A scalable HPC framework for bioinformatics in resource-limited settings: design principles, implementation, and sustainability from the UVRI experience

Authors

Alfred Ssekagiri (ORCID: https://orcid.org/0000-0002-6549-3550)
Sumir Panji (ORCID: https://orcid.org/0000-0003-0447-0598)
Mike Nsubuga (ORCID: https://orcid.org/0009-0004-7668-3917)
Edward Lukyamuzi (ORCID: https://orcid.org/0000-0001-5274-4624)
Grace Kebirungi (ORCID: https://orcid.org/0000-0002-9918-4617)
Suresh Maslamoney
Atwine Mugume
Jonathan Kayondo
Daudi Jjingo
Nicola J Mulder
Timothy Kimbowa Wamala
Ronald Galiwango

Institutions

University of Cape Town (ZA)
Open Data Institute (GB)
Makerere University (UG)
Uganda Virus Research Institute (UG)

Publication Details

Journal: Bioinformatics
Published: 2026-03-23
DOI: https://doi.org/10.1093/bioinformatics/btag149
Primary Topic: Genetics, Bioinformatics, and Biomedical Research
Type: article
Field-Weighted Citation Impact: 0.00

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article

A scalable HPC framework for bioinformatics in resource-limited settings: design principles, implementation, and sustainability from the UVRI experience

Alfred Ssekagiri, Sumir Panji, Mike Nsubuga, Edward Lukyamuzi et al.

Mar 23, 2026

Bioinformatics

Genetics, Bioinformatics, and Biomedical Research

article

A scalable HPC framework for bioinformatics in resource-limited settings: design principles, implementation, and sustainability from the UVRI experience

Alfred Ssekagiri, Sumir Panji, Mike Nsubuga, Edward Lukyamuzi, Grace Kebirungi, Suresh Maslamoney, Atwine Mugume, Jonathan Kayondo, Daudi Jjingo, Nicola J Mulder, Timothy Kimbowa Wamala, Ronald Galiwango

March 23, 2026article en

Abstract

No abstract available for this paper.

Bioinformatics

University of Cape Town (ZA), Open Data Institute (GB), Makerere University (UG), Uganda Virus Research Institute (UG)

Responsible consumption and production, Industry, innovation and infrastructure

Openalex Percentile: Top 7%

Genetics, Bioinformatics, and Biomedical Research

DOI Open Access PDF OpenAlex

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A scalable HPC framework for bioinformatics in resource-limited settings: design principles, implementation, and sustainability from the UVRI experience — Alfred Ssekagiri, Sumir Panji, et al. · Bioinformatics (2026) | TGRS Research Map | TGRS