Regularly updated benchmark sets for statistically correct evaluations of AlphaFold applications

AlphaFold2 changed structural biology by providing high-quality structure predictions for all possible proteins. Since its inception, a plethora of applications were built on AlphaFold2, expediting discoveries in virtually all areas related to protein science. In many cases, however, optimism seems to have made scientists forget about data leakage, a serious issue that needs to be addressed when evaluating machine learning methods. Here we provide a rigorous benchmark set that can be used in a broad range of applications built around AlphaFold2/3.

Authors

Institutions

Publication Details

Journal
Briefings in Bioinformatics
Published
2025-02-27
DOI
https://doi.org/10.1093/bib/bbaf104
Citations
4
Primary Topic
Machine Learning in Bioinformatics
Type
article
Field-Weighted Citation Impact
3.22

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Regularly updated benchmark sets for statistically correct evaluations of AlphaFold applications

Péter Tompa, Gábor Tusnády, László Dobson
4 citations
Briefings in Bioinformatics
Machine Learning in Bioinformatics
3.22
article

Regularly updated benchmark sets for statistically correct evaluations of AlphaFold applications

Péter Tompa, Gábor Tusnády, László Dobson
article en
4 citations

Abstract

AlphaFold2 changed structural biology by providing high-quality structure predictions for all possible proteins. Since its inception, a plethora of applications were built on AlphaFold2, expediting discoveries in virtually all areas related to protein science. In many cases, however, optimism seems to have made scientists forget about data leakage, a serious issue that needs to be addressed when evaluating machine learning methods. Here we provide a rigorous benchmark set that can be used in a broad range of applications built around AlphaFold2/3.

Briefings in BioinformaticsVol. 26(2)
Semmelweis University (HU), Vlaams Instituut voor Biotechnologie (BE), National Institute of Oncology (HU), VIB-VUB Center for Structural Biology (BE), HUN-REN Research Centre for Natural Sciences (HU)
Nemzeti Kutatási Fejlesztési és Innovációs Hivatal
Openalex Percentile: Top 9%
Machine Learning in Bioinformatics
3.22
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.