Evidence map›Paper›PMID 34591953›Full record

ArticleBriefings in bioinformatics2022

Bioinformatics mentorship in a resource limited setting.

Daudi Jjingo, Gerald Mboowa, Ivan Sserwadda, Robert Kakaire, Davis Kiberu, Marion Amujal, Ronald Galiwango, David Kateete, Moses Joloba, Christopher C Whalen

Abstract read
In one paragraph

Article in Briefings in bioinformatics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

13 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Daudi JjingoThe African Center of Excellence in Bioinformatics and Data Intensive Sciences, the Infectious Diseases Institute, Makerere University, Kampala-Uganda.ORCID 0000-0003-1685-9234
Gerald MboowaThe African Center of Excellence in Bioinformatics and Data Intensive Sciences, the Infectious Diseases Institute, Makerere University, Kampala-Uganda.ORCID 0000-0001-8445-9414
Ivan SserwaddaThe African Center of Excellence in Bioinformatics and Data Intensive Sciences, the Infectious Diseases Institute, Makerere University, Kampala-Uganda.
Robert KakaireDepartment of Epidemiology and Biostatistics, College of Public Health, University of Georgia, Athens, GA, USA.
Davis KiberuThe African Center of Excellence in Bioinformatics and Data Intensive Sciences, the Infectious Diseases Institute, Makerere University, Kampala-Uganda.
Marion AmujalDepartment of Immunology and Molecular Biology, College of Health Sciences, Makerere University, Kampala-Uganda.
Ronald GaliwangoThe African Center of Excellence in Bioinformatics and Data Intensive Sciences, the Infectious Diseases Institute, Makerere University, Kampala-Uganda.
David KateeteDepartment of Immunology and Molecular Biology, College of Health Sciences, Makerere University, Kampala-Uganda.
Moses JolobaDepartment of Immunology and Molecular Biology, College of Health Sciences, Makerere University, Kampala-Uganda.
Christopher C WhalenDepartment of Epidemiology and Biostatistics, College of Public Health, University of Georgia, Athens, GA, USA.

Funding

Emory/Georgia TB Research Advancement Center (TRAC)P30AI168386 · NIAID · EMORY UNIVERSITY · PI Neel Rajnikant Gandhi, Jyothi Rengarajan · 2022 to 2026
$5.8M
Computational and Molecular Epidemiology Training in TB and HIV in UgandaD43TW010045 · FIC · UNIVERSITY OF GEORGIA · PI WHALEN, CHRISTOPHER C. · 2015 to 2019
$1.5M
NURTURING GENOMICS AND BIOINFORMATICS RESEARCH CAPACITY IN AFRICA (BRecA)U2RTW010672 · FIC · MAKERERE UNIVERSITY COLLEGE OF HEALTH SCIENCES · PI JJINGO, DAUDI, KATEETE, DAVID PATRICK · 2017 to 2022
$1.3M
FIC NIH HHS D43 TW010045FIC NIH HHS U2R TW010672NIAID NIH HHS P30 AI168386NIH HHS 1D43TW010045-01
6 · The paper itself

Abstract

backgroundThe two recent simultaneous developments of high-throughput sequencing and increased computational power have brought bioinformatics to the forefront as an important tool for effective and efficient biomedical research. Consequently, there have been multiple approaches to developing bioinformatics skills. In resource rich environments, it has been possible to develop and implement formal fully accredited graduate degree training programs in bioinformatics. In resource limited settings with a paucity of expert bioinformaticians, infrastructure and financial resources, the task has been approached by delivering short courses on bioinformatics-lasting only a few days to a couple of weeks. Alternatively, courses are offered online, usually over a period of a few months. These approaches are limited by both the lack of sustained in-person trainer-trainee interactions, which is a key part of quality mentorships and short durations which constrain the amount of learning that can be achieved.

methodsHere, we pioneered and tested a bioinformatics training/mentorship model that effectively uses the available expertise and computational infrastructure to deliver an in-person hands-on skills training experience. This is done through a few physical lecture hours each week, guided personal coursework over the rest of the week, group discussions and continuous close mentorship and assessment of trainees over a period of 1 year.

resultsThis model has now completed its third iteration at Makerere University and has successfully mentored trainees, who have progressed to a variety of viable career paths.

conclusionsOne-year (intermediate) skills based in-person bioinformatics training and mentorships are viable, effective and particularly appropriate for resource limited settings.

Indexed as

Biomedical ResearchMentorsComputational BiologyHigh-Throughput Nucleotide SequencingHumansUniversitiesbioinformaticscomputational biologyeducationintermediatementorshiptraining

Identifiers

PMID34591953
PMCPMC8769693

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.