Computational Systems Biology

Systems Biology is concerned with the quantitative study of complex biosystems at the molecular, cellular, tissue, and systems scales. Its focus is on the function of the system as a whole, rather than on individual parts.

This exciting new arena applies mathematical modeling and engineering methods to the study of biological systems. This book is the first of its kind to focus on the newly emerging field of systems biology with an emphasis on computational approaches. The work covers new concepts, methods for information storage, mining and knowledge extraction, reverse engineering of gene and metabolic networks, as well as modelling and simulation of multi-cellular systems. Central themes include strategies for predicting biological properties and methods for elucidating structure-function relationships.

Graduate students and researchers in Bioinformatics, Biocomputing, Theoretical Biology, Biochemistry/Biophysics, and Cell Biology.

CONTENT

1. Introducing Computational Systems Biology. A Kriete and R Eils I. Enabling Information and Integration Technologies for Systems Biology:
2. Databases for Systems Biology. J Eils, C Lawerenz, K Astrahantseff, M Ginkel, and R Eils Natural Language Processing and Ontology-enhanced Biomedical Literature Mining for Systems Biology. X Hu Integrated Imaging Informatics. B Parvin, G Fontenay, Q Yang, and MH Barcellos-Hoff Simpathica: A Computational Systems Biology Tool within the Valis Bioinformatics Environment. B Mishra, M Antoniotti, S Paxia and N Ugel Standards, Platforms and Applications. HM Sauro II. Foundations of Biochemical Network Analysis and Modeling
3. Introduction to Computational Models of Biochemical Reaction Networks. FJ Bruggeman, BM Bakker, JJ Hornberg, and HV Westerhoff
4. Biological Foundations of Signal Transduction and the Systems Biology Perspective. U Klingmüller
5. Reconstruction of Metabolic Network from Genome Information and Its Structural and Functional Analysis. H-W Ma and A-P Zeng
6. Integrated Regulatory and Metabolic Models. M.W. Covert III. Computer Simulations of Dynamic Networks
7. A Discrete Approach to Network Modeling. R Laubenbacher and P Mendes
8. Gene Networks: Estimation, Modeling and Simulation. S Imoto, H Matsuno, and S Miyano
9. Computational models for circadian rhythms: Deterministic versus stochastic approaches. J-C Leloup, D Gonze, and A Goldbeter IV. Multi-Scale Representations of Cells and Emerging Phenotypes
10. Multistability and Multicellularity: Cell Fates as High-dimensional Attractors of Gene Regulatory Networks. S Huang
11. Spatio-Temporal Systems Biology. A Ghosh, D Miller, R Zou, B Sokhansanj,and A Kriete
12. Cytomics—from cell states to predictive medicine. G Valet, RF Murphy, JP Robinson, A Tárnok, A Kriete
13. The IUPS Physiome Project: Progress and Plans. P Hunter, K Burrowes, J Fernandez, P Nielsen, N Smith, and M Tawhai Subject Index