Mastering Python for Bioinformatics
O'Reilly Media (Verlag)
978-1-0981-0088-9 (ISBN)
Ken Youens-Clark, author of Tiny Python Projects (Manning), demonstrates not only how to write effective Python code but also how to use tests to write and refactor scientific programs. You'll learn the latest Python features and tools - including linters, formatters, type checkers, and tests - to create documented and tested programs. You'll also tackle 14 challenges in Rosalind, a problem-solving platform for learning bioinformatics and programming.
Create command-line Python programs to document and validate parameters
Write tests to verify refactor programs and confirm they're correct
Address bioinformatics ideas using Python data structures and modules such as Biopython
Create reproducible shortcuts and workflows using makefiles
Parse essential bioinformatics file formats such as FASTA and FASTQ
Find patterns of text using regular expressions
Use higher-order functions in Python like filter(), map(), and reduce()
Ken Youens-Clark works as a Data Engineer at The Critical Path Institute where he helps partners in industry, academia, and government find novel drug therapies for diseases ranging from cancer and tuberculosis to thousands of rare diseases. His career in bioinformatics began in 2001 when he joined a plant genomics project at Cold Spring Harbor Laboratory under the direction of Dr. Lincoln Stein, a prominent author of books and modules in Perl and an early advocate for open software, data, and science. In 2014 Ken moved to Tucson, AZ, to work as a Senior Scientific Programmer at the University of Arizona where he completed a MS in Biosystems Engineering in 2019. While at UA, Ken enjoyed teaching programming and bioinformatics skills, and used some of those ideas in his first book, Tiny Python Projects (Manning, 2020), which uses a test-driven development approach to teaching Python.
Erscheinungsdatum | 20.05.2021 |
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Verlagsort | Sebastopol |
Sprache | englisch |
Maße | 178 x 233 mm |
Themenwelt | Informatik ► Datenbanken ► Data Warehouse / Data Mining |
ISBN-10 | 1-0981-0088-3 / 1098100883 |
ISBN-13 | 978-1-0981-0088-9 / 9781098100889 |
Zustand | Neuware |
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