Transcript Various Career Options Available

Opportunities in Bioinformatics
Presented By
Dr G. P. S. Raghava
Co-ordinator, Bioinformatic Centre
IMTECH, Chandigarh
Email: [email protected]
Web: http://imtech.res.in/raghava/
What is Bioinformatics (BI) ?
More About Bioinformatics
Historical Background
Media Hype & Confusion
Important Applications of BI
Bioinformatics in India
Demand of BI Professionals
How to Enter in BI (Course & Degrees)
What is Bioinformatics
– Biocomputing: Application of Computer in
Biosciences
– Biocomputing started in 1960’s
– Explosion of Genomic Data
– Access and Management of Data
– Biocomputing+Information Science
– Role of Internet in BI
Core of Bioinformatics
•Relationships between
TDQAAFDTNIVTLTRFVM
EQGRKARGTGEMTQLLNS
LCTAVKAISTAVRKAGIA
HLYGIAGSTNVTGDQVKK
LDVLSNDLVINVLKSSFA
TCVLVTEEDKNAIIVEPE
KRGKYVVCFDPLDGSSNI
DCLVSIGTIFGIYRKNST
DEPSEKDALQPGRNLVAA
GYALYGSATMLV
sequence
3D structure
protein functions
•Properties and evolution of genes, genomes,
proteins, metabolic pathways in cells
•Use of this knowledge for prediction, modelling, and
design
The challenge
(Boguski, 1999)
In 1995, the number of genes in the database started to exceed
the number of papers on molecular biology and genetics in the
literature!
More About Bioinformatics
Multiple
Sequence
Alignment
Database
Homology
Searching
Sequence
Analysis
Genome
Mapping
Protein
Analysis
Proteomics
Bio
Informatics
Sample
Registration &
Tracking
3D
Modeling
Homology
Modeling
Docking
Intellectual
Property
Auditing
Integrated
Data
Repositories
Common
Visual
Interfaces
Computational Biology
in the High-Throughput Era
The Genome and Beyond
Scientific Challenges
 Algorithmic Challenges
 Computational Challenges

Historical Background
Life Science - young compared to
physics and chemistry
 1953 Structure of DNA
 1960s Understanding of “code of life”
 1970s Genetic manipulation technology
 1980s Widespread innovation biotechnology/genetic revolution
 1990s Human Genome Project
 2000s Structural Genomics ?

Media Hype and Confusion
Anybody can do BI
 BI can do anything
 Colleges/Courses/Training
 No Quality Check
 Limited Knowledge of Subject
 More user than developer

Why Bioinformatcs is Required
Data growth is exponential
 Difficult to understand life without BI
 Detection of new diseases
 BI tools allow to save expr. Expend.
 Rational Drug design
 Computer-aided vaccine design

Application of Bioinformatics
Genome Annotation
 Protein Structure Prediction
 Proteomics
 DNA Chip technology
 Disease Diagnostics
 Fingerprinting Technique
 Drug/Vaccine Design

Genome Annotation
The Process of Adding Biology Information and
Predictions to a Sequenced Genome Framework
Protein Structures
Protein Structure Prediction

Experimental Techniques
– X-ray Crystallography
– NMR

Limitations of Current Experimental
Techniques
– Protein DataBank (PDB) -> 17000 protein structures
– SwissProt -> 90,000 proteins
– Non-Redudant (NR) -> 800,000 proteins

Importance of Structure Prediction
– Fill gap between known sequence and structures
– Protein Engg. To alter function of a protein
– Rational Drug Design
Traditional Proteomics
1D gel electrophoresis (SDS-PAGE)
 2D gel electrophoresis
 Protein Chips

– Chips coated with proteins/Antibodies
– large scale version of ELISA

Mass Spectrometry
– MALDI: Mass fingerprinting
– Electrospray and tandem mass
spectrometry

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Sequencing of Peptides (N->C)
Matching in Genome/Proteome Databases
Overview of 2D Gel

SDS-PAGE + Isoelectric focusing (IEF)
– Gene Expression Studies
– Medical Applications
– Sample Experiments

Capturing and Analyzing Data
– Image Acquistion
– Image Sizing & Orientation
– Spot Identification
– Matching and Analysis
Comparision/Matcing of Gel Images

Compare 2 gel images
– Set X and y axis
– Overlap matching spots
– Compare intensity of spots

Scan against database
– Compare query gel with all gels
– Calculate similarity score
– Sort based on score
Mass Fingerprinting

Add protease (e.g. trypsin)
– Get fragment size of peptides

Scan against peptides of a protein
obtained theortically by that protease

Scan against all proteomes
DNA Chip Technology
Differential Proteomics:
Fingerprints of Disease
Normal Cells
Disease Cells
Phenotypic
Changes
•Differential protein expression
• Protein nitration patterns
•Altered phosporylation
•Altered glycosylation profiles
Utility
•Target discovery
•Disease pathways
•Disease biomarkers
Fingerprinting Technique

What is fingerprinting
– It is technique to create specific pattern for a given
organism/person
– To compare pattern of query and target object
– To create Phylogenetic tree/classification based on pattern

Type of Fingerprinting
–
–
–
–

DNA Fingerprinting
Mass/peptide fingerprinting
Properties based (Toxicity, classification)
Domain/conserved pattern fingerprinting
Common Applications
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–
–
–
–
Paternity and Maternity
Criminal Identification and Forensics
Personal Identification
Classification/Identification of organisms
Classification of cells
Drug Design based on Bioinformatics Tools

Detect the Molecular Bases for Disease
– Detection of drug binding site
– Tailor drug to bind at that site
– Protein modeling techniques
– Traditional Method (brute force testing)

Rational drug design techniques
– Screen likely compounds built
– Modeling large number of compounds (automated)
– Application of Artificial intelligence
– Limitation of known structures

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Search of Target protein
Search of Lead compound
History of Bioinformatics in India

Biocomputing started in 1950’s
– IISc Banglore (Prof G Ramachandran)
– Mostly analysis of protein structure

Distributed information center (DIC)
– DBT initiate 9 DICs during 1986-7
– National Facilities (IMT,IISc,IARI,JNU,MKU)
– Sub-DICs started (around 50)
– Mirror sites in 1999 (IMT,Pune,JNU,IISc)
Education in Bioinformatics

Role of BIC’s in education
– Workshops, training, course etc started
– Facilities/Infrastructure in BI
– Advanced diploma in BI (Pune,JNU,MKU)
– M.Sc. In bioinformatics

Private Sector
– Number of courses initiated
– Dedicated training centers
Universities
 R&D Institutes

– Ph.D in Bioinformatics (IMT)
Business Comparisons
Company
Chase-Manhattan
AMR Corporation
Nation’s Bank
Sprint
IBM
MCI
Microsoft
United Parcel
Revenues
IT Budget
Pct
16,431,000,000 1,800,000,000 10.95 %
17,753,000,000 1,368,000,000 7.71 %
17,509,000,000 1,130,000,000 6.45 %
14,235,000,000
873,000,000 6.13 %
75,947,000,000 4,400,000,000 5.79 %
18,500,000,000 1,000,000,000 5.41 %
11,360,000,000
510,000,000 4.49 %
22,400,000,000 1,000,000,000 4.46 %
Bristol-Myers Squibb 15,065,000,000
Pfizer 11,306,000,000
Pacific Gas & Electric 10,000,000,000
Wal-Mart104,859,000,000
K-Mart 31,437,000,000
440,000,000
300,000,000
250,000,000
550,000,000
130,000,000
2.92 %
2.65 %
2.50 %
0.52 %
0.41 %
Typical Bioinformatics
Multi-Disciplinary Training
•Scientists
– Biology, Molecular Genetics, Clinical Biochemistry,
Protein Structure Chemistry
•Mathematicians
– Statistics, Algorithms, Image processing
•Computer Scientists
– Database, User Interface/Visualizations, Networking
(Internets/Intranets), Instrument Control
Typical Bioinformatics
Multi-Disciplinary Functions
•Scientists
– Experimental Design & Interpretation
– Laboratory Protocols & Standards/Controls
•Mathematicians
– Analysis & Correlation of Data
– Validation methodologies
•Computer Scientists
– Information Storage / Control Vocabulary
– Data Mining
Bioinformatics Architecture
Users
Workstation
NT
servers
Unix
servers
&
Specialized
Hardware
Web
Browser
MS
Access
Shared
Access
Databases
Proprietary
Internal
Databases
External
External
Proprietary
Public
Databases Databases
Active Livewire
Server
Java & Desktop
Programs
CGI
Web
Server
Business Opportunities in BI
Software development
 Web servers development
 Train manpower in Field of BI
 Database management
 Rational Drug design
 Develop Diagnostic kits
 Assist user in Vaccine development
 Consultant to Biotech Companies

Bioinformatics at IMT, Chandigarh
http://imtech.res.in/bic/
http://imtech.res.in/
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Mirror Sites (http://www.imtech.res.in/mirror_sites/)

Public Domain Resources in Biology (www.imtech.res.in/)
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IMTECH Library on Internet (/lib/)
Concept of vaccine design
Protein Structure Prediction (Olympic-2000)
Gene Prediction
Software for general use
– GNU software
– SUN Freeware
– PostgreSQL
Site: http//:imtech.res.in/raghava/www.html
THANK YOU!