TY - GEN AU - Robeva,Raina S. TI - Algebraic and discrete mathematical methods for modern biology SN - 9780128012130 U1 - 570.151 23 PY - 2015/// CY - Amsterdam PB - Academia Press KW - Biology KW - Mathematical models KW - Biomathematics. N1 - Includes bibliographical references and index; 1. Graph theory for systems biology: interval graphs, motifs, and pattern recognition -- 2. Food webs and graphs -- 3. Adaptation and fitness graphs -- 4. Signaling networks : asynchronous Boolean models -- 5. Dynamics of complex Boolean networks: canalization, stability, and criticality -- 6. Steady state analysis of Boolean models: a dimension reduction approach -- 7. Biomodel engineering with petri nets -- 8. Transmission of infectious diseases : data, models, and simulations -- 9. Disease transmission dynamics on networks: network structure versus disease dynamics-- 10. Predicting correlated responses in quantitative traits under selection: a linear algebra approach -- 11. Metabolic analysis: algebraic and geometric methods -- 12. Reconstructing the phylogeny: computational methods -- 13. RNA secondary structures : combinatorial models and folding algorithms -- 14. RNA secondary structures: an approach through pseudoknots and fatgraphs -- Acknowledgments -- References -- Index N2 - Written by experts in both mathematics and biology, Algebraic and Discrete Mathematical Methods for Modern Biology offers a bridge between math and biology, providing a framework for simulating, analyzing, predicting, and modulating the behavior of complex biological systems. Each chapter begins with a question from modern biology, followed by the description of certain mathematical methods and theory appropriate in the search of answers. Every topic provides a fast-track pathway through the problem by presenting the biological foundation, covering the relevant mathematical theory, and highlighting connections between them. Many of the projects and exercises embedded in each chapter utilize specialized software, providing students with much-needed familiarity and experience with computing applications, critical components of the "modern biology" skill set. This book is appropriate for mathematics courses such as finite mathematics, discrete structures, linear algebra, abstract/modern algebra, graph theory, probability, bioinformatics, statistics, biostatistics, and modeling, as well as for biology courses such as genetics, cell and molecular biology, biochemistry, ecology, and evolution ER -