Work

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

Year: 2018

Type: preprint

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.

DOI: 10.7287/peerj.preprints.27415v1

Authors: Serghei Mangul, Lana Martin, Ben Langmead, Javier Sanchez Galan, Ian Toma, Pavel Pevzner, Eleazar Eskin

Institutions: University of California, Los Angeles, Johns Hopkins University, Universidad Tecnológica de Panamá, George Washington University, University of California San Diego

Language: English

Topic: Genetics, Bioinformatics, and Biomedical Research

Subfield: Molecular Biology

Field: Biochemistry, Genetics and Molecular Biology

Domain: Life Sciences

SDGs: Reduced inequalities, Partnerships for the goals

Open Access status: gold

OpenAlex ID: W2921650865

Cites:

Cited by: 1

Related to: 10