Evidence map›Paper›PMID 29023441›Full record

ArticlePLoS computational biology2017

Women are underrepresented in computational biology: An analysis of the scholarly literature in biology, computer science and computational biology.

Kevin S Bonham, Melanie I Stefan

Abstract read
In one paragraph

Article in PLoS computational biology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers.

0numbers the graph read from it
0cells of the map it votes in
31citing 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

31 citing papers in PubMed.

  1. Article
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  5. A critical analysis of plant science literature reveals ongoing inequities.Proceedings of the National Academy of Sciences of the United States of America · 2023
    Article
  6. Article
  7. Editorial: Women in plant biotechnology 2022.Frontiers in plant science · 2023
    Article
  8. Article
  9. Article
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  11. Article
  12. Engagement patterns with female and male scientists on Facebook.Public understanding of science (Bristol, England) · 2022
    Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
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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

2 authors.

Kevin S BonhamMicrobiology and Immunobiology, Harvard Medical School, Boston, Massachusetts, United States of America.ORCID http://orcid.org/0000-0003-3200-7533
Melanie I StefanCentre for Integrative Physiology, Edinburgh Medical School, Biomedical Sciences, University of Edinburgh, Edinburgh, United Kingdom.ORCID http://orcid.org/0000-0002-6086-7357

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

While women are generally underrepresented in STEM fields, there are noticeable differences between fields. For instance, the gender ratio in biology is more balanced than in computer science. We were interested in how this difference is reflected in the interdisciplinary field of computational/quantitative biology. To this end, we examined the proportion of female authors in publications from the PubMed and arXiv databases. There are fewer female authors on research papers in computational biology, as compared to biology in general. This is true across authorship position, year, and journal impact factor. A comparison with arXiv shows that quantitative biology papers have a higher ratio of female authors than computer science papers, placing computational biology in between its two parent fields in terms of gender representation. Both in biology and in computational biology, a female last author increases the probability of other authors on the paper being female, pointing to a potential role of female PIs in influencing the gender balance.

Indexed as

AuthorshipBiologyComputational BiologyInformation ScienceCareer ChoiceFemaleHumansPublicationsSex DistributionWomen

Identifiers

PMID29023441
PMCPMC5638210

What OpenQuestion holds

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LicenceCC BY
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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.