On biases of attention in scientific discovery

ABSTRACT Summary How do nuances of scientists’ attention influence what they discover? We pursue an understanding of the influences of patterns of attention on discovery with a case study about confirmations of protein–protein interactions over time. We find that modeling and accounting for attentio...

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Bibliographic Details
Published in:Bioinformatics (Oxford, England) England), 2021-04, Vol.36 (22-23), p.5269-5274
Main Authors: Singer, Uriel, Radinsky, Kira, Horvitz, Eric
Format: Article
Language:English
Subjects:
Attention
Availability
Bias
Missing data
Pattern recognition
Protein interaction
Proteins
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Summary:ABSTRACT Summary How do nuances of scientists’ attention influence what they discover? We pursue an understanding of the influences of patterns of attention on discovery with a case study about confirmations of protein–protein interactions over time. We find that modeling and accounting for attention can help us to recognize and interpret biases in large-scale and widely used databases of confirmed interactions and to better understand missing data and unknowns. Additionally, we present an analysis of how awareness of patterns of attention and use of debiasing techniques can foster earlier discoveries. Availability and implementation The data is freely available at https://github.com/urielsinger/PPI-unbias.
ISSN:1367-4803
1367-4811
DOI:10.1093/bioinformatics/btaa1036