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New Frontiers of Network Analysis in Systems Biology

by Ma'ayan, Avi.
Authors: MacArthur, Ben D.%editor. | SpringerLink (Online service) Physical details: X, 199 p. 31 illus., 6 illus. in color. online resource. ISBN: 9400743300 Subject(s): Medicine. | Gene expression. | Biotechnology. | Proteomics. | Biological models. | Cytology. | Biomedicine. | Biomedicine general. | Cell Biology. | Systems Biology. | Proteomics. | Gene Expression. | Biotechnology.
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E-Book E-Book AUM Main Library 610 (Browse Shelf) Not for loan

Preface -- 1. Gene expression profiling of single cells, Fumio Arai et al -- 2. Cell Fate Regulatory Networks, Sonya J. Ridden and Ben D. MacArthur -- 3. Noise in Regulatory Networks, Srinandan Dasmahapatra -- 4. Generalised Modelling in Systems Biology, Thilo Gross -- 5. Relative quantification mass spectrometry using iTRAQ isobaric tags, Richard D. Unwin et al -- 6. Deciphering Protein Complexes and Protein Interaction Networks for Stem Cell Pluripotency, Jianlong Wang -- 7. Omics era in stem cell research: data integration of multi-regulatory layers, Ana Sevilla et al -- 8. High Throughput Affinity Purification and Mass Spectrometry to Determine Protein Complex Interactions, Anna Malovannaya et al -- 9. Network Pharmacology to Aid the Drug Discovery Process, Ruth Dannenfelser et al -- 10. What can networks do for you?, Bernhard M. Schuldt et al -- Index.

The rapidly developing field of systems biology is influencing many aspects of biological research and is expected to transform biomedicine. Some emerging offshoots and specialized branches in systems biology are receiving particular attention and are becoming highly active areas of research. This collection of invited reviews describes some of the latest cutting-edge experimental and computational advances in these emerging sub-fields of systems biology. In particular, this collection focuses on the study of mammalian embryonic stem cells; new technologies involving mass-spectrometry proteomics; single cell measurements; methods for modeling complex stochastic systems; network-based classification algorithms; and the revolutionary emerging field of systems pharmacology.

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