Bioinformatics Algorithms

Design and Implementation in Python
Erscheinungsjahr 2018
ISBN: 978-0-12-812520-5
Verlag: Elsevier Science Publishing Co Inc

Buch, Englisch, 400 Seiten, Format (B × H): 233 mm x 190 mm, Gewicht: 838 g

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.

Zielgruppe

<p>Bioinformatics and Computational Biology researchers, biomedical engineers, as well as undergrad and post-graduate students in Bioinformatics and Computational Biology.</p>

Autoren/Hrsg.

Rocha, Miguel

Ferreira, Pedro G.

Fachgebiete

• Medizin | Veterinärmedizin Medizin | Public Health | Pharmazie | Zahnmedizin Medizin, Gesundheitswesen Medizintechnik, Biomedizintechnik, Medizinische Werkstoffe
• Medizin | Veterinärmedizin Medizin | Public Health | Pharmazie | Zahnmedizin Medizin, Gesundheitswesen Medizinische Mathematik & Informatik
• Technische Wissenschaften Sonstige Technologien | Angewandte Technik Medizintechnik, Biomedizintechnik

Inhaltsverzeichnis

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

Über Autor(innen)

Rocha, Miguel
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.

Ferreira, Pedro G.
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.