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Principles of Computational Cell Biology: from protein complexes to cellur Networks.
This first textbook of its kind provides an ideal introduction to the field for students of biology and bioinformatics. Carefully designed study exercises -- with corresponding answers -- offer excellent support for those preparing for exams in these subjects, and help introduce the more technical a...
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| Format: | Printed Book |
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Weinheim
Wiley-VCH
2008
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| Subjects: |
| LEADER | 03584nam a2200169Ia 4500 | ||
|---|---|---|---|
| 999 | |c 27693 |d 27693 | ||
| 020 | |a 9783527315550 | ||
| 082 | |a 571.60113 HEL-P | ||
| 100 | |a Volkhard Helms | ||
| 245 | |a Principles of Computational Cell Biology: from protein complexes to cellur Networks. | ||
| 260 | |a Weinheim |b Wiley-VCH |c 2008 | ||
| 300 | |a xii, 277 pages ; 24 cm | ||
| 505 | |a Networks in biological cells. Some basics about networks ; Biological background ; Cellular pathways ; Ontologies and databases ; Methods in cellular modeling -- Algorithms on mathematical graphs. Primer on mathematical graphs ; A few words about algorithms and computer programs ; Data structures for graphs ; Dijkstra's algorithm ; Minimum spanning tree ; Graph drawing -- Protein-protein interaction networks : pairwise connectivity. Principles of protein-protein interactions ; Experimental high-throughput methods of detecting ; Bioinformatic prediction of protein-protein interactions ; Bayesian networks for judging the accuracy of interactions ; Bayesian networks for judging the accuracy of interactions ; Protein domain networks -- Protein-protein interaction networks : structural hierarchies. Protein interaction graph networks ; Finding cliques ; Random graphs ; Scale-free graphs ; Detecting communities in networks ; Modular decomposition ; Network growth mechanisms -- Gene regulatory networks. Regulation of gene transcription at promoters ; Gene regulatory networks ; Graph theoretical models ; Dynamic models ; Motifs -- Metabolic networks. Introduction ; Stoichiometric matrix ; Linear algebra primer ; Flux balance analysis ; Double description method ; Extreme pathways and elementary modes ; Minimal cut sets ; High-flux backbone -- Kinetic modeling of cellular processes. Ordinary differential equation models. Modeling cellular feedback loops by ODEs ; Partial differential equations ; Dynamic Monte Carlo (Gillespie algorithm) ; Stochastic modeling of a small molecular network ; Parameter optimization with generic algorithms -- Structures of protein complexes and subcellular structures. Examples of protein complexes ; Complexeome of S. cerevisiae ; Experimental determination of three-dimensional structures of protein complexes ; Density fitting ; Fourier transformation ; Advanced density fitting ; FFT protein-protein docking ; Prediction of assemblies from pairwise docking ; Electron tomography -- Biomolecular association and binding. Modeling by homology ; Structural properties of protein-protein interfaces ; Bioinformatic prediction of protein-protein interfaces ; Forces important for biomolecular association ; Protein-protein association ; Assembly of macromolecular complexes : the ribosome -- Integrated network. Correlating interactome and gene regulation ; Response of Gene regulatory network to outside stimuli ; Integrated analysis of metabolic and regulatory networks -- Outlook. | ||
| 520 | |a This first textbook of its kind provides an ideal introduction to the field for students of biology and bioinformatics. Carefully designed study exercises -- with corresponding answers -- offer excellent support for those preparing for exams in these subjects, and help introduce the more technical aspects of the topic while keeping maths to a minimum. In particular the text focuses on a network-based approach to the study of cellular systems. | ||
| 650 | |a Cytology--Computer simulation. Cytology--Mathematical models. | ||
| 942 | |c BK | ||
| 952 | |0 0 |1 0 |4 0 |6 571_601130000000000_HELP |7 0 |9 30297 |a DCB |b DCB |d 2015-09-01 |l 0 |o 571.60113 HEL-P |p DCB1093 |r 2015-09-01 |w 2019-07-19 |y BK | ||