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.
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Table of Contents
Part I: Bioinformatics Basics 1. Introduction 2. Relevant Biological Concepts 3. Algorithms and Python: Introduction 4. Optimization: Basic Concepts and Algorithms
Part II: Sequence Analysis Algorithms 5. Basic Processing of DNA Sequences: Transcription and Translation 6. Finding Patterns in Sequences 7. Pairwise Sequence Alignment 8. Searching Similar Sequences in Databases 9. Multiple Sequence Alignment 10. Phylogenetic Analysis 11. Motif Discovery 12. Hidden Markov Models 13. Stochastic Algorithms
Part III: Graph and Large-Scale Sequencing Data Processing 14. Graphs 15. Biological Networks 16. Assembling Reads into Genomes 17. Matching Reads to Reference Sequences
Part IV: Conclusions 18. Further Reading and Resources 19. Final Words
Appendix: Python Reference Functions
Authors
Miguel Rocha Associate Professor of Informatics and Senior Researcher, University of Minho, Portugal.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 Assistant Researcher, Ipatimup/i3S, Portugal.
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.
