Evidence map›Paper›PMID 41091691›Full record

ArticlePLoS computational biology2025

Impact of the COVID-19 pandemic on computational biology early career researchers: A global retrospective study.

Pradeep Eranti, Megha Hegde, Syed Muktadir Al Sium, R Gonzalo Parra, Alastair M Kilpatrick, Sayane Shome, Farzana Rahman

Abstract read
In one paragraph

Article in PLoS computational biology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

7 authors.

Pradeep ErantiUniversité Paris Cité, Inserm, T3S, Paris, France.ORCID 0000-0002-3060-3967
Megha HegdeSchool of Computing and Mathematics, Faculty of Engineering, Computing, and the Environment, Kingston University London, London, United Kingdom.
Syed Muktadir Al SiumIndustrial Microbiology Research Division, BCSIR Chattogram Laboratories, Bangladesh Council of Scientific and Industrial Research (BCSIR), Chattogram, Bangladesh.ORCID 0000-0002-9497-5380
R Gonzalo ParraComputational Biology Group, Life Sciences Department, Barcelona Supercomputing Center, Barcelona, Spain.ORCID 0000-0003-2446-016X
Alastair M KilpatrickCentre for Regenerative Medicine, Institute for Regeneration and Repair, The University of Edinburgh, 4-5 Little France Drive, Edinburgh BioQuarter, Edinburgh, United Kingdom.ORCID 0000-0002-4795-8799
Sayane ShomeDepartment of Anesthesia, Perioperative, and Pain Medicine, Stanford University School of Medicine, Stanford, California, United States of America.
Farzana RahmanSchool of Computing and Mathematics, Faculty of Engineering, Computing, and the Environment, Kingston University London, London, United Kingdom.ORCID 0000-0002-4785-5845

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The COVID-19 pandemic led to devastating physical, psychological, and financial impacts on millions of people across the world. Amidst a rapidly evolving research landscape, the global scientific community was forced to swiftly adapt to novel working methods, including remote collaboration tools, virtual conferences, and online research platforms. Surveys of life sciences researchers have indicated that computational biologists experienced less disruption and a smoother transition to remote working than experimental biologists, due to their reduced reliance on laboratory equipment. Despite this adaptability, the sudden shift to remote work, compounded by stress and social isolation, has posed significant mental health challenges for these workers. However, remote work has also facilitated opportunities for more flexible work arrangements and increased collaboration across geographical boundaries. To investigate these impacts, we conducted surveys of computational biologists during the Intelligent Systems for Molecular Biology (ISMB) conferences in 2020 and 2021, which were held virtually due to the COVID-19 lockdowns. This study implements a thorough statistical analysis of the survey results to offer insights into the repercussions of the lockdowns on researchers and their work. Key areas of investigation include the effects of institutional support (or lack thereof), the difference in productivity compared to pre-lockdown levels, and the significance of gender in determining these impacts. Notably, a lack of institutional support with regard to mental health and finances was shown to have a significant negative effect on early-career researchers. Although limited by a small sample size, our study sets the stage for a more robust exploration of these trends in future research. Importantly, by illuminating the challenges and opportunities arising from the COVID-19 pandemic and lockdowns, our study offers hope for potential solutions supporting the well-being of early-career researchers in unprecedented circumstances.

Indexed as

Computational BiologyCOVID-19Research PersonnelFemaleHumansMalePandemicsRetrospective StudiesSARS-CoV-2Surveys and QuestionnairesTeleworking

Identifiers

PMID41091691
PMCPMC12527158

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.