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An Introduction to Programming for Bioscientists: A Python-Based Primer

Computing has revolutionized the biological sciences over the past several decades, such that virtually all contemporary research in molecular biology, biochemistry, and other biosciences utilizes computer programs. The computational advances have come on many fronts, spurred by fundamental developm...

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Detalles Bibliográficos
Autores principales: Ekmekci, Berk, McAnany, Charles E., Mura, Cameron
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4896647/
https://www.ncbi.nlm.nih.gov/pubmed/27271528
http://dx.doi.org/10.1371/journal.pcbi.1004867
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author Ekmekci, Berk
McAnany, Charles E.
Mura, Cameron
author_facet Ekmekci, Berk
McAnany, Charles E.
Mura, Cameron
author_sort Ekmekci, Berk
collection PubMed
description Computing has revolutionized the biological sciences over the past several decades, such that virtually all contemporary research in molecular biology, biochemistry, and other biosciences utilizes computer programs. The computational advances have come on many fronts, spurred by fundamental developments in hardware, software, and algorithms. These advances have influenced, and even engendered, a phenomenal array of bioscience fields, including molecular evolution and bioinformatics; genome-, proteome-, transcriptome- and metabolome-wide experimental studies; structural genomics; and atomistic simulations of cellular-scale molecular assemblies as large as ribosomes and intact viruses. In short, much of post-genomic biology is increasingly becoming a form of computational biology. The ability to design and write computer programs is among the most indispensable skills that a modern researcher can cultivate. Python has become a popular programming language in the biosciences, largely because (i) its straightforward semantics and clean syntax make it a readily accessible first language; (ii) it is expressive and well-suited to object-oriented programming, as well as other modern paradigms; and (iii) the many available libraries and third-party toolkits extend the functionality of the core language into virtually every biological domain (sequence and structure analyses, phylogenomics, workflow management systems, etc.). This primer offers a basic introduction to coding, via Python, and it includes concrete examples and exercises to illustrate the language’s usage and capabilities; the main text culminates with a final project in structural bioinformatics. A suite of Supplemental Chapters is also provided. Starting with basic concepts, such as that of a “variable,” the Chapters methodically advance the reader to the point of writing a graphical user interface to compute the Hamming distance between two DNA sequences.
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spelling pubmed-48966472016-06-16 An Introduction to Programming for Bioscientists: A Python-Based Primer Ekmekci, Berk McAnany, Charles E. Mura, Cameron PLoS Comput Biol Education Computing has revolutionized the biological sciences over the past several decades, such that virtually all contemporary research in molecular biology, biochemistry, and other biosciences utilizes computer programs. The computational advances have come on many fronts, spurred by fundamental developments in hardware, software, and algorithms. These advances have influenced, and even engendered, a phenomenal array of bioscience fields, including molecular evolution and bioinformatics; genome-, proteome-, transcriptome- and metabolome-wide experimental studies; structural genomics; and atomistic simulations of cellular-scale molecular assemblies as large as ribosomes and intact viruses. In short, much of post-genomic biology is increasingly becoming a form of computational biology. The ability to design and write computer programs is among the most indispensable skills that a modern researcher can cultivate. Python has become a popular programming language in the biosciences, largely because (i) its straightforward semantics and clean syntax make it a readily accessible first language; (ii) it is expressive and well-suited to object-oriented programming, as well as other modern paradigms; and (iii) the many available libraries and third-party toolkits extend the functionality of the core language into virtually every biological domain (sequence and structure analyses, phylogenomics, workflow management systems, etc.). This primer offers a basic introduction to coding, via Python, and it includes concrete examples and exercises to illustrate the language’s usage and capabilities; the main text culminates with a final project in structural bioinformatics. A suite of Supplemental Chapters is also provided. Starting with basic concepts, such as that of a “variable,” the Chapters methodically advance the reader to the point of writing a graphical user interface to compute the Hamming distance between two DNA sequences. Public Library of Science 2016-06-07 /pmc/articles/PMC4896647/ /pubmed/27271528 http://dx.doi.org/10.1371/journal.pcbi.1004867 Text en © 2016 Ekmekci et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Education
Ekmekci, Berk
McAnany, Charles E.
Mura, Cameron
An Introduction to Programming for Bioscientists: A Python-Based Primer
title An Introduction to Programming for Bioscientists: A Python-Based Primer
title_full An Introduction to Programming for Bioscientists: A Python-Based Primer
title_fullStr An Introduction to Programming for Bioscientists: A Python-Based Primer
title_full_unstemmed An Introduction to Programming for Bioscientists: A Python-Based Primer
title_short An Introduction to Programming for Bioscientists: A Python-Based Primer
title_sort introduction to programming for bioscientists: a python-based primer
topic Education
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4896647/
https://www.ncbi.nlm.nih.gov/pubmed/27271528
http://dx.doi.org/10.1371/journal.pcbi.1004867
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