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Practical Systems Biology: Volume 61: Society for Experimental Biology

Editat de Alistair Hetherington, Claire Grierson
en Limba Engleză Hardback – iun 2008
Systems biology is the study of organisms as interacting networks of genes, proteins and reactions. Practical Systems Biology provides a detailed overview of the different approaches used in this relatively new discipline, integrating bioinformatics, genomics, proteomics and metabolomics. Various areas of research are also discussed, including the use of computational models of biological processes, and post-genomic research.
Each chapter is written by an experienced researcher and gives an excellent account of various issues of systems biology that is suitable for postgraduate and postdoctoral researchers who are interested in this expanding area of science.
 
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Specificații

ISBN-13: 9780415407809
ISBN-10: 041540780X
Pagini: 236
Ilustrații: 105 b/w images, 5 halftones and 50 line drawings
Dimensiuni: 156 x 234 x 20 mm
Greutate: 0.5 kg
Ediția:1
Editura: CRC Press
Colecția Taylor & Francis
Seria Society for Experimental Biology


Public țintă

Postgraduate and Professional

Cuprins

1. What is Systems Biology and Why Do It?  2. The Circuitry of Circadian Rhythms  3. Intracellular Signalling During Bacterial Chemotaxis  4. Intercellular Signalling and Self-Organisation of Dictyostelium discoideum  5. Modelling the Mammalian Heart  6. Using Mathematical Models to Probe Experimental Data  7. Bioinformatic Approaches to Biological Systems  8. Modelling Tools for Systems Biology and MAPK Cascade Dynamics  9. An Introduction to Metabolic Modelling  10. Vertical Systems Biology: From DNA to Flux and Back  11. Cell Sampling and RNA Amplification Methods  12. Proteomics Methods  13. Towards a Virtual Devleoping Organ 

Descriere

Practical Systems Biology provides a detailed overview of the different approaches used in this relatively new discipline, integrating bioinformatics, genomics, proteomics and metabolomics. Various areas of research are also discussed, including the use of computational models of biological processes, and post-genomic research.