Mathematical Principles in Bioinformatics

This textbook provides a solid mathematical foundation for biology students,with an understanding of how to implement them in bioinformatics problems. It discusses and provides principles that relate to current open problems in bioinformatics,and considers a variety of models. Prerequisites include first courses in linear algebra,probability and statistics,and mathematical analysis. The content is divided into two parts,with the first part introducing basic concepts and the second part describing several bioinformatics principles using a rigorous mathematical formulation. The book focuses on the governing principle in biology and provides plenty of alignment-free methods,which cannot be found in any other book.

Format: Hardback
Length: 167 pages
Publication date: 12 January 2024
Publisher: Springer International Publishing AG

This comprehensive textbook offers an accessible introduction to bioinformatics for students in mathematics with no prior biology knowledge. It equips biology students with robust mathematical tools and provides insights into their practical application in bioinformatics problems. In addition to covering foundational concepts, the text introduces innovative approaches to understanding biological sequences. Its concise presentation sets it apart, delving into current open problems in bioinformatics while considering diverse models. The convex hull principle is highlighted, fostering a new interdisciplinary research domain at the intersection of biology, mathematics, and computer science. Prerequisites include first courses in linear algebra, probability and statistics, and mathematical analysis. Researchers in mathematics, biology, and math-biology will also find valuable aspects of this text.

The textbook is organized into two parts. The first part comprises three chapters, providing a foundational understanding of bioinformatics. Chapter 1 offers a biological background in molecular biology for mathematicians, Chapter 2 introduces biological databases commonly used, and Chapter 3 explores alignment methods, including global/local alignment, heuristic alignment, and multiple alignment.

The second part, consisting of five chapters, delves into various bioinformatics principles using a rigorous mathematical framework. Chapter 4 introduces the time-frequency spectral principle and its applications in bioinformatics. Chapters 5 a.

b.

c.

d.

e. 5.a introduces the hidden Markov model and its applications in bioinformatics. Chapter 5.b discusses sequence similarity and sequence alignment methods. Chapter 5.c explores phylogenetic analysis and tree construction. Chapter 5.d introduces machine learning techniques in bioinformatics. Chapter 5.e discusses database searching and retrieval methods.

Throughout the textbook, real-world examples and case studies are used to illustrate the theoretical concepts and their practical applications in bioinformatics. The authors have extensive experience in teaching bioinformatics courses and have incorporated their research works and lecture notes into the text.

This textbook is an invaluable resource for students seeking to bridge the gap between mathematics and biology, providing them with the necessary mathematical tools and insights to excel in bioinformatics. Whether you are a mathematics student interested in exploring the biological world or a biology student seeking to enhance your computational skills, this textbook will be a valuable companion on your academic journey.

Weight: 481g
Dimension: 235 x 155 (mm)
ISBN-13: 9783031482946
Edition number: 1st ed. 2023