Adelaide SA 5001
    Tel (+ 618) 8201 2727
    Fax (+ 618) 8201 3177
    Email: Intl.Office@flinders.edu.au
  - Europe

Downloads and Upgrades

2009-11-02T21:33:00.000-08:00

As part of its new SOLiD3 Plus sequencing system, Life Technologies has released BioScope, software that provides an "integrated framework for data analysis,"

GenBank 174.0 is available via FTP from the National Center for Biotechnology.

The new release contains 108,560,236,506 base pairs of non-whole-genome-shotgun sequence and 149,348,923,035 base pairs of WGS sequence. Uncompressed, the new release flatfiles require roughly 416 GB (sequence files only) or 445 GB including the 'short directory,' 'index,' and the *.txt files.

The total number of sequence data files increased by 31, and the number of index files by three with this release.

A new haplogroup qualifier, which is a group of similar haplotypes that share a common ancestor with a SNP mutation, has been introduced as of this GenBank release.

NCBI noted that because GSS sequences are maintained in two different systems, there is a "discrepancy between the filenames and file headers" for 78 of the GSS flatfiles in release 174.0.

NCBI has also released Blast 2.2.22, which includes new Blast+ command-line applications built with the NCBI C++ toolkit.

Other changes include a new entrez_query command line option for restricting remote BLAST databases, user interface improvements to windowmasker, a provision for long words with blastp, and added support for best-hit algorithm parameters in strategy files.

Temis has launched Luxid 5.1, the latest version of its content mining application that has been enhanced so it is easier-to-use, with "more powerful analytics."

Luxid 5.1 offers content enrichment capabilities through Temis' new software-as-a- service offering. The application also has an enhanced knowledge browser, with "wider" methods to customize Skill Cartridges to include "vocabulary lists and entity attributes, combining them with semantic rules," the company said.

Tripos has released version 5.0 of its Benchware Discovery 360 platform, which includes expanded data access and analysis capabilities with "full featured forms-based querying and browsing, a data access dashboard for data searches, and a range of integration options," the company said.

Metabolic profiling

2009-11-02T21:27:00.000-08:00

DTC Genetic testing...??

2009-11-02T21:24:00.000-08:00

What is direct-to-consumer genetic testing?

Traditionally, genetic tests have been available only through healthcare providers such as physicians, nurse practitioners, and genetic counselors. Healthcare providers order the appropriate test from a laboratory, collect and send the samples, and interpret the test results. Direct-to-consumer genetic testing refers to genetic tests that are marketed directly to consumers via television, print advertisements, or the Internet. This form of testing, which is also known as at-home genetic testing, provides access to a person’s genetic information without necessarily involving a doctor or insurance company in the process.

If a consumer chooses to purchase a genetic test directly, the test kit is mailed to the consumer instead of being ordered through a doctor’s office. The test typically involves collecting a DNA sample at home, often by swabbing the inside of the cheek, and mailing the sample back to the laboratory. In some cases, the person must visit a health clinic to have blood drawn. Consumers are notified of their results by mail or over the telephone, or the results are posted online. In some cases, a genetic counselor or other healthcare provider is available to explain the results and answer questions. The price for this type of at-home genetic testing ranges from several hundred dollars to more than a thousand dollars.

The growing market for direct-to-consumer genetic testing may promote awareness of genetic diseases, allow consumers to take a more proactive role in their health care, and offer a means for people to learn about their ancestral origins. At-home genetic tests, however, have significant risks and limitations. Consumers are vulnerable to being misled by the results of unproven or invalid tests. Without guidance from a healthcare provider, they may make important decisions about treatment or prevention based on inaccurate, incomplete, or misunderstood information about their health. Consumers may also experience an invasion of genetic privacy if testing companies use their genetic information in an unauthorized way.

Genetic testing provides only one piece of information about a person’s health—other genetic and environmental factors, lifestyle choices, and family medical history also affect a person’s risk of developing many disorders. These factors are discussed during a consultation with a doctor or genetic counselor, but in many cases are not addressed by at-home genetic tests. More research is needed to fully understand the benefits and limitations of direct-to-consumer genetic testing.

UCSC Genome browser..

2009-10-19T07:07:00.000-07:00

This site contains the reference sequence and working draft assemblies for a large collection of genomes. It also provides a portal to the ENCODE project.The UCSC Genome Browser is developed and maintained by the Genome Bioinformatics Group, a cross-departmental team within the Center for Biomolecular Science and Engineering (CBSE) at the University of California Santa Cruz (UCSC).

This application includes following features and software applications:

BIOINFORMATICS COMPANIES

2009-10-13T20:17:00.001-07:00

InCyte
Informagen
InforSense
Ingenovis
Interactiva
Inpharmatica
Insightful Corporation
Insilico Biotechnology
In Silico Labs
Insilico Software
InvenioBioSolutions
LabLogic
Omnigon Technologies
OpenEye
OriGenel
Packard BioChip Technologies
Partek
PharmaDM
Proinformatix
Protein Mechanics
ProSanos
Proteom
QGene
RabbitHutch
Receptor Science
Redstorm Scientific

Bioinformatics Services
Bioinformatics Solutions
BioIT
BioLateral
BioMax Informatics
Biomedical Computing
Biomedical Informatics
BioSoft
BioSolve
Biotique Systems
BioTools
BioWisdom
Caesar Software
Chang Bioscience
Eragen
Fractal Genomics
Gemini Genomics
GeneCodes
GeneData
Gene-IT
GeneticXchange
Geneva Bioinformatics
GenMatrix
Genomica
Genomix
Genops Bioinformatics
GenStruct
Hitachi Life Science Division
LION BioScience
Mantik Bioinformatik
Matrix Science
MDL Information Systems
METabolic EXplorer
MetaWorks
MicroDiscovery
MiraiBio
Molecular Application Group
Molecular Mining
Molecular Networks
MolecularWare
MPI Software Technology
Neomorphic
NetGenics
Net-ID
Ocimum Biosolutions
Rosetta Biosoftware
Science Factory
Scinova
Silicon Graphics
Silico Insights
Simulations Plus
SoftBerry
Southwest Parallel Software
Strand Genomics
Tripos
Turbo Genomics
Virtual Genetics
Visipoint
VizXlabs
Waban Software
WebGenetics
WireWorks West
X-MINE
Xpogen

PROTEIN MODELLING

2009-10-13T20:08:00.001-07:00

The process of evolution has resulted in the production of DNA sequences that encode proteins with specific functions. In the absence of a protein structure that has been determined by X-ray crystallography or NMR spectroscopy, researchers can try to predict the three-dimensional structure using protein or molecular modeling. This method uses experimentally determined protein structures (templates) to predict the structure of another protein that has a similar amino acid sequence (target).

Although molecular modeling may not be as accurate at determining a protein's structure as experimental methods, it is still extremely helpful in proposing and testing various biological hypotheses. Molecular modeling also provides a starting point for researchers wishing to confirm a structure through X-ray crystallography and NMR spectroscopy. As the different genome projects are producing more sequences, and because novel protein folds and families are being determined, protein modeling will become an increasingly important tool for scientists working to understand normal and disease-related processes in living organisms.

METABOLOMICS.......???

2009-10-13T20:04:00.000-07:00

Metabolomic involves the systematic estimation of small molecules from a range of organisms, followed by statistical analyses and other investigations of that large quantity of data.

The draft sequences for the human genome has focused attention on the tremendous effort still required to understand the function of expressed genes, and the way in which genes and the proteins they encode interact within cells and organisms. Metabolomics, or the global analysis of cellular metabolites, provides a powerful new tool for gaining insight into functional biology. Snapshots of the level of small molecules within a cell, and how those levels change under different conditions, are complementary to gene expression and proteomic studies, and are actively being applied to studies of infectious diseases, production and model organisms, as well as human cells and plants.

It requires analytical techniques such as chromatography, molecular spectroscopy and mass spectrometry, coupled with multivariate data analysis methods. The aim of metabolomics is to obtain the widest possible coverage, in terms of the type and number of compounds analysed. This is achieved by making use of several, complementary analytical methods.

For target compound analysis and metabolic profiling, main techniques are gas chromatography (GC), high performance liquid chromatography (HPLC) and nuclear magnetic resonance (NMR). These approaches rely on chromatographic separations, often coupled with well-developed calibrations for specific analytes.

In metabolic fingerprinting, samples are analysed as crude extracts without any separation step, using NMR, direct injection mass spectrometry (MS), or Fourier transform infrared (FT-IR) spectroscopy. These fingerprinting approaches are often combined with multivariate analysis, to get the most out of the data.

Gas Chromatography (GC)

Developments involving gas chromatography have been responsible for the recent upsurge of interest in plant metabolomics. GC provides high-resolution compound separations, and can be used in conjunction with a flame ionisation detector (GC/FID) or a mass spectrometer (GC/MS). Both detection methods are highly sensitive and universal, able to detect almost any organic compound, regardless of its class or structure. However, most of the metabolites found in plant extracts are too involatile to be analysed directly by GC methods. The compounds have to be converted to less polar, more volatile derivatives before they are applied to the GC column. Efficient derivatisation methods are available, but relatively low sample throughput is a drawback of the GC method, particularly when there are many samples to be examined.

High Performance Liquid Chromatography (HPLC)

HPLC, with UV detection, is probably the most common method used for targeted analysis of plant materials, and for metabolic profiling of individual classes. A derivatisation step is not essential (unless needed for detection), since involatile and volatile substances may be measured equally well. Selection of compounds arises initially from the type of solvent used for extraction (as with all methods that use an extraction step), and then from the type of column and detector. For example HPLC/UV will only detect compounds with a suitable chromophore; a column selected for its ability to separate one class of compounds will not generally be useful for other types. HPLC profiling methods all rely to a great extent on comparisons with reference compounds. The full UV spectrum (measured for each peak when UV-diode array detectors are used) gives some useful information on the nature of compounds in complex profiles, but often indicates the class of the compound rather than its exact identity.

Nuclear Magnetic Resonance (NMR)

In principle, proton (¹H) NMR can detect any metabolites containing hydrogen. Signals can be assigned by comparison with libraries of reference compounds, or by two-dimensional NMR. ¹H NMR spectra of plant extracts are inevitably crowded not only because there is a large number of contributing compounds, but also because of the low overall chemical shift dispersion. ¹H spectra are also complicated by spin-spin couplings which add to signal multiplicity, although they are an important source of structural information. In ¹³C NMR, the chemical shift dispersion is twenty times greater and spin-spin interactions are removed by decoupling. Despite these advantages, the low sensitivity of ¹³C NMR prevents its routine use with complex extracts. Sensitivity can be enhanced when seedlings are grown in the presence of ¹³C enriched carbon dioxide, but this is obviously only an option for laboratory based studies.

Direct Injection Mass Spectometry

It is also possible to obtain metabolite 'mass profiles' without any chromatographic separation. Such profiles are obtained by injecting crude extracts into the electrospray ionisation source of a high-resolution mass spectrometer. This technique generates mainly protonated, deprotonated or adduct molecules, such as [M+H]⁺, [M+cation]⁺ or [M-H]^- for each species present in the mixture, with little or no fragmentation. Thus a fingerprint spectrum is obtained with a single peak for each metabolite, separated from other metabolites according to (accurate) molecular mass. The fingerprint can be used as a classification tool, for example in taxonomy. Some mass analysers are capable of ultra-high resolution and permit the mass to be determined to four or five decimal places. This allows unique formulae to be assigned to peaks with masses of a few hundred or so. The coupling of high sensitivity with high resolution provides a method of determining a rough estimate of the number of metabolites present and a valuable first indication, from the formulae, of their identities. Its main weakness is the inability to separate isomers of the same molecular mass.

Multivariate Analysis

Plant extracts are very complex in composition and, if many samples are examined, it is difficult to make meaningful comparisons of large numbers of spectra or chromatograms 'by eye'. Multivariate statistical methods can be extremely useful, as they are able to compress data into a more easily managed form. This can assist in visualizing, for example, how a given sample relates to other samples - a central issue in metabolomics. Multivariate analysis is practically essential in the fingerprinting approaches, but is also helpful in techniques where individual metabolites are explicitly quantified (eg GC/MS).

Principal component analysis (PCA) is a well-known and effective method of data compression. PCA transforms the original data (e.g. intensity values in a spectrum) into a set of 'scores' for each sample, measured with respect to the principal component axes ('loadings'). The PC scores replace the original variates, and are: (i) ordered, with successive PCs accounting for decreasing amounts of variance, and (ii) orthogonal, with no correlation between the scores on different axes. Due to these properties, a small number of PCs can replace the many original variates without much loss of information.

Scatter plots of the scores on the first few PC loadings provide an excellent means of visualizing and summarising the data and often reveal patterns that cannot be discerned in the original data. The scores plots may show clustering of similar samples, separation of different sample types, or the presence of outliers. Plots of the loadings themselves may be used to explore which compounds are most responsible for, say, separating samples into groups: the most important compounds (peaks) tend to correspond to high absolute loading values.

PHYLOGENETICS

2009-10-13T20:00:00.000-07:00

Phylogenetic systematics is that field of biology that does deal with identifying and understanding the evolutionary relationships among the many different kinds of life on earth, both living (extant) and dead (extinct).

Systematics describes the pattern of relationships among taxa and is intended to help us understand the history of all life. But history is not something we can see—it has happened once and leaves only clues as to the actual events. Scientists use these clues to build hypotheses, or models, of life's history. In phylogenetic studies, the most convenient way of visually presenting evolutionary relationships among a group of organisms is through illustrations called phylogenetic trees.

Molecular phylogenetics

The field of molecular phylogenetics has grown, both in size and in importance, since its inception in the early 1990s, attributable mostly to advances in molecular biology and more rigorous methods for phylogenetic tree building. The importance of phylogenetics has also been greatly enhanced by the successful application of tree reconstruction, as well as other phylogenetic techniques, to more diverse and perplexing issues in biology. Phylogenies are used essentially by drawing inferences from the structure of the tree or from the way the character states map onto the tree. Broadly speaking, the relationships established by phylogenetic trees often describe a species' evolutionary history and, hence, its phylogeny, the historical relationships among lineage's or organisms or their parts, such as their genes.

Molecular phylogenetics attempts to determine the rates and patterns of change occurring in DNA and proteins and to reconstruct the evolutionary history of genes and organisms. Two general approaches may be taken to obtain this information. In the first approach, scientists use DNA to study the evolution of an organism. In the second approach, different organisms are used to study the evolution of DNA. Whatever the approach, the general goal is to infer process from pattern: the processes of organismal evolution deduced from patterns of DNA variation and processes of molecular evolution inferred from the patterns of variations in the DNA itself.

Studies of gene and protein evolution often involve the comparison of homologs, sequences that have common origins but may or may not have common activity. Sequences that share an arbitrary level of similarity determined by alignment of matching bases that are homologous. These sequences are inherited from a common ancestor that possessed similar structure, although the ancestor may be difficult to determine because it has been modified through descent.

A straightforward phylogenetic analysis consists of four steps:

Alignment—building the data model and extracting a dataset.
Determining the substitution model—consider sequence variation.
Tree building.
Tree evaluation.

SEQUENCE ALIGNMENT

2009-10-13T19:57:00.000-07:00

Alignment is the result of a comparison of two or more gene or protein sequences in order to determine their degree of base or amino acid similarity. Sequence alignments are used to determine the similarity, homology, function or other degree of relatedness between two or more genes or gene products. The likelihood that the two sequences are related is represented in an alignment score. This score is calculated by totaling the scores for each matched pair of residues at each position in the alignment.

The general approach for similarity searching involves the use of a set of algorithms such as the BLAST programs to compare a query sequence to all the sequences in a specified database. Comparisons are made in a pairwise fashion. Each comparison is given a score reflecting the degree of similarity between the query and the sequence being compared. The higher the score, the greater the degree of similarity. The similarity is measured and shown by aligning two sequences. Alignments can be global or local. A global alignment is an optimal alignment that includes all characters from each sequence, whereas a local alignment is an optimal alignment that includes only the most similar local region or regions. Discriminating between real and artifactual matches is done using an estimate of probability that the match might occur by chance. The similarity itself, is not a sufficient indicator of function.

Blast

The BLAST programs (Basic Local Alignment Search Tools) are a set of sequence comparison algorithms introduced in 1990 that are used to search sequence databases for optimal local alignments to a query. The BLAST programs improved the overall speed of searches while retaining good sensitivity (important as databases continue to grow) by breaking the query and database sequences into fragments ("words"), and initially seeking matches between fragments. The initial search is done for a word of length "W" that scores at least "T" when compared to the query using a given substitution matrix. Word hits are then extended in either direction in an attempt to generate an alignment with a score exceeding the threshold of "S". The "T" parameter dictates the speed and sensitivity of the search.

The quality of each pair-wise alignment is represented as a score and the scores are ranked. Scoring matrices are used to calculate the score of the alignment base by base (DNA) or amino acid by amino acid (protein). A unitary matrix is used for DNA pairs because each position can be given a score of +1 if it matches and a score of zero if it does not. Substitution matrices are used for amino acid alignments. These are matrices in which each possible residue substitution is given a score reflecting the probability that it is related to the corresponding residue in the query. The alignment score will be the sum of the scores for each position. Various scoring systems (e.g. PAM, BLOSUM and PSSM) for quantifying the relationships between residues have been used.

PROTEIN ANALYSIS

2009-10-13T19:54:00.000-07:00

Proteins are responsible for maintaining all cellular functions and their production is governed by the genetic code. A disease may be the result of gene mutations that cause changes in the structure and activity of a protein. Therefore, characterising proteins and understanding their function is important for identifying novel drug targets and designing more effective medicines. Protein analysis is the study of the total protein content of a cell type or organism. It gives a better understanding of the function of genes and the proteins for which they code. This knowledge is of fundamental importance for the development of molecular medicine. Protein analysis is a complex process that requires multiple steps and advanced technologies. Two of the most important technologies are Mass Spectometry and 2D gel elctroforesis.

Mass Spectometry

Matrix-assisted laser desorption/ionisation-time of flight mass spectrometry (MALDI-TOF MS) is a relatively novel technique in which a co-precipitate of an UV-light absorbing matrix and a biomolecule is irradiated by a nanosecond laser pulse. Most of the laser energy is absorbed by the matrix, which prevents unwanted fragmentation of the biomolecule. The ionised biomolecules are accelerated in an electric field and enter the flight tube. During the flight in this tube, different molecules are separated according to their mass to charge ratio and reach the detector at different times. In this way each molecule yields a distinct signal. The method is used for detection and characterisation of biomolecules, such as proteins, peptides, oligosaccharides and oligonucleotides, with molecular masses between 400 and 350,000 Da. It is a very sensitive method, which allows the detection of low amounts of molecules.

Protein identification by this technique has the advantage of short measuring time (few minutes) and negligible sample consumption (less than 1 pmol) together with additional information on microheterogeneity (e.g. glycosylation) and presence of by-products. Although molecular biology has provided powerful techniques for DNA analysis, this is not yet reflected in protein analysis. Genome sequencing has yielded a wealth of information on predicted gene products, but for the majority of the expressed proteins no function is known. Proteomics is an important new field of study of protein properties (expression levels, interactions, post-translational modifications etc.) and thus can be described as functional genomics at the protein level. The mass accuracy of MALDI-TOF MS will be sufficient to characterise proteins (after tryptic digestion) from completely sequenced genomes.

(http://www-micrbiol.sci.kun.nl/tech/malditof.html)

2D Gel electrophoresis

By comparing the proteinaceous composition (the proteome) of microorganisms, the contribution of differentially expressed proteins to specific microbial traits can be assessed. The proteome is visualised by 2D-gelelectrophoresis and proteins of interest can be identified on the genome by MALDI-TOF MS. Two dimensional gel electrophoresis separates proteins first on their isoelectric point and in the second dimension on their molecular mass. Through hydration proteins are absorbed by dried gelstrips which carry an immobilised pH gradient. The hydrated first dimensional gel is subjected to a strong electric field. Acid proteins at the alkaline side of the gel will dissociate and become negatively charged. Because of the electric field these proteins will migrate to the positive pole (the acidic side of the gel). Proteins will reach a point where they become neutralised by the gel, lose their net charge and do not migrate further. The same scenario applies to basic proteins. With the currently available equipment it is possible to reproducably separate proteins which differ in only a single pH unit over 24 cm.

GENOME SEQUENCING

2009-10-13T19:46:00.000-07:00

Sequencing is the method to get the order of DNA basepairs of a DNA fragment. This fragment can be small (like 500 bp) or a whole genome of an organism. One of the major methods of DNA sequencing in known as chain termination sequencing, dideoxy sequencing, or Sanger sequencing after its inventor biochemist Frederick Sanger. The method is elegantly simple. While DNA chains are normally made up of deoxynucleotides (dNTPs), the Sanger method uses also dideoxynucleotides.

Dideoxynucleotides (ddNTPs) are missing a hydroxy (OH) group at the 3' position. This position is normally where one nucleotide attaches to another to form a chain. If there is no OH group in the 3' position, the additional nucleotides cannot be added to the chain, thus interrupting chain elongation. A small fraction of one of the bases will contain stopnucleotides. This means that everytime that nucleotide is added, a fraction of the strings will stop growing and keep the length it has reached at that time. When you first devide your sample in four tubes, you can do this procedure four times. This means with all the four basepairs. When you run these four samples on a gel, you can read the sequence from the smallest fragment to the largest..

Since 1986 the process of reading the sequence can be done with an automated fluorescence sequencer. The automated sequencer runs on the same principle as the Sanger method (dideoxynucleotide chain termination). But here a laser constantly scans the bottom of the gel, detecting the bands that move down the gel. Where the manual method uses radioactive labeling, automated cappilary sequencing uses fluorescent tags on the ddNTPs (a different dye for each nucleotide). This makes it possible for all four reactions (dGTP, dATP, dCTP, and dTTP) to be run in one lane and increases the speed of the process four times. The runs are fully automated nowadays, and the gels are replaced by cappilaries. This is a very efficient method and is very useful for fast and automatically sequencing of large DNA fragments.

More about sequencing on the history page.

There are two methods of deviding the genome in smaller parts for large-scale sequencing:

The Conventional Method
Shotgunning

The Conventional Method

Once scientists use PCR to create many copies of a single strand of the DNA fragment they begin to synthesis the location of each letter. The original method involves the following:

Step 1: Place identical DNA strands into four test tubes, each one containing a ddNTP that resembles one of the four nucleotides in DNA (A, T, C, G) and lots of dNTPs (which are free-floating nucleotides) that also resemble the DNA letter, except they do not build functioning DNA chains.
Step 2: Then add the polymerase enzyme and a known primer DNA, similar to the one used in PCR, to the test tubes. The primer marks the beginning of each sequenced string of DNA. In each test tube, the dNTPs, which act like letters in a DNA bond with the complementary nucleotide, thereby copying the original strand. However, the ddNTP in each test tube also bond with the DNA fragments at a probable ratio of 1 bond 100 times it could bond. Each time this happens the copy terminates, thereby creating millions of DNA strings of differing length that start with the same primer and each ending with the same ddNTP nucleotide. This is determined by which of the four test tubes being analysed, since only one of the ddNTPs are in each test tube.
Step 3: Then use Gel Electrophoresis to arrange the DNA pieces from largest to smallest and X-ray detection to determine the length of the strings.

This is the method that was first developed. Fortunately, contemporary institutes no longer use this exact method but one that is four times faster. By using ddNTPs tagged with fluorescents they no longer need four test tubes, but a single one, which contains all four fluorescent ddNTPs. They then rely on computers to detect the different colours of the ending pieces of the DNA segments after Gel Electrophoresis to determine the letters and length of the DNA chain. More information is given in the History part of this website.

The Shotgun Method

For using the shotgunning method, first A genomic library is made by cutting a whole genome with restriction enzymes and inserting each piece into a bacterium, which is then cloned. These segments are then detected and ordered by computers.

Step 1: Blend the post PCR DNA string that is to be sequenced into little fragments.
Step 2: Place the new segments into a test tube filled with the polymerase enzyme and a primer bit of DNA.
Step 3: Now, like in the original method, let the DNA rebuilds itself with the dNTPs and the fluorescent ddNTPs tagged in the test tubes until all the strings have terminated.
Step 4: Use Gel Electrophoresis to sort the fragments by size and a computer to record the many DNA fragments lengths. Lastly the computer should process and realign these fragments into the original string, thereby sequencing it.

The advantage of using smaller fragments of the larger DNA chain is that since the time required sequencing the DNA has been greatly shorted. Therefore, machines can sequence the fragments many times in order to achieve a high level of accuracy, by using sequencing software which lines up the DNA by finding overlapping letter sequences in the many pieces after the gel electrophoresis. However, scientists have experienced a few problems when 'shotgunning' DNA strings with many common and reoccurring sequences; therefore researchers using the 'shotgunning' process often sequence the DNA both backwards and forwards to return more accurate results. The following graphic shows how the small DNA fragments are realigned to assemble the full sequence.

Actuality billions of overlapping DNA pieces need to be aligned for an acceptable accuracy. Fortunately, by highly automating the 'shotgunning' method of sequencing, scientists are quickly organising enough DNA pieces to return precise chains faster than competitors using more conventional techniques.

ESTs are also very useful in the mapping of a genome. The 3' ESTs serve as a common source of STSs because of their likelihood of being unique to a particular species and provide the additional feature of pointing directly to an expressed gene. These ESTs gives much information as a reliable genomic landmark for genome mapping.

There are two types of shotgunning:

Hierarchical (clone by clone)
Whole genome

Hierarchical shotgunning means, the genome will be broken up into overlapping segments whose relative locations were known; each segment was then shotgun-sequenced. Using the whole genome shotgunning technique, the whole genome will be broken in pieces several times and all pieces are sequenced. Both types detect and order the segments by computer after sequencing each segment. The whole genome shotgunning was invented by Craig Venter's TIGR and the technique was used to sequence several genomes, like the influenza microbe, Drosophila melanogaster and Venter's part of the human genome.

MICROARRAY TECHNOLOGY

2009-10-12T18:52:00.001-07:00

Microarrays exploit the preferential binding of complementary single-stranded nucleic acid sequences. A microarray is typically a glass slide, on to which DNA molecules are attached at fixed locations (spots). There may be tens of thousands of spots on an array, each containing a huge number of identical DNA molecules (or fragments of identical molecules), of lengths from twenty to hundreds of nucleotides. (According to quick napkin calculations by Wilhelm Ansorge and John Quackenbush in Schnookeloch in Heidelberg on 4 October 2001, the number of DNA molecules in a microarray spot is 10⁷-10⁸). For gene expression studies, each of these molecules ideally should identify one gene or one exon in the genome, however, in practice this is not always so simple and may not even be generally possible due to families of similar genes in a genome.

Microarrays that contain all of the approximate 6000 genes of the yeast genome have been available since 1997. The spots are either printed on the microarrays by a robot, or synthesised by photolithography (similarly as in computer chip productions) or by ink-jet printing. The spot diameter is of the order of 0.1 mm, for some microarray types can be even smaller.

There are different ways how microarrays can be used to measure the gene expression levels. One of the most popular microarray applications allows the comparison of gene expression levels in two different samples, e.g., the same cell type in a healthy and diseased state. This is called cDNA microarray. An other array technique is oligo arrays.

cDNA Microarray

In the preparation of a cDNA microarray, the total mRNA from the cells in two different conditions is extracted and reverse transcription PCR (RT-PCR) is used to convert the RNA transcripts into cDNA. The cDNAs are usually composed of 500 -2000 basepairs long. The complete pool of cDNA is representative of transcriptional events in the tissue source of the RNA. The genes that were being actively transcribed in the sample will have mRNA copies that should have been first purified and then copied into cDNA during the RT-PCR step. The reverse transcription event for the control and experimental mRNA are identical in every step except one, and it is this step that enables differential gene expression to be determined. Nucleotides labelled with a green fluorescent dye Cy3 are incorporated into the control cDNA, while nucleotides labelled with a red fluorescent dye Cy5 are incorporated into the experimental DNA. After preparation, both probes are mixed and allowed to hybridise to the glass slide. Excess hybridisation buffer is washed off following an overnight incubation, and the slides are then ready to be scanned. Labelled gene products from the extracts hybridise to their complementary sequences in the spots due to the preferential binding - complementary single stranded nucleic acid sequences tend to attract to each other and the longer the complementary parts, the stronger the attraction.

Oligonucleotide Microarray

The physical chemistry of hybridisation is oligonucleotide microarrays is clearly different from that of cDNA microarrays. Oligonucleotides range in size from 10-25 bases. So, the DNA fragments in the spots are much smaller than cDNA fragments are. Oligonucleotide microarrays are used to detect point mutations (the missing, adding or changing of a single base) in a known DNA sequence. Single base mismatches do have much more influence on binding to an oligonucleotide sequence compared to cDNA. For example, a small genome can be synthesized on a chip as a set of thousands of 20 bp long fragments. When a single basepair match exists, the fluorescence intensity decreases significant. This technique gives possibilities to find most of the point mutations in a known DNA sequence.

Data quantification

The dyes enable the amount of sample bound to a spot to be measured by the level of fluorescence emitted when a laser excites it. If the RNA from the sample in condition 1 is in abundance, the spot will be green, if the RNA from the sample in condition 2 is in abundance, it will be red. If both are equal, the spot will be yellow, while if neither are present it will not fluoresce and appear black. Thus, from the fluorescence intensities and colours for each spot, the relative expression levels of the genes in both samples can be estimated.

The raw data that are produced from microarray experiments are the hybridised microarray images. To obtain information about gene expression levels, these images should be analysed, each spot on the array identified, its intensity measured and compared to the background. This is called image quantification and is done by image analysis software. To obtain the final gene expression matrix from spot quantification's, all the quantities related to some gene (either on the same array or on arrays measuring the same conditions in repeated experiments) have to be combined and the entire matrix has to be scaled to make different arrays comparable.

Microarrays are already producing massive amounts of data. These data, like genome sequence data, can help us to gain insights into underlying biological processes only if they are carefully recorded and stored in databases, where they can be queried, compared and analysed by different computer software programs. The EBI as well as the NCBI are establishing a public repository for microarray gene expression data analogous to banks for DNA sequence data.

Microarray is fundamentally a technique to identify complete gene expression profiles in selected tissues. Microarray experiments can give false positive and false negative results. Additional means of analysing gene expression (Northern blotting or RNAse protection assays) must be used to control microarray conclusion.

CLICK ON THE LINK BELOW FOR ANIMATED EXPLANATION:

http://www.youtube.com/watch?v=ePFE7yg7LvM&feature=related

GENE EXPRESSION ANALYSIS

2009-10-12T18:45:00.000-07:00

Northern blotting

Northern blotting is a laboratorium technique to analyse RNA expression. The experiment takes several steps. First the total amount of RNA is isolated. Then it is separated on fragment length by gel electroforesis. Then it is transferred to nitrocelloluse or nylon filter paper. The filter can then used to search for a particular RNA by several probing techniques, for instance radioactive labeling of the probe. The probe should be complement to the RNA you are looking for. This simple procedure can indicate in which tissues or cell types a particular gene is expressed. In this way a Northern blot is often used for diagnostic purposes. It can also be used to confirm results from other experimental technques like microarray .

Micro Array Analysis: (see Pictorial representation):

http://8e.devbio.com/images/ch04/06.NB.01.thumb.jpg

ESTs,Physical maps,Cytogenic maps

2009-10-12T18:35:00.000-07:00

ESTs : ESTs are small pieces of DNA sequence (usually 200 to 500 nucleotides long) that are generated by sequencing either one or both ends of an expressed gene. The 3' ESTs serve as a common source of STSs because of their likelihood of being unique to a particular species and provide the additional feature of pointing directly to an expressed gene.

ESTs as Gene Discovery Resource:As observed ESTs represent a copy of just the interesting part of a genome, that which is expressed, they have proven themselves again and again as powerful tools in the hunt for genes involved in hereditary diseases. ESTs also have a number of practical advantages in that their sequences can be generated rapidly and inexpensively, only one sequencing experiment is needed per each cDNA generated. ESTs are powerful tools in the hunt for known genes because they greatly reduce the time required to locate a gene. Using this method, scientists have already isolated genes involved in Alzheimer's disease, colon cancer, and many other diseases.

Cytogenetic Map:

A cytogenetic map is the visual appearance of a chromosome when stained and examined under a microscope. Particularly important are visually distinct regions, called light and dark bands, which give each of the chromosomes a unique appearance. This feature allows a person's chromosomes to be studied in a clinical test known as a karyotype, which allows scientists to look for chromosomal alterations.

Physical map:

A physical map is a collection of overlapping clones that have been arranged into a tiling path based on either fingerprinting (digestion of clones with restriction enzymes and comparison of the fragment sizes) or hybridisation.

The genetic markers can help to integrate these three maps mentioned above.

For Arabidopsis thaliana, TAIR's comprehensive MapViewer is an integrated graphic display of each Arabidopsis chromosome. TAIR is the internet site where all information and data about Arabidopsis is combined. MapViewer shows genetic, physical, and sequence maps in one site and allows users to search, browse, and align different maps in a region of interest. In the future, all the maps will be fully integrated into a genome map for the organism.

An Important concept of "GENE MAPPING"

2009-10-12T18:22:00.000-07:00

Genetic map

Well lets use some imagination: Like interstate maps having cities and towns that serve as landmarks, the genetic maps have landmarks known as genetic markers, or "markers" for short. The term "marker" is used very broadly to describe any observable variation that results from an alteration, or mutation, at a single genetic locus. A marker may be used as one landmark in a map if, in most cases, that stretch of DNA is inherited from parent to child according to the standard rules of inheritance. Markers can be within genes that code for a noticeable physical characteristic such as leaf colour, or a not so noticeable trait such as a disease. The greater the distance between two linked genes, the greater the chance that two nonsister chromatids would cross over in the region between the genes and the greater the proportion of recombinants that would be produced. Thus, by determining the frequency of recombinants, we can obtain a measure of map distance between the genes. Today, several other genetic markers are used to detect linkage. There are several genetic markers:

RFLPs/ (Restriction Fragment Length Polymorphism's): They were among the first developed DNA markers. RFLPs are defined by the presence or absence of a specific site, called a restriction site, for a bacterial restriction enzyme. This enzyme breaks apart strands of DNA wherever they contain a certain nucleotide sequence...
VNTRs/ ( Variable Number of Tandem Repeat Polymorphisms): They mainly occur in non-coding regions of DNA. This type of marker is defined by the presence of a nucleotide sequence that is repeated several times. In each case, the number of times a sequence is repeated may vary..
Microsatellite polymorphism's: Defined by a variable number of repeats of a very small number of base pairs. Oftentimes, these repeats consist of the nucleotides, or bases, cytosine and adenosine. The number of repeats for a given microsatellite may differ between individuals, hence the term polymorphism--the existence of different forms within a population;
SNPs/ Single Nucleotide Polymorphism's: They are individual point mutations, or substitutions of a single nucleotide, that do not change the overall length of the DNA sequence in that region. SNPs occur throughout an individual's genome;
AFLP/ Amplified Fragment Length Polymorphism: They mainly involve a DNA fingerprinting technique which detects DNA restriction fragments by means of PCR amplification.

Currently, the most powerful mapping technique, and one that has been used to generate many genome maps, relies on Sequence Tagged Site (STS) mapping: A STS is a short DNA sequence that is easily recognisable and occurs only once in a genome (or chromosome).

What are Databases..??

2009-10-12T18:19:00.000-07:00

Databases

At the beginning of the "genomic revolution," a bioinformatics concern was the creation and maintenance of a database to store biological information, such as nucleotide and amino acid sequences. Development of this type of database involved not only design issues, but also the development of complex interfaces whereby researchers could both access existing data as well as submit new or revised data.

Ultimately, however, all of this information must be combined to form a comprehensive picture of normal cellular activities so that researchers may study how these activities are altered in different disease states. Therefore, the field of bioinformatics has evolved such that the most pressing task now involves the analysis and interpretation of various types of data, including nucleotide and amino acid sequences, protein domains, and protein structures. The actual process of analysing and interpreting data is referred to as computational biology. Important sub-disciplines within bioinformatics and computational biology include:

The development and implementation of tools that enable efficient access to, and use and management of, various types of information;

The development of new algorithms (mathematical formulas) and statistics with which to assess relationships among members of large data sets, such as methods to locate a gene within a sequence, predict protein structure and/or function, and cluster protein sequences into families of related sequences.

Biological databases

A biological database is a large, organised body of persistent data, usually associated with computerised software designed to update, query, and retrieve components of the data stored within the system. A simple database might be a single file containing many records, each of which includes the same set of information. For example, a record associated with a nucleotide sequence database typically contains information such as contact name; the input sequence with a description of the type of molecule; the scientific name of the source organism from which it was isolated; and, often, literature citations associated with the sequence. For researchers to benefit from the data stored in a database, two additional requirements must be met:

Easy access to the information;

A method for extracting only that information needed to answer a specific biological question.

Entrez

At the site of the NCBI, many of the databases are linked through a unique search and retrieval system, called Entrez. Entrez allows a user to not only access and retrieve specific information from a single database, but to access integrated information from many NCBI databases. For example, the Entrez protein database is cross-linked to the Entrez taxonomy database. This allows a researcher to find taxonomic information of the protein of interest. An overview of the most important databases is given in the part Databases on this site.

Why Bioinformatics is important..??

2009-10-12T17:57:00.000-07:00

The genome sequencing projects has produced large amounts of nucleotide and protein sequence data. Traditionally, molecular biology research was carried out entirely at the experimental laboratory bench but the huge increase in the scale of data being produced in this genomic era has seen a need to incorporate computers into this research process.

Sequence generation, and its subsequent storage, interpretation and analysis are entirely computer dependent tasks. However, the molecular biology of an organism is a very complex issue with research being carried out at different levels including the genome, proteome, transcriptome and metabalome levels. Following on from the explosion in volume of genomic data, similar increases in data have been observed in the fields of proteomics, transcriptomics and metabolomics.

The first challenge facing the bioinformatics community today is the intelligent and efficient storage of this mass of data. It is important to provide easy and reliable access to this data. The data itself is meaningless before analysis and the sheer volume present makes it impossible for even a trained biologist to begin to interpret it manually. Therefore, incisive computer tools must be developed to allow the extraction of meaningful biological information.

There are three central biological processes around which bioinformatics tools must be developed:

DNA sequence determines protein sequence

Protein sequence determines protein structure

Protein structure determines protein function

what is GENOMICS..??

2009-10-12T13:50:00.000-07:00

Must tell you most of the topics in Bioinformatics that u will be coming across are simple in meaning...i mean GENOMICS u can again use ur grey cells passively and without scratching ur head can tell "its basically study of particular organism's genome" off course ur right...!!!

But again my blog would be a failure if I cant get u into understanding what exactly is going on...RIGHT!!!

so then Wat exactly is constituting our/any organism's genome..??

the Chromosomes.DNA sequences with genes embedded onto the chromosomes/DNA sequence(both are possible) Ref-GENE 8...

Primarily a genome study (GEnomiCS) involves the study of these sequences...

Though Higher Genomics study involves sequencing, comparative genomics, genome annotation, microarray technology....

Some of these techniques i have kept as video tutorials(Micro array technique) keeping in view the easy understanding in relatively less time...

GENOMICS

2009-10-12T13:24:00.000-07:00

Now then once we are done with the "what's,the who's and where's"...i feel i can start up the topics on BIOINFORMATICS....how bout GENOMICS.....??

So then where are we using our Bioinformatics skills..??

2009-10-12T12:52:00.000-07:00

once we are clear with the basic answers of what and how (u have to plz give a feedback on dat)

I am sure we can pass onto the next level so as to know where exactly do we utilize The Great BIOINFORMATICS:

Post Genomic analysis: The journey is not over yet..and our great fraternity of scientists and researchers are still hungry for more knowledge on genomes & proteomes and bout wats unknown the greatest allay of our research team is a team comprising of people called (bioinformaticians) who constantly thrive on making their works easier for genomics study and the study of the unknown..

phylogentic analyses: This is best explained in the forms of phylograms and cladograms..convenient way of observing the evolution..

visualization, modelling and simulation of metabolic pathways and regulatory networks
software tools: part of this is dealt in form of systems biology as treating the tissue system or organism as a complex circuit or machinery..
protein structure prediction,
data processing, data management,
database searches,
gene expression, expression data analysis,
recognition of genes and regulatory elements..

Why Bioinformatics...??

2009-10-12T12:47:00.000-07:00

I am sure that this must be the question you might be thinking,that after cramming these many topics and syllabis wat exactly are we planning to achhieve in Bioinformatics...well then here's the answer for that:

provide new insights into biological function

understand the functioning of living things

to apply the knowledge for "improving the quality of life" (in order to understand and fight against diseases)

databases (design, handling, ...)

gene and genome mapping

analysis of gene expression data

search for gene functions

identification of genetic risk factors

pathways, metabolic and regulatoric networks (modelling, simulation, ...)

structure prediction (protein folding, sequence alignments, homology search, ...)

target identification

drug design (docking studies, HTS, screening tests, ...)

gene therapy....

ExPASy proteomics server

2009-10-12T12:22:00.000-07:00

This was basically a server created solely for Swiss institute of bioinformatics(SIB)..

Main areas of focus being Protein sequence structure as well as 2D PAGE..

UniProt

2009-10-12T12:12:00.000-07:00

This was a joint initiative comprising of the three significant protein database banks:

Protein Information Research(PIR)- by Georgetown univ
Swiss Institute of Bioinformatics(SIB)
European Molecular Biology Labs(EMBL) (EIB)

Protein Data Bank(PDB)

2009-10-12T06:43:00.001-07:00

Protein Databank Bank(PDB) maintained by RCSB...Non- profit consortium of three organisations:

1, Rutgers State Univ.(NJ)

2. San diego Super computer center(Univ of California)(SD)

3. National institute of standards & technology.

International collaborations include:

European Bioinformatics Institute Macromolecular structure Db Group

institute for protein research,Osaka univ(japan)

EMBL(European Molecular Biology Labs)

2009-10-12T02:04:00.000-07:00

PROTEIN DATABANKS: Protein Information Resource(PIR)

2009-10-11T22:18:00.001-07:00

The Protein Information Resource (PIR) is an integrated public bioinformatics resource to support genomic, proteomic and systems biology research and scientific studies (Wu et al., 2003).

PIR was established in 1984 by the National Biomedical Research Foundation (NBRF) as a resource to assist researchers in the identification and interpretation of protein sequence information. Prior to that, the NBRF compiled the first comprehensive collection of macromolecular sequences in the Atlas of Protein Sequence and Structure, published from 1965-1978 under the editorship of Margaret O. Dayhoff. Dr. Dayhoff and her research group pioneered in the development of computer methods for the comparison of protein sequences, for the detection of distantly related sequences and duplications within sequences, and for the inference of evolutionary histories from alignments of protein sequences.

Dr. Winona Barker and Dr. Robert Ledley assumed leadership of the project after the untimely death of Dr. Dayhoff in 1983. In 1999 Dr. Cathy H. Wu joined NBRF, and later on Georgetown University Medical Center (GUMC), to head the bioinformatics efforts of PIR, and has served first as Principal Investigator and, since 2001, as Director.

For over four decades, beginning with the Atlas of Protein Sequence and Structure, PIR has provided protein databases and analysis tools freely accessible to the scientific community including the Protein Sequence Database (PSD).

In 2002 PIR, along with its international partners, EBI (European Bioinformatics Institute) and SIB (Swiss Institute of Bioinformatics), were awarded a grant from NIH to create UniProt, a single worldwide database of protein sequence and function, by unifying the PIR-PSD, Swiss-Prot, and TrEMBL databases.

In 2009 Dr. Wu accepted the Edward G. Jefferson Chair of Bioinformatics and Computational Biology at the University of Delaware (UD).

Today, PIR maintains staff at UD and GUMC and continues to offer world leading resources to assist with proteomic and genomic data integration and the propagation and standardization of protein annotation.

2009-10-11T21:47:00.001-07:00

The image above basically represents the main DATABASE HOUSES amongst which the significant Nucleotide(DNA/RNA), Protein residues are excahnged and updated...

DNA DATABANK OF JAPAN(DDBJ)

2009-10-11T21:44:00.000-07:00

DNA Data Bank of Japan (DDBJ) is the sole nucleotide sequence data bank in Asia, which is officially certified to collect nucleotide sequences from researchers and to issue the internationally recognized accession number to data submitters. Since we exchange the collected data with EMBL-Bank/EBI (European Bioinformatics Institute) and GenBank/NCBI (National Center for Biotechnology Information) on a daily basis, the three data banks share virtually the same data at any given time. The virtually unified database is called "the International Nucleotide Sequence Database (INSD)". DDBJ collects sequence data mainly from Japanese researchers, but of course accepts data and issue the accession number to researchers in any other countries.
DDBJ is organized by the Center for Information Biology and DNA Data Bank of Japan (CIB-DDBJ) of the National Institute of Genetics (NIG) with endorsement of The Japanese Ministry of Education, Culture, Sports, Science and Technology (MEXT). 99% of INSD data from Japanese researchers are submitted through DDBJ.
The principal purpose of DDBJ operations is to improve the quality of INSD, as public domains. When researchers make their data open to the public through INSD and commonly shared in world wide, we at DDBJ make efforts to describe information on the data as rich as possible, according to the unified rules of INSD, preferably without any stress by using DDBJ.

2009-10-11T12:01:00.001-07:00

The NEW FRONTIER IN BIOINFORMATICS

2009-10-10T18:38:00.000-07:00

SYSTEM BIOLOGY...

What exactly is "BIOINFORMATICS"?(2)

2009-10-10T16:38:00.000-07:00

In the past scientists(biologists,biotechnologist,chemists) used to rely on real time experiments and practical approach for deriving even minute details of a study,Manuel approach for study always required the scientist to do experiments and take measurements(temp,enzyme,etc) with exact precession even a single error could result in an abortive experimentation and thus wastage of hard work, finance etc...with the advancement of technology we observed an increasing influence of technology in the field of Biotechnology , Molecular biology later Drugs and pharmaceutical industry... This ever increasing influential part of technology involving Molecular biology,BT.This application of Information technology in molecular biology was later termed as BIOINFORMATICS coined by PAULIEN HOEGWEG in 1979..thus the scientist community could easily rely on machine derived calculations and values for deriving experiments making the work less erroneous and low manual workload.

In Vitro work into In Silico work is the main bioinformatics application

Human Genome Project

2009-10-10T16:15:00.000-07:00

Must see,.......

The protein story...regarding structure

2009-10-10T15:50:00.000-07:00

Proteins are Macromolecules composed of 20 different AMINO ACIDS(Essential amino acids) average structure or molecule of protein consisting of around 300 amino acids or 25oo atoms,the amino acids in proteins are covalently bonded and its the amino acid side chains deciding the chemical property of proteins including both structure and functions..usually proteins fold up into specific structures called as the secondary structures(alpha helix and beta sheets)...This video is all about how the proteins are in constant change...

What exactly is "BIOINFORMATICS"?

2009-10-10T15:22:00.000-07:00

This is supposed to be the first question that shud pop up into every newbies brain but I think we can easily guess out the "literal" meaning as something that is involving BIO+INFORMATICS and can give you a simple answer by writing (BIO+INFORMATICS= BIOINFORMATICS).

In this blog i would like to depict the true works that goes on behind this simple equation...

What we study in bio informatics:

Biotechnology & its applications.

Micro & Molecular biology

Computing languages(C,C++,JAVA,.NET...).
Scripting languages (PERL, Python, Bio-PERL, Bio-RUBY..)

Database management system(DBMS), Relational(RDBMS)..

Sql, My-Sql.

Mathematical Concepts and applications involving integration, calculus, and graph theory..

In short Bioinformatics is the integrated application of all the above mentioned topics into further studies(Advanced study) involving:

GENOMICS

structural genomics

functional genomics

PROTEOMICS

NANOTECHNOLOGY

RECOMBINANT DNA TECHNOLOGY

ARTIFICIAL INTELLIGENCE (in biological mol. simulations)

GRID COMPUTING for datamanagement

SYSTEMS BIOLOGY

COMPUTATIONAL BIOLOGY

PHARMACOGENOMICS

PHARMACOGENETICS

BIOPHYSICS

BIOMEDICAL INFORMATICS

MATHEMATICAL BIOLOGY

PHARMACOINFORMATICS

AGROINFORMATICS

In-Silico ADME(Tox) prediction

CHEMINFORMATICS

2009-10-10T14:44:00.000-07:00

Presentation of the Polymerase Chain Reaction(PCR)with audios,

hope is helpful for you all!!!!!

2009-10-10T14:28:00.000-07:00

Nice presentation of DNA replication

2009-10-10T14:05:00.000-07:00

This is how the DNA MicroArray technology actually works out...

2009-10-10T13:37:00.000-07:00

Online tutorials on Protein Data location and retrieval.

SNPs

2009-10-10T12:23:00.000-07:00

NCBI (National Center For Biotechnology Information)

2009-10-10T12:19:00.001-07:00

The National Center for Biotechnology Information (NCBI) is part of the United States National Library of Medicine (NLM), a branch of the National Institutes of Health. The NCBI is located in Bethesda, Maryland(38.994994°N 77.099339°W ) and was founded in 1988 through legislation sponsored by Senator Claude Pepper. The NCBI houses genome sequencing data in GenBank and an index of biomedical research articles in PubMed Central and PubMed, as well as other information relevant to biotechnology. All these databases are available online through the Entrez search engine.

The NCBI is directed by David Lipman, one of the original authors of the BLAST sequence alignment program and a widely respected figure in Bioinformatics. He also leads an intramural research program, including groups led by Stephen Altschul (another BLAST co-author), David Landsman, and Eugene Koonin (a prolific author on comparative genomics).

Jobs

2009-10-10T12:17:00.001-07:00

Application Specialist, 29th Sep 2009
Dreamers Consulting
Mumbai, 2-5 years, 4.30-6.70 lacs: The product range is called Process Monitoring tools, it is used to check the microbial contamination in microbiology labsThe product range comes under the umberalla of BIOPROCESS DIV

Jobs

2009-09-26T09:55:00.000-07:00

get the job at http://www.webindia123.com/career/options/bioinfo/intro.htm

Animation Tutorials for RECOMBINANT DNA Technology - R DNA tech

2009-09-24T22:49:00.001-07:00

http://www.bioteach.ubc.ca/TeachingResources/Applications/GMOpkgJKloseGLampard2.swf

An interesting site to clear all ur molecular biology doubts

2009-09-24T02:19:00.003-07:00

http://www.johnkyrk.com/
I found this site to be quiet useful while reviewing my molecular biology and genetics...try it out

An interesting site to clear all ur molecular biology doubts

2009-09-24T02:19:00.002-07:00

http://www.johnkyrk.com/

Felt this site to be quiet helpful for clearing some basic concepts regarding

Molecular biology...check it out..!!!

An interesting site to clear all ur molecular biology doubts

2009-09-24T02:19:00.001-07:00

http://www.johnkyrk.com/

NCBI (National Center For Biotechnology Information)

2009-09-23T22:28:00.000-07:00

http://www.ncbi.nlm.nih.gov/
Bioinformatics was first started as a field of study under the dept of Biotechnology at the National Center For Biotechnology Information...Estb

interrelations between the various databases in NCBI

2009-09-23T22:26:00.000-07:00

http://www.ncbi.nlm.nih.gov/Database/datamodel/index.html