Summary
Protein databases list interactions without showing how reliable each one is, treating a single unverified test the same as many confirmed studies. The authors created ProLiVis 2.0, a tool that scores how trustworthy each protein interaction is by considering factors like how many independent labs confirm it. It also improves how these networks are shown visually in web browsers and lets users regenerate exact figures. Their analysis revealed most protein interactions in a database for SARS-CoV-2 are reported only once, highlighting a big gap in replication that previous views missed.
What this means in practice
- •For bioinformatics tool developers: Integrate trust scoring in protein interaction visualizations to highlight evidence reliability from multiple independent labs.
- •For pharmaceutical data analysts: Filter protein interaction networks for drug target exploration by prioritizing interactions with stronger, independently confirmed evidence.
Tested on one dataset.
Authors
Melih Sözdinler, Yalçın Doksanbir, Gökhan Akpınar, Ege Aktan
Abstract
Protein-protein interaction databases record evidence without weighing it. In BioGRID, an interaction asserted once by a single high-throughput screen and one confirmed by twenty laboratories across a dozen assays are the same kind of row in the same file. Tools built on such databases inherit that flattening: they draw every reported interaction as an edge, and the resulting picture states that two proteins interact without stating how much anyone should believe it. We present ProLiVis 2.0, a rewrite of the literature-centric visualization system of arXiv:2111.12794. It contributes three things. First, a citation-trust model that scores each interaction from seven terms, including a term for the number of independent laboratories behind the supporting publications, obtained by clustering those publications over shared institutional affiliations; a plain count of publications cannot distinguish five confirmations from one group publishing five times. Second, a deterministic reformulation of the center layout, closed-form and $O(n \log n)$, which replaces the force-directed placement of the original and makes published figures regenerable from a session manifest. Third, an implementation that runs entirely in a web browser, with an embedded analytical database, requiring no installation and uploading no data. On BioGRID release 5.0.260 restricted to SARS-CoV-2, 24,344 of 34,540 reported interactions (70%) rest on a single publication, and raising the trust threshold to 0.2 leaves 11,320 of them. That the large majority of a curated interaction network is unreplicated is a fact no existing view of the database makes visible.