Systems Biology: Integrative Biology and Simulation ToolsAleš Prokop, Béla Csukás Springer Science & Business Media, 28.08.2013 - 553 Seiten 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 Major drugs losing patent protection or being withdrawn from the market are simply not being replaced by new therapies – the pharmaceutical market model is no longer functioning effectively and most pharmaceutical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. |
Im Buch
Ergebnisse 1-5 von 36
Seite 27
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... Nat Rev Mol Cell Biol 4(3):237–243 Hunter PJ, Crampin EJ, Nielsen PMF (2008) Bioinformatics, multiscale modeling and the IUPS physiome project. Brief Bioinf 9(4):333–343 21. 22. 23. 24. 25. 26. 27. 28. 29. 30. 1 Functional Genomics ...
Seite 28
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... Nat Rev Genet 11(1):31–46 Zhang J, Chiodini R, Badr A, Zhang G (2011) The impact of next-generation sequencing on genomics. J Genet Genomics 38(3):95–109 Martin JA, Wang Z (2011) Next-generation transcriptome assembly. Nat Rev Genet 12 ...
Seite 29
... Nat Rev Genet 11(10):685–696 Pastinen T (2010) Genome-wide allele-specific analysis: insights into regulatory variation Nat Rev Genet 11(8):533–538 Thomas T, Gilbert J, Meyer F (2012) Metagenomics—a guide from sampling to data analysis ...
... Nat Rev Genet 11(10):685–696 Pastinen T (2010) Genome-wide allele-specific analysis: insights into regulatory variation Nat Rev Genet 11(8):533–538 Thomas T, Gilbert J, Meyer F (2012) Metagenomics—a guide from sampling to data analysis ...
Seite 30
... Nat Rev Genet 1(3):231–236 Mount DR (2004) Bioinformatics: sequence and genome analysis. Cold Spring Harbor Laboratory Press, Second Ashburner M, Ball CA, Blake JA, Botstein D, Butler H, Cherry JM, Davis AP, Dolinski K, Dwight SS, Eppig ...
... Nat Rev Genet 1(3):231–236 Mount DR (2004) Bioinformatics: sequence and genome analysis. Cold Spring Harbor Laboratory Press, Second Ashburner M, Ball CA, Blake JA, Botstein D, Butler H, Cherry JM, Davis AP, Dolinski K, Dwight SS, Eppig ...
Seite 31
... Nat Rev Genet 11(3):191–203 Rakyan VK, Down TA, Balding DJ, Beck S (2011) Epigenome-wide association studies for common human diseases. Nat Rev Genet 12(8):529–541 Birney E, Stamatoyannopoulos JA, Dutta A, Guigó R, Gingeras TR ...
... Nat Rev Genet 11(3):191–203 Rakyan VK, Down TA, Balding DJ, Beck S (2011) Epigenome-wide association studies for common human diseases. Nat Rev Genet 12(8):529–541 Birney E, Stamatoyannopoulos JA, Dutta A, Guigó R, Gingeras TR ...
Inhalt
3 | |
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 |
Andere Ausgaben - Alle anzeigen
Systems Biology: Integrative Biology and Simulation Tools Aleš Prokop,Béla Csukás Keine Leseprobe verfügbar - 2013 |
Systems Biology: Integrative Biology and Simulation Tools Ales Prokop,Bela Csukas Keine Leseprobe verfügbar - 2015 |
Systems Biology: Integrative Biology and Simulation Tools Aleš Prokop,Béla Csukás Keine Leseprobe verfügbar - 2013 |
Häufige Begriffe und Wortgruppen
activation agent-based modeling algorithm alignment analysis annotation apoptosis approach Bayesian networks biochemical Bioinformatics biological networks biological systems biomedical BioModels Database cancer cell cycle CellML cellular complex components Comput Biol data sets data types database disease distribution drug dynamics experimental function gene expression gene expression data gene networks Gene Ontology gene regulatory networks genetic genome graph human identify inference input integration kinetic metabolic networks metabolomics methods microarray microRNA modules molecular molecules multiple multiscale Nat Rev Natl Acad Sci nodes Nucleic Acids Res parameters perturbations Petri nets phenotype PLoS prediction Proc Natl Acad processes properties protein protein-protein interactions proteomics random RBNs reactions receptor regulation represent robustness rule-based modeling SBML scale SED-ML sequencing signal transduction signaling pathways silico simulation specific structure synaptic plasticity Syst Biol systems biology target topological transcription factors tumor variables yeast