Overcoming research bias: The untapped potential of biomedically important but understudied proteins

Researchers have concentrated much of their attention on a limited number of disease-associated proteins to develop life-changing therapeutics. However, this research bias overlooks many important therapeutic targets yet to be explored. In this work, we quantitatively assess the magnitude of this bias and describe a new approach that aggregates data from several databases to inspire the investigation of understudied but biomedically important proteins. Our method combines literature analysis, protein interaction data, and diverse sources of clinical, genetic, and molecular information to evaluate both how well a protein has been studied and its potential biomedical importance. Together, these data can be explored through either a user-friendly script or website to discover understudied, but biomedically important targets for investigation and drug discovery.

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Publication Details

Journal
iScience
Published
2025-08-15
DOI
https://doi.org/10.1016/j.isci.2025.113210
Primary Topic
vaccines and immunoinformatics approaches
Type
article
Field-Weighted Citation Impact
0.00

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article

Overcoming research bias: The untapped potential of biomedically important but understudied proteins

Carlos Madrid-Aliste, András Fiser, Steven Grudman
iScience
vaccines and immunoinformatics approaches
article

Overcoming research bias: The untapped potential of biomedically important but understudied proteins

Carlos Madrid-Aliste, András Fiser, Steven Grudman
article en

Abstract

Researchers have concentrated much of their attention on a limited number of disease-associated proteins to develop life-changing therapeutics. However, this research bias overlooks many important therapeutic targets yet to be explored. In this work, we quantitatively assess the magnitude of this bias and describe a new approach that aggregates data from several databases to inspire the investigation of understudied but biomedically important proteins. Our method combines literature analysis, protein interaction data, and diverse sources of clinical, genetic, and molecular information to evaluate both how well a protein has been studied and its potential biomedical importance. Together, these data can be explored through either a user-friendly script or website to discover understudied, but biomedically important targets for investigation and drug discovery.

iScienceVol. 28(9)
Albert Einstein College of Medicine (US)
National Institutes of Health
Openalex Percentile: Top 81%
vaccines and immunoinformatics approaches
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