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Bioinformatics software for genomic: a systematic review on GitHub
Bioinformatics is an interdisciplinary field that develops software methods and tools to understand biological data. Actually, in branches such as genomics, there are a large number of software tools that serve to support different processes such as genetic data sequencing, genomes, biotechnological...
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Published in: | PeerJ preprints 2018-11 |
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Main Authors: | , , , |
Format: | Article |
Language: | English |
Subjects: | |
Online Access: | Get full text |
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Summary: | Bioinformatics is an interdisciplinary field that develops software methods and tools to understand biological data. Actually, in branches such as genomics, there are a large number of software tools that serve to support different processes such as genetic data sequencing, genomes, biotechnological applications, among other activities, which contribute knowledge to different fields of study such as environment, medicine, energy and others. As a support to the area of genomics and specifically to the field of genomics, we describe and propose a method based on mining software repositories (MSR), which monitors, evaluates and maps the genomic software hosted in the GitHub. We use the VigHub tool to extract meta-data from projects and create visualizations on technological maps. We present a detailed systematic review of the genomic software projects on GitHub, where the highlights of the genomics area are shown. Specifically we show the technological maps of the programming languages most used in the creation of software. The Time-line, where software projects are displayed by category, relevance and programming languages as a function of time. Classification of the repositories by software categories and the most successful genomic software repositories in GitHub according to stars and score. This paper is aimed at bioinformatics researchers that require relevant information about the current state of a specific genomic technology found in GitHub. The method facilitates the identification of ideas, source code, specific data, platforms, applications, scripts and tools that support research and innovation in genomic software projects. The analysis provided in this paper allowed to identify software trends in the area, as well as new perspectives and future technologies. |
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ISSN: | 2167-9843 |
DOI: | 10.7287/peerj.preprints.27352v3 |