Note: Lecture Notes in Artificial Intelligence 3303 -- Knowledge Exploration in Life Science Informatics -- Copyright -- Preface -- Table of Contents -- A Pen-and-Paper Notation for Teaching Biosciences -- An Exploration of Some Factors Affecting the Correlation of mRNA and Proteomic Data -- Improving Rule Induction Precision for Automated Annotation by Balancing Skewed Data Sets -- A Randomized Algorithm for Distance Matrix Calculations in Multiple Sequence Alignment* -- Extracting Sequential Patterns for Gene Regulatory Expressions Profiles -- Data Analysis of Microarrays Using SciCraft -- Functional Data Analysis of the Dynamics of Gene Regulatory Networks -- Text Mining of Full Text Articles and Creation of a Knowledge Base for Analysis of Microarray Data -- Analysis of Protein/Protein Interactions Through Biomedical Literature: Text Mining of Abstracts vs. Text Mining of Full Text Articles -- Ranking for Medical Annotation: Investigating Performance, Local Search and Homonymy Recognition -- A New Artificial Life Formalization Model: A Worm with a Bayesian Brain★ -- Teaching Grasping to a Humanoid Hand as a Generalization of Human Grasping Data -- JavaSpaces - An Affordable Technology for the Simple Implementation of Reusable Parallel Evolutionary Algorithms -- Detecting and Adapting to Concept in Bioinformatics Drift -- Feature Extraction and Classification of the Auditory Brainstem Response Using Wavelet Analysis -- Evaluation of Outcome Prediction for a Clinical Diabetes Database -- Cytochrome P450 Classification of Drugs with Support Vector Machines Implementing the Nearest Point Algorithm -- Multiple-Instance Case-Based Learning for Predictive Toxicology -- Modelling and Prediction of Toxicity of Environmental Pollutants -- Modelling Aquatic Toxicity with Advanced Computational Techniques: Procedures to Standardize Data and Compare Models. , Author Index.

Note: Intro -- Understanding the Dynamics of Biological Systems -- Preface -- Contents -- Contributors -- Chapter 1 Effects of Protein Quality Control Machinery on Protein Homeostasis -- 1.1 Protein Folding is Catalyzed by a Complex Network of Reactions -- 1.1.1 Disruptions to the Protein Folding Network are Associated with Disease -- 1.1.2 The ER Functions as a Protein Folding Factory -- 1.1.3 Mathematical Models of Protein Quality Control Provide Novel Insights into the Regulation of Protein Assembly -- 1.2 Case Studies -- 1.2.1 Case Study I: Protein Folding Without Quality Control -- 1.2.1.1 Assumptions -- 1.2.1.2 Analytical Solution -- 1.2.1.3 Timescale Analysis -- 1.2.1.4 Conclusions for Case Study I -- 1.2.2 Case Study II: Protein Folding with Quality Control -- 1.2.2.1 Assumptions -- 1.2.2.2 Qualitative Dynamical Behavior and Equilibrium Points -- 1.2.2.3 Timescale Analysis -- 1.2.2.4 Parametric Sensitivity Analysis -- 1.2.2.5 Conclusions for Case Study II -- 1.3 Lessons Learned -- Appendix -- References -- Chapter 2 Metabolic Network Dynamics: Properties and Principles -- 2.1 Introduction -- 2.2 Dynamic Mass Balances and Fundamental Subspaces -- 2.2.1 Key Considerations in Networks -- 2.2.2 Properties of Dynamic Systems -- 2.2.2.1 Underlying Structure of the Jacobian -- 2.2.2.2 Structural Similarity -- 2.2.2.3 Flux-Concentration Duality -- 2.2.2.4 Hierarchical Dynamics -- 2.3 Dual Jacobian Matrices -- 2.4 Stoichiometry Versus Gradients -- 2.5 Example: Folate Metabolism -- 2.5.1 Constituent Matrices and Subspaces -- 2.5.2 Hierarchical Pooling of Metabolites -- 2.5.3 Environmental Perturbations -- 2.6 Conclusions -- 2.6.1 Future Directions: Constructing Genome-Scale Models -- References -- Chapter 3 A Deterministic, Mathematical Modelfor Hormonal Control of the Menstrual Cycle -- 3.1 Introduction and Biological Background. , 3.2 The Pituitary and Ovarian Models -- 3.3 Fitting Parameters -- 3.4 Parameter Sensitivity and Bifurcations -- 3.5 Exogenous Hormone Effects -- 3.6 Conclusion -- References -- Chapter 4 Modeling Transport Processes and Their Implications for Chemical Disposition and Action -- 4.1 Introduction -- 4.1.1 The Fate of Chemicals in the Body -- 4.1.1.1 Absorption -- 4.1.1.2 Distribution -- 4.1.1.3 Metabolism -- 4.1.1.4 Excretion -- 4.1.2 Chemical and Pathophysiological-Mediated Alterations in Drug Disposition -- 4.1.3 Extrapolation of Data Between Biological Scenarios -- 4.2 Traditional Pharmacokinetic Approaches to Modeling Drug Disposition -- 4.3 More Complex Models of Drug Movement Across Biological Membranes -- 4.3.1 The Measurement of Chemical Movement Across Biological Membranes -- 4.3.2 General Considerations for Measuring Movement of Drugs Across Biological Membranes -- 4.3.2.1 Simple Versus Complex Measurement Systems -- 4.3.2.2 Ionization Status of the Drug -- 4.3.2.3 Heterogeneity in Drug Dispersion -- 4.3.2.4 Chemical Sequestration -- 4.3.2.5 Physico-Chemical Characteristics of the Chemical -- 4.3.2.6 ATP Usage Within the Test System -- 4.3.3 Measurement of Passive Diffusion -- 4.3.4 Measurement of Active Transport -- 4.4 The Integration of Drug Disposition and Drug Fate into a Predictive Model of the Life Cycle of a Drug in the Body -- 4.4.1 Multiple Drug Resistance Phenotype in Cancer Treatment -- 4.5 Summary -- References -- Chapter 5 Systems Biology of Tuberculosis: Insights for Drug Discovery -- 5.1 Introduction -- 5.2 Understanding Mtb: A Parts Catalogue -- 5.3 Assembling the Parts: Network Reconstruction -- 5.3.1 Annotation of Genomes -- 5.3.2 Impact of High-Throughput Experiments -- 5.4 Network Modeling and Simulation -- 5.4.1 Reconstruction of Mtb Metabolism -- 5.4.1.1 Flux Balance Analysis -- 5.4.1.2 Mycolic Acid Pathway. , 5.4.1.3 Genome-Scale Metabolic Models -- 5.4.2 Transcriptional Analysis -- 5.4.2.1 Transcriptional Regulatory Networks in Mtb -- 5.4.3 Analysis of the Mtb Interactome -- 5.5 Target Identification -- 5.5.1 Multi-Level Target Identification Pipeline: TargetTB -- 5.5.1.1 Importance of Systems-Based Approaches -- 5.5.2 Disruption of Metabolism -- 5.5.3 Tackling Resistance in Mtb -- 5.6 Interface with the Host: Modeling Host--Pathogen Interactions -- 5.6.1 Response Networks -- 5.6.2 Mechanistic Models of Immune System Dynamics -- 5.6.3 Boolean Modeling of Mtb-Human Interactions -- 5.7 Future Perspectives -- References -- Chapter 6 Qualitative Analysis of Genetic Regulatory Networks in Bacteria -- 6.1 Introduction -- 6.2 Carbon Starvation in E. coli -- 6.3 Modeling and Model Reduction -- 6.4 Qualitative Analysis of Dynamics -- 6.5 Formal Verification of Network Properties -- 6.6 Model Completion -- 6.7 Conclusions -- References -- Chapter 7 Modeling Antibiotic Resistance in Bacterial Colonies Using Agent-Based Approach -- 7.1 Introduction -- 7.1.1 MRSA Antibiotic Resistance Mechanisms -- 7.1.2 Overview of Modeling Approaches -- 7.1.3 Agent-Based Modeling Approach -- 7.2 Micro-Gen Bacterial Simulator -- 7.2.1 Environment -- 7.2.2 Bacterial Agents -- 7.2.2.1 Growth Parameters -- 7.2.2.2 Antibiotic Resistance Mechanisms -- 7.2.2.3 Overcrowding Algorithm -- 7.2.3 Antibiotics -- 7.2.4 -Lactamase Enzymes -- 7.2.5 Program Flow Structure -- 7.2.6 Parallelisation -- 7.3 Simulations of Bacteria--Antibiotic Interactions -- 7.4 Conclusions and Future Work -- References -- Chapter 8 Modeling the Spatial Pattern Forming Modules in Mitotic Spindle Assembly -- 8.1 Introduction -- 8.2 Microtubule Dynamics -- 8.2.1 Nucleation -- 8.2.2 Polymerization -- 8.3 Microtubule-Motor Interactions -- 8.3.1 Microtubule Gliding Assays -- 8.3.2 Motor Mechanics. , 8.3.3 Microtubule-Motor Patterns -- 8.4 Chromosome Dynamics -- 8.4.1 Search and Capture -- 8.4.2 Metaphase Plate Formation -- 8.5 Reaction-Diffusion Gradients of Microtubule Dynamics Regulation -- 8.5.1 Stathmin -- 8.5.2 RanGTP Nucleation and Stabilization Gradients -- 8.5.3 Long-Range Stabilization Gradients -- 8.6 Outlook -- References -- Chapter 9 Cell-Centred Modeling of Tissue Behaviour -- 9.1 Introduction: Towards a Virtual Cell Biology -- 9.2 Can Computation Cope with Cellular Complexity? -- 9.2.1 Being Generic: Function Versus Detail -- 9.3 Cells and Computation -- 9.4 Developing a Multi-Scale Model -- 9.5 The Agent Basis: The Communicating-Stream X-Machine -- 9.6 Biology, Physics, Chemistry and Computation -- 9.6.1 Forces on Cells -- 9.7 Hierarchy in Computational Models -- 9.8 Examples at Molecular and Cell Level -- 9.8.1 NF-B Signalling -- 9.8.2 Urothelium Monolayer Growth -- 9.8.3 Epidermis Multilayer Growth -- 9.9 A Framework for Multi-Scale Modeling -- 9.10 Describing Individual-Based Models -- 9.11 Visualisation and Graphical Output -- 9.12 Repeatability, Sensitivity Analysis and Validation -- 9.13 Lessons Learned -- References -- Chapter 10 Interaction-Based Simulations for Integrative Spatial Systems Biology -- 10.1 Introduction -- 10.2 Computer Modeling and Simulation in Integrative and Spatial Systems Biology -- 10.2.1 Dynamical Systems in Systems Biology -- 10.2.1.1 The Need of a Unifying Simulation Language -- 10.2.1.2 State and Evolution Function in Systems Biology -- 10.2.1.3 Dynamical Systems with a Dynamical Structure -- 10.2.1.4 Local Interactions -- 10.2.2 Individual-Based Models and Their Simulations -- 10.2.2.1 Multi-Agent Implementation -- 10.2.2.2 The Spatial Structure of Interactions -- 10.3 The MGS Domain-Specific Programming Language -- 10.3.1 Topological Collection -- 10.3.2 Transformation. , 10.3.3 Two Models of Diffusion -- 10.3.3.1 The Numerical Resolution of the Continuous Model -- 10.3.3.2 The Discrete Stochastic Evolution of a Diffusing Particle -- 10.4 A Synthetic Multicellular Bacterium -- 10.4.1 Synthetic Biology -- 10.4.2 The International Genetically Engineered Machine Competition -- 10.4.3 Objectives of the SMB Project -- 10.4.4 The Paris Team Proposal -- 10.5 Modeling in MGS -- 10.5.1 Solving Differential Equations -- 10.5.1.1 The SMB Proof of Concept -- 10.5.1.2 Analysis of the ODE Model -- 10.5.1.3 A Numerical Solution of Differential Equations -- 10.5.1.4 Interpretation of the Simulations' Results -- 10.5.2 Cellular Automata -- 10.5.2.1 The Spatial Organization of the SMB -- 10.5.2.2 A Discrete Spatial Framework -- 10.5.2.3 MGS Expression of a Cellular Automaton -- 10.5.2.4 Interpretation of the Simulations' Results -- 10.5.3 Stochastic Simulations -- 10.5.3.1 Robustness Analysis of the SMB Design -- 10.5.3.2 Stochastic Modeling for Sensitivity to Noise Analysis -- 10.5.3.3 Gillespie-Based Simulations in MGS -- 10.5.3.4 Interpretation of the Simulations' Results -- 10.5.4 Integrative Modeling -- 10.5.4.1 Description of the Model -- 10.5.4.2 Integration of the Two Models -- 10.5.4.3 Interpretation of the Simulations' Results -- 10.6 Related Work, Conclusions, and Perspectives -- 10.6.1 Related Work -- 10.6.2 Conclusions and Perspectives -- Appendix -- References -- Glossary -- Index.

Note: Intro -- Combining a High-Throughput Bioinformatics Grid andBioinformatics Web Services -- Introduction -- Materials and Methods -- Architecture -- Data Flow Implementation -- Results and Discussion -- Conclusion -- References -- Using Public Resource Computing and SystematicPre-calculation for Large Scale Sequence Analysis -- Introduction -- Public Resource Computing -- Systematic Pre-calculation of Sequence Analyses -- Systems and Methods -- Implementation -- BOINC Server -- BOINC Applications -- Results -- Performance of BOINC-Applications -- The BOINCSIMAP Project -- Conclusion -- Availability -- References -- Accelerated microRNA-Precursor DetectionUsing the Smith-Waterman Algorithm onFPGAs -- Introduction -- Previous Work -- FPGA in Bioinformatics -- Detecting microRNA Precursor Sequences with Smith-Waterman -- Scanning a Single Genomic Sequence -- Comparative Application -- Results -- Biological Relevance -- Interfacing of the Smith-Waterman Accelerator to LiSA -- Computational Performance -- Summary and Conclusion -- Implementation of a Distributed Architecture forManaging Collection and Dissemination of Data for FetalAlcohol Spectrum Disorders Research -- Introduction -- Distributed Nature of CIFASD -- Commitment to Data Integration -- Clinical Needs vs. Computer Science Research -- System Design -- Data Dictionaries -- Data Entry -- Central Repository and Data Flow -- Assuring Data Quality -- Reliable Infrastructure -- Results and Conclusions -- References -- Grid-Enabled High Throughput Virtual Screening -- Introduction -- Large Scale in Silico Docking Against Malaria -- Introduction -- Objectives -- In Silico Docking Against Avian Influenza -- Introduction -- Objectives -- The Grid Tools -- The Grid Infrastructures -- The WISDOM Production Environment -- The DIANE Framework -- Results -- WISDOM Results -- Perspectives. , Perspective on the Grid Side: WISDOM-II -- From Virtual Docking to Virtual Screening -- Conclusion -- References -- Grid Computing for the Estimation of Toxicity:Acute Toxicity onFathead Minnow (Pimephales promelas) -- Introduction -- Predictive Models for the Toxicity Prediction -- Grid Computing for Prediction Models -- Estimation of Acute Toxicity on Fathead Minnow -- Experimental Data -- Molecular Structures -- Molecular Descriptors -- Forward Selection of Descriptors to Multi-linear Regression -- Heuristic Back-Propagation Neural Networks for QSAR -- Results and Discussion -- Model Based on Multi-linear Regression -- Model Based on Artificial Neural Networks -- Comparison with Previously Published Models -- Conclusions -- Peer-to-Peer Experimentation in ProteinStructure Prediction: An Architecture,Experiment and Initial Results -- Introduction: Peer-to-Peer Experimentation -- Scientists as Peers in a Web Community -- Scientific Coordination as Peer-to-Peer Communication -- Experiment Implementation -- The MagentA Architecture -- Example Experiment: Consistency-Checking in Protein Structure Prediction -- 3-D Structural Models for Yeast Proteins -- Data Sources -- Processing/Pre-filtering of Data Sets -- Consistency-Checking -- Results and Discussion -- Conclusions and Future Work -- Gene Prediction in Metagenomic Libraries Usingthe Self Organising Map and High PerformanceComputing Techniques -- Introduction -- Rationale for the SOM -- The SOM -- Descriptor -- Analysis -- Parallel Approach -- MPI Implementation -- Annotation -- Results -- Conclusions -- A Distributed System for Genetic Linkage Analysis -- Introduction -- The Grid Execution Hierarchy Scheduling Algorithm -- Grid Execution Hierarchy -- Scheduling Tasks in Grid Hierarchy -- Handling Multiple Grids at the Same Level of the Execution Hierarchy. , Parallel Algorithm for the Computation of LOD Score -- Serial Algorithm -- Parallel Algorithm -- Implementation of the Parallel Algorithm for Execution in Grid Hierarchy -- Deployment of SUPERLINK-ONLINE -- Results -- Parallel Algorithm Performance -- Performance of the Grid Execution Hierarchy Scheduling Algorithm -- Related Work and Conclusions -- References -- Enabling Data Sharing and Collaboration inComplex Systems Applications -- Introduction -- Data Sharing Methods -- Objective -- An Example -- Characteristics of Our Network -- Resource Management and Grouping -- Security -- Scalability -- Performance -- Fairness -- Design Issues -- Content Storage and Management -- Network Structure -- Access Controls and Secure Storage -- Content Replication and Accountability -- Architecture and Implementation -- The Data -- The Database -- Database Interface -- User Interface Layer -- Practical Details -- Database Creation and Roles -- Security -- Installing and Connecting -- Performance -- Other Configuration Issues -- Conclusions -- Accessing Bio-databases with OGSA-DAI -A Performance Analysis -- Introduction -- OGSA-DAI -- Methods -- Results -- Hardware and Software Configuration -- Loading Data -- Retrieving Data -- Conclusion -- Systems Support for Remote Visualization of GenomicsApplications over Wide Area Networks -- Introduction -- System Overview -- Compressing 2-D Pixel Segments -- Basic Compression Algorithm -- Content-Based Anchoring of 2-D Pixel Segments -- An Optimization with Two-Level Fingerprinting -- Implementation -- Evaluation -- Experimental Testbed -- Network Communication Requirements -- Compression Results -- Related Work -- Conclusion -- References -- HVEM DataGrid: Implementation of a BiologicData Management System for Experiments withHigh Voltage Electron Microscope -- Introduction -- Related Works -- Background. , HVEM DataGrid System -- System Architecture and Design -- Schema of HVEM DataGrid -- Data Workflow -- Data Management and Access -- Data Search -- System Implementation -- Environmental Setup -- DataGrid Test -- Conclusion and Future Work.

Note: Intro -- Preface -- Organization -- Table of Contents -- Author Index.