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                                 SYSTEMS BIOLOGY:
                     THE FUTURE FOR INTEGRATED DRUG DISCOVERY
                                         
                                 TABLE OF CONTENTS
         
         EXECUTIVE SUMMARY
         
         CHAPTER 1 INTRODUCTION
         
           1.1 Introduction to systems biology
         
           1.2 Hypothesis-generation and discovery science
         
           1.3 The human genome project and systems biology
         
           1.4 Approaches to systems biology
              1.4.1 Bottom-up approach
              1.4.2 Top-down approach
         
           1.5 Enabling technologies in systems biology
              1.5.1 Technologies for global measurements
              1.5.2 Computational tools for analysis
         
           1.6 Systems biology and drug R&D
         
           1.7 Systems biology and predictive diagnostics
         
         CHAPTER 2 SYSTEMS BIOLOGY MODELS
         
           2.1  Introduction
         
           2.2  Mathematical models
              2.2.1  Types of mathematical model
                     ... Deterministic models
                     ... Stochastic models
                     ... Monte Carlo simulations and parameter estimation
              2.2.2  Structuring models
              2.2.3  Modelling biological systems
              2.2.4  Modelling diseases
              2.2.5  A common language for using and sharing models
              2.2.6  FDA stance on modelling
         
           2.3  Integration of Systems Biology with "Omics" Technologies
              2.3.1  Omics Overview
              2.3.2  Genomics and First generation models
              2.3.3  Proteomics and Second generation models
              2.3.4  Metabolomics and third-generation models
              2.3.5  Genome-scale models and integrated databases
              2.3.6  Integration via other Markup Languages
                     ... Genomics
                     ... Proteomics
                     ... Other markup languages
         
           2.4  Overview of Modelling Software
              2.4.1  Introduction
              2.4.2  BALSA
              2.4.3  BASIS
              2.4.4  BioCHARON/CHARON
              2.4.5  biocyc2SBML
              2.4.6  Bio Sketch Pad
              2.4.7  BioSpreadsheet
              2.4.8  BioUML
              2.4.9  BSTLab
              2.4.10  CADLive
              2.4.11  CellDesigner
              2.4.12  Cellerator
              2.4.13  Cellware
              2.4.14  Cytoscape
              2.4.15  dBSolve
              2.4.16  Dizzy
              2.4.17  E-Cell System
              2.4.18  Gepasi
              2.4.19  Jarnac
              2.4.20  JDesigner
              2.4.21  JigCell
              2.4.22  JSIM (Java-Based Integrative Model
                      Simulation and Analysis Environment)
              2.4.23  JWS
              2.4.24  Karyote
              2.4.25  libSBML
              2.4.26  MathSBML
              2.4.27  MOMA
              2.4.28  Monod
              2.4.29  NetBuilder
              2.4.30  PathArt
              2.4.31  pathScout
              2.4.32  ProcessDB
              2.4.33  ProMoT/DIVA
              2.4.34  Systems Biology Workbench (SBW)
              2.4.35  SCIPath (Systems Complexity Interface
                      for Pathways)
              2.4.36  SigPath
              2.4.37  SigTran
              2.4.38  Simpathica
              2.4.39  StochSim
              2.4.40  STOCKS
              2.4.41  Trelis
              2.4.42  V-Cell
              2.4.43  VLX Suite

           2.5 Academic initiatives in systems biology
              2.5.1 Introduction
              2.5.2 Stanford University
              2.5.3 Institute of Systems Biology
              2.5.4 California QB3 Institute
              2.5.5 Massachusetts Institute of Technology
              2.5.6 Whitehead Institute for Biomedical Research
              2.5.7 Harvard University Medical School
              2.5.8 German Systems Biology Initiative
              2.5.9 University of Michigan Life Science Institute
              2.5.10  US DOE Genomes to Life
              2.5.11  NIH  Roadmap for Medical Research
         
         CHAPTER 3 EXPEDITING DRUG DISCOVERY AND DEVELOPMENT
         
           3.1 Introduction
         
           3.2 Emphasising the experimental side
              3.2.1 Companies and technologies
              3.2.1 Therapeutic areas
         
           3.3 Emphasising the computational side
              3.3.1 Companies and technologies
              3.3.2 Therapeutic areas
         
           3.4 Creating "virtual patients"
              3.4.1 Companies and technologies
              3.4.2 Therapeutic areas
         
         CHAPTER 4 COMPANY PROFILES
         
           4.1 Beckman Coulter Inc
           4.2 Beyond Genomics
           4.3 Bioseek
           4.4 Cyprotex
           4.5 Eli Lilly (Systems Biology, Singapore)
           4.6 Entelos Inc
           4.7 GeneGo Inc
           4.8 IBM (including IBM Life Sciences)
           4.9 Linden Technologies Inc
           4.10 Predix Pharmaceuticals Inc

         APPENDIX 1  SBML REPRESENTATION OF WNT/CATENIN SIGNALLING MODEL

         APPENDIX 2  AN EXAMPLE OF A RUN PROTOCOL IN THE MICROARRAY GENE
                     EXPRESSION MARKUP LANGUAGE (MAGE-ML)