Bioinformatics Algorithms : Design and Implementation in Python

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.

• Presents an ideal text for bioinformatics students with little to no knowledge of computer programming
• Based on over 12 years of pedagogical materials used by the authors in their own classrooms
• Features a companion website with downloadable codes and runnable examples (such as using Jupyter Notebooks) and exercises relating to the book

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.