000			02450nam a22001577a 4500
020			_a9780815345688
082			_a570.15195 _bVOI-F
100			_a Voit , Eberhard O.
245			_aA First Course in Systems Biology/ _c Eberhard O. Voit
260			_aNew York: _bTAYLOR & FRANCIS, _c2013.
300			_a445 P.
505			_a 1. Biological Systems 2. Introduction to Mathematical Modeling 3. Static Network Models 4. The Mathematics of Biological Systems 5. Parameter Estimation 6. Gene Systems 7. Protein Systems 8. Metabolic Systems 9. Signaling Systems 10. Population Systems 11. Integrative Analysis of Genome, Protein, and Metabolite Data: A Case Study in Yeast 12. Physiological Modeling: The Heart as an Example 13. Systems Biology in Medicine and Drug Development 14. Design of Biological Systems 15. Emerging Topics in Systems Biology
520			_aA First Course in Systems Biology is an introduction for advanced undergraduate and graduate students to the growing field of systems biology. Its main focus is the development of computational models and their applications to diverse biological systems. The book begins with the fundamentals of modeling, then reviews features of the molecular inventories that bring biological systems to life and discusses case studies that represent some of the frontiers in systems biology and synthetic biology. In this way, it provides the reader with a comprehensive background and access to methods for executing standard systems biology tasks, understanding the modern literature, and launching into specialized courses or projects that address biological questions using theoretical and computational means. New topics in this edition include: default modules for model design, limit cycles and chaos, parameter estimation in Excel, model representations of gene regulation through transcription factors, derivation of the Michaelis-Menten rate law from the original conceptual model, different types of inhibition, hysteresis, a model of differentiation, system adaptation to persistent signals, nonlinear nullclines, PBPK models, and elementary modes. The format is a combination of instructional text and references to primary literature, complemented by sets of small-scale exercises that enable hands-on experience, and large-scale, often open-ended questions for further reflection.
650			_a Systems biology. Computational biology. Systems Biology.
942			_cBK
999			_c261106 _d261106