Using bioinformatics training to boost research capacities in resource-limited regions

Serghei Mangul; Lana Martin; Ben Langmead; Javier Sanchez Galan; Ian Toma; Pavel Pevzner; Eleazar Eskin

doi:10.7287/peerj.preprints.27415v1

Using bioinformatics training to boost research capacities in resource-limited regions

Serghei Mangul ¹, Lana Martin¹, Ben Langmead², Javier Sanchez Galan³, Ian Toma⁴, Pavel Pevzner⁵, Eleazar Eskin¹

1 University of California, Los Angeles, Los Angeles, CA, United States

2 The Johns Hopkins University, Baltimore, United States

3 Universidad Tecnológica de Panamá, Panama, Panama

4 George Washington University, DC, United States

5 University of California, San Diego, San Diego, United States

DOI: 10.7287/peerj.preprints.27415v1

Published: 2018-12-06
Accepted: 2018-12-06

Subject Areas: Bioinformatics, Computational Biology, Genomics, Science and Medical Education
Keywords: bioinformatics education, lower-income countries

Licence: This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ Preprints) and either DOI or URL of the article must be cited.

Cite this article: Mangul S, Martin L, Langmead B, Galan JS, Toma I, Pevzner P, Eskin E. 2018. Using bioinformatics training to boost research capacities in resource-limited regions. PeerJ Preprints 6:e27415v1 https://doi.org/10.7287/peerj.preprints.27415v1

Abstract

Bioinformatics algorithms are now crucial for processing high throughput “-omics” data and deriving meaningful interpretations in most biomedical and life science research domains. Bioinformatics-related training and research mostly take place in nations with higher income economies. Scientists in lower-income countries publish less frequently than scientists in higher-income countries. Major discoveries in bioinformatics do not require expensive laboratory equipment. We proposed a framework that would enable scientists in lower-income countries to re-analyze published “-omics” data given training, support, and access to standard computing hardware and cloud-based resources.