Systems Biology: Integrative Biology and Simulation Tools

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Aleš Prokop, Béla Csukás
Springer Science & Business Media, 28.08.2013 - 553 Seiten
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Growth in the pharmaceutical market has slowed down – almost to a standstill. One reason is that governments and other payers are cutting costs in a faltering world economy. But a more fundamental problem is the failure of major companies to discover, develop and market new drugs. Major drugs losing patent protection or being withdrawn from the market are simply not being replaced by new therapies – the pharmaceutical market model is no longer functioning effectively and most pharmaceutical companies are failing to produce the innovation needed for success. This multi-authored new book looks at a vital strategy which can bring innovation to a market in need of new ideas and new products: Systems Biology (SB). Modeling is a significant task of systems biology. SB aims to develop and use efficient algorithms, data structures, visualization and communication tools to orchestrate the integration of large quantities of biological data with the goal of computer modeling. It involves the use of computer simulations of biological systems, such as the networks of metabolites comprise signal transduction pathways and gene regulatory networks to both analyze and visualize the complex connections of these cellular processes. SB involves a series of operational protocols used for performing research, namely a cycle composed of theoretical, analytic or computational modeling to propose specific testable hypotheses about a biological system, experimental validation, and then using the newly acquired quantitative description of cells or cell processes to refine the computational model or theory.
 

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Inhalt

1 Functional Genomics Proteomics Metabolomics and Bioinformatics for Systems Biology
3
A Survey on Graph Classifying Techniques
42
Models and Data
65
4 Regulatory Crosstalk Analysis of Biochemical Networks in the Hippocampus and Nucleus Accumbens
94
5 Properties of Biological Networks
129
A Review of Enabling Technologies
179
6 On Different Aspects of Network Analysis in Systems Biology
180
7 Computational Approaches for Reconstruction of TimeVarying Biological Networks from Omics Data
209
11 Parameter Identifiability and Redundancy with Applications to a General Class of Stochastic Carcinogenesis Models
321
Formal Knowledge Representation in Systems Biology for Model Construction Retrieval Validation and Discovery
355
Part IIICritical Analysis of MultiScale Computational Methods and Tools Computational Tools for Crossing Levels and Applications
374
13 Computational Infrastructures for Data and Knowledge Management in Systems Biology
375
14 Computational Tools and Resources for Integrative Modeling in Systems Biology
399
An Example AgentBased Model of Acute Pulmonary Inflammation
429
16 Reconstruction and Comparison of Cellular Signaling Pathway Resources for the SystemsLevel Analysis of CrossTalks
462
17 A Survey of Current Integrative Network Algorithms for Systems Biology
479

A Framework for Integrative Approaches
240
9 Innovations of the RuleBased Modeling Approach
273
10 Reproducibility of ModelBased Results in Systems Biology
301
18 Direct Computer Mapping Based Modeling of a Multiscale Process Involving p53miR34a Signaling
496
Index
549
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