Transcript sri

Knowledgebase Creation & Systems
Biology:
A new prospect in discovery informatics
S.Shriram,
Siri Technologies (Cytogenomics),
Bangalore
What is a knowledgebase?
A knowledgebase provides an integrated
approach to biological simulation that
combines process, technology, tools and
applications for solving complex problems and
for data representation, validation and
prediction

The use of simulation in pharmaceutical
research enables investigators to
anticipate potential issues in the drug
discovery process and to select the best
overall design principles in advance of
real-life studies

Knowledgebases forms the base for
SYSTEM BIOLOGY - ie study of biological
systems using a holistic approach
Advantages of Knowledgebase

Access proprietary and public databases, data
analysis tools, and computer algorithms within a
single, expandable, web-based software
environment
 Streamline data analysis and interpretation
 Share experimental data and models across
organizational networks
Advantages….

Explore new experimental scenarios, test
hypotheses, and generate predictive
information
 Create, run, modify and routinely upgrade
detailed models of cells, tissues and organs
with little or no dependence on highly trained
programmers
Path to Knowledgebase
Database
Infobase
Knowledgebase
Creation of Knowledgebase

Identify the disease and tissue (eg. pancreatic cancer
and pancreas and other related tissues)

Data to be gathered form curation of literature,
experiments(eg. gene expression studies), clinical
studies and analysis/interpretation of these details to
extract information (eg. identify targets/side effects of
known drugs in the pathways)
Creation…

Represent complex experimental data in
mathematical form and then uses these equations to
build customized biological models

Models to aid prediction of effects of new drugs, etc.
Drug Discovery –Emerging needs for
Knowledgebase
Bioinformatics
Chemo-informatics
Target
identification
Target
evaluation and
selection
Lead
identification/o
ptimization
Process
development
Preclinical
evaluation
Curated Knowledgebase
Clinical
evaluation
Drug
Types of Knowledgebase
Pathways
Gene/Protein/Target
Ligands/
Drugs
Integrated Platform for Bio and
Chemo Knowledgebase
Patent & Published
Literature
Proprietary Data
Bioinformatics
Chemoinformatics
Integrated
Knowledgebase
Ligand centric knowledgebase
Patents &
literature
Structure 2D,
3D
Synthesis
Drug Targets
Target Sequence
Analogs
SAR
Physico-chemical properties
Ligand
Centric
Target Structure (3D)
Ligand – target
interaction
Combinatorial
chemistry
Pharmacophore
models
Assay / Bioactivity
Regulatory information
ADME and Toxicity
Data Integration
OMIM
UniGene
Probeset
BODYMAP
Homologene
Integrated
Database
GenBank
LocusLink
SWISS-PROT
Homologous
Features of pathway database
• Clickable maps that give data on the proteins of interest
• Multiple search modes, including protein, signaling
molecule and ligand structure based searches and other
filters like physiology, organism, disease state etc
• Provision for a comprehensive account of the diseases,
to enable the user to build and visualize non-canonical
pathways
Caspase Pathway
Features of Pathway Knowledgebase

Tagging of gene expression data (from Microarray, SAGE,
etc) onto the simple clickable pathway maps.

In-silico manipulation of pathways – ie predict the
alterations in expression levels in any given tissue or
disease conditions

Ease target prioritization
Building blocks of SYSTEM BIOLOGY
Organism / disease
Cell / tissue
Pathways
Gene/Protein/Target
Ligands/
Drugs
Why we need biological systems?

To figure out
 What is the effect of an intervention in one
part of the system, and its associated
problem?
 What intervention one has to make in order to
obtain some desired result?
Key Players
 Physiome Sciences
 Entelos Inc.
Predictive biology
Clinical
Response
Molecular
Target
Computer
Simulation
Fragmented
Expertise
Integrated
Knowledge
Predictive
Biological
Models
Novel
Insights
Bioinformatics
Gene
Chips
High-Throughput
Systems
Knock-outs
Healthcare
Alliances
Example
Since these equations
are completely defined
by the knowledge of
connectivity of a network,
and knowledge of various
transition rate constants,
and since these
quantities are all stored
in a databases, the
equations may be
generated automatically
on a computer
Allen
resident cell
activation
Bill
inflammatory
cell influx
8% improvement in FEV1
resident cell
activation
inflammatory
cell influx
21% improvement in FEV1
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Applications of Systems Biology
Understanding disease dynamics
•
•
Test hypotheses of a disease pathology
–
Ask better questions
–
Plan better experiments
Identify and fill the knowledge gaps
Bridging biochemistry to clinical outcomes
•
Target assessment & prioritization
•
Drug candidate advancement
•
Combination therapy assessment
Designing and understanding clinical studies
•
Patient selection and dosing
•
Surrogate marker prediction

Entelos demo
Thanks to
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Siri Technologies
Cytogenomics
Jubilant Biosys
Entelos
Physiome Sciences
Thank you