Evidence map›Paper›PMID 39172543›Full record

ArticleGigaScience2024

Design and implementation of a scalable high-performance computing (HPC) cluster for omics data analysis: achievements, challenges and recommendations in LMICs.

Kais Ghedira, Oussema Khamessi, Chaima Hkimi, Selim Kamoun, Nader Dhamer, Kamel Daassi, Wassim Ben Salah, Houcemeddine Othman, Wahbi Belhadj, Youssef Ghorbal

Abstract read
In one paragraph

Article in GigaScience, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Strain-level analyses of public sequencing data to characterizeOne health (Amsterdam, Netherlands) · 2026
    Article
  2. Cancers · 2026
    Article
  3. Article
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.

Kais GhediraLaboratory of Bioinformatics, Biomathematics and Biostatistics, LR16IPT09, Institut Pasteur de Tunis, University of Tunis El Manar, Tunis 1002, Tunisia.ORCID 0000-0002-3387-6493
Oussema KhamessiLaboratory of Bioinformatics, Biomathematics and Biostatistics, LR16IPT09, Institut Pasteur de Tunis, University of Tunis El Manar, Tunis 1002, Tunisia.ORCID 0000-0002-3617-5705
Chaima HkimiLaboratory of Bioinformatics, Biomathematics and Biostatistics, LR16IPT09, Institut Pasteur de Tunis, University of Tunis El Manar, Tunis 1002, Tunisia.ORCID 0000-0002-9167-2480
Selim KamounLaboratory of Bioinformatics, Biomathematics and Biostatistics, LR16IPT09, Institut Pasteur de Tunis, University of Tunis El Manar, Tunis 1002, Tunisia.ORCID 0000-0001-5891-3206
Nader DhamerLaboratory of Bioinformatics, Biomathematics and Biostatistics, LR16IPT09, Institut Pasteur de Tunis, University of Tunis El Manar, Tunis 1002, Tunisia.ORCID 0009-0000-0351-403X
Kamel DaassiDirection Informatique de l'Institut Pasteur de Tunis, Institut Pasteur de Tunis, University of Tunis El Manar, Tunis 1002, Tunisia.
Wassim Ben SalahDirection Informatique de l'Institut Pasteur de Tunis, Institut Pasteur de Tunis, University of Tunis El Manar, Tunis 1002, Tunisia.
Houcemeddine OthmanSydney Brenner Institute for Molecular Bioscience, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg 2193, South Africa.ORCID 0000-0002-1159-6482
Wahbi BelhadjThe European Bioinformatics Institute-European Bioinformatics Institute (EMBL-EBI), Hinxton CB10 1SD, United Kingdom.ORCID 0000-0003-2672-7075
Youssef GhorbalHPC Core Facility of the Institut Pasteur Paris, 25-28 Rue du Dr Roux, 75015 Paris, France.ORCID 0009-0004-0232-4196

Funding

Tunisian Ministry of Higher Education and Scientific Research
6 · The paper itself

Abstract

backgroundThe advent of high-throughput technologies, including cutting-edge sequencing devices, has revolutionized biomedical data generation and processing. Nevertheless, big data applications require novel hardware and software for parallel computing and management to handle the ever-growing data size and analysis complexity. On-premise, high-performance computing (HPC) is increasingly used in biomedical research for big data stewardship.

findingsIn this work, we present Tunisia's first high-performance computational infrastructure for omics research.

methodWe highlight measurements and recommendations that may help institutions in other low- and middle-income countries that are eager to implement local HPC in facilities for bioinformatics research and omics data analyses.

Indexed as

Computational BiologySoftwareBig DataData AnalysisDeveloping CountriesGenomicsHumansbioinformaticscomputational powercomputing clusterHPCinfrastructureTunisia

Identifiers

PMID39172543
PMCPMC11340639

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.