Bioinformatics Algorithms: Design and Implementation in Python

by Miguel Rocha, Pedro G. Ferreira

Overview

Bioinformatics Algorithms: Design and Implementation in Python provides a comprehensive book on many of the most important bioinformatics problems, putting forward the best algorithms and showing how to implement them. The book focuses on the use of the Python programming language and its algorithms, which is quickly becoming the most popular language in the bioinformatics field. Readers will find the tools they need to improve their knowledge and skills with regard to algorithm development and implementation, and will also uncover prototypes of bioinformatics applications that demonstrate the main principles underlying real world applications.

Product Details

ISBN-13:	9780128125205
Publisher:	Elsevier Science
Publication date:	06/12/2018
Pages:	400
Product dimensions:	7.50(w) x 9.25(h) x (d)

About the Author

Miguel Rocha is an Associate Professor at the University of Minho (Portugal), where he

teaches in the Informatics Department and has a senior researcher position in the Centre

of Biological Engineering. He is the Director and founder of the Master in Bioinformatics

since 2007, teaching and coordinating curricular units related to Bioinformatics algorithms

and tools, data analysis and machine learning. His research is mainly devoted to

Bioinformatics subjects, including the development of tools and algorithms for metabolic

modelling andomics data analysis.

Pedro G. Ferreira is an Assistant Researcher at Ipatimup/i3S (Portugal), where he has an FCT Investigator Starting grant. He develops research on computational biology in particular in the fields of cancer and population genomics. He has collaborated with several research groups and has been involved in different international consortia including ICGC-CLL, GEUVADIS or GTEx. He has intensive training in Bioinformatics and experience in genomics start-up environment where he has developed information systems for personal genomics data interpretation.

Table of Contents

Part I: Bioinformatics Basics1. Introduction2. Relevant Biological Concepts3. Algorithms and Python: Introduction4. Optimization: Basic Concepts and Algorithms

Part II: Sequence Analysis Algorithms5. Basic Processing of DNA Sequences: Transcription and Translation6. Finding Patterns in Sequences7. Pairwise Sequence Alignment8. Searching Similar Sequences in Databases9. Multiple Sequence Alignment10. Phylogenetic Analysis11. Motif Discovery12. Hidden Markov Models13. Stochastic Algorithms

Part III: Graph and Large-Scale Sequencing Data Processing14. Graphs15. Biological Networks16. Assembling Reads into Genomes17. Matching Reads to Reference Sequences

Part IV: Conclusions18. Further Reading and Resources19. Final Words

Appendix: Python Reference Functions

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From the Publisher

Provides a basis for understanding algorithm development and implementation in Python, with limited computer programming experience needed