Integer Linear Programming in Computational and Systems Biology An Entry-Level Text and Course
Integer Linear Programming in Computational and Systems Biology: An Entry-Level Text and Course by Dan Gusfield, published by Cambridge University Press on June 13, 2019, spans 428 pages and is presented in English. This book introduces integer linear programming (ILP) as a modeling and optimization technique that is gaining traction in biological computation. It aims to familiarize readers with ILP through practical examples drawn from various fields, including genomics, phylogenetics, and cancer research, making it accessible to those without prior knowledge in biology or computation.
Readers will find a comprehensive guide that teaches both the logic behind modeling and the practical workflow for applying ILP in biological contexts. The text includes numerous exercises and software tools in Python and Perl to reinforce learning. By focusing on topics such as optimization and data science, this book serves as a valuable resource for both entry-level and advanced students in biological and computational disciplines, as well as specialists seeking to enhance their understanding of ILP applications in life sciences.
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Integer linear programming (ILP) is a versatile modeling and optimization technique that is increasingly used in non-traditional ways in biology, with the potential to transform biological computation. However, few biologists know about it. This how-to and why-do text introduces ILP through the lens of computational and systems biology. It uses in-depth examples from genomics, phylogenetics, RNA, protein folding, network analysis, cancer, ecology, co-evolution, DNA sequencing, sequence analysis, pedigree and sibling inference, haplotyping, and more, to establish the power of ILP. This book aims to teach the logic of modeling and solving problems with ILP, and to teach the practical ‘work flow’ involved in using ILP in biology. Written for a wide audience, with no biological or computational prerequisites, this book is appropriate for entry-level and advanced courses aimed at biological and computational students, and as a source for specialists. Numerous exercises and accompanying software (in Python and Perl) demonstrate the concepts.
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