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Bioinformatics Algorithms: Design and Implementation in Python provides a comprehensive book on many of the most important bioinformatics problems, putting forward the best algo… Read more
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Immediately download your ebook while waiting for your print delivery. No promo code is needed.
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.
Bioinformatics and Computational Biology researchers, biomedical engineers, as well as undergrad and postgraduate students in Bioinformatics and Computational Biology
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
MR
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.
PF