Integer linear programming (ILP) is a powerful modeling and optimization technique that is increasingly used in biology. This how-to and why-do text introduces ILP through the lens of computational and systems biology, with 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. It aims to teach the logic of modeling and solving problems with ILP and the practical work flow involved in using ILP in biology, suitable for entry-level and advanced courses and for specialists.

Format: Hardback
Length: 428 pages
Publication date: 13 June 2019
Publisher: Cambridge University Press

Integer linear programming (ILP) is a versatile modeling and optimization technique that is increasingly being used in non-traditional ways in biology, with the potential to transform biological computation. However, few biologists are aware of its existence. This how-to and why-do text introduces ILP through the lens of computational and systems biology, using 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 its power. This book aims to teach the logic of modeling and solving problems with ILP and to teach the practical workflow 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, as well as a source for specialists. Numerous exercises and accompanying software (in Python and Perl) demonstrate the concepts.

Introduction to Integer Linear Programming (ILP) in Biology

Integer linear programming (ILP) is a powerful modeling and optimization technique that has been increasingly used in various fields, including biology. In this text, we will introduce ILP through the lens of computational and systems biology, providing a comprehensive guide for both beginners and experts.

What is Integer Linear Programming?

ILP is a mathematical approach that involves solving optimization problems with linear constraints. It is a technique that allows for the efficient modeling and analysis of complex systems, such as biological systems. By representing the system as a set of linear equations and constraints, ILP can be used to find the optimal solution to a given problem.

Applications of Integer Linear Programming in Biology

ILP has numerous applications in biology, ranging from genomics to ecology. In genomics, ILP can be used to optimize gene expression patterns, identify regulatory networks, and predict protein structures. In phylogenetics, ILP can be used to reconstruct phylogenetic trees, estimate evolutionary rates, and identify conserved regions. In RNA, protein folding, and network analysis, ILP can be used to model complex biological processes, such as protein folding, gene expression regulation, and network dynamics. In cancer, ILP can be used to optimize drug treatments, predict patient outcomes, and identify potential drug targets. In ecology, ILP can be used to model population dynamics, habitat selection, and resource allocation.

Why is Integer Linear Programming Important in Biology?

ILP is important in biology because it allows for the efficient modeling and analysis of complex systems. By leveraging the power of linear programming, biologists can gain insights into the behavior of biological systems and develop effective strategies for addressing biological problems.

Getting Started with Integer Linear Programming in Biology

If you are new to ILP in biology, it is important to start with a basic understanding of the principles and techniques. This text will provide you with the necessary background information to get started. We will cover topics such as linear programming, optimization, and constraint satisfaction, as well as the specific applications of ILP in biology.

Examples of Integer Linear Programming in Biology

To demonstrate the power of ILP in biology, we will provide in-depth examples from various fields. These examples will cover topics such as genomics, phylogenetics, RNA, protein folding, network analysis, cancer, ecology, co-evolution, DNA sequencing, sequence analysis, pedigree and sibling inference, haplotyping, and more. Each example will be accompanied by code and explanations to help you understand the underlying principles and apply them to your own research.

Conclusion

Integer linear programming is a versatile modeling and optimization technique that has the potential to transform biological computation. By introducing ILP through the lens of computational and systems biology, we hope to provide a comprehensive guide for both beginners and experts. With the help of this text, you will be able to leverage the power of ILP to address biological problems and gain insights into the behavior of complex biological systems.

Weight: 946g
Dimension: 188 x 261 x 25 (mm)
ISBN-13: 9781108421768