Leaderboards/Machine Learning in Bioinformatics

Machine Learning in Bioinformatics

Last updated July 15, 2026

Rising Stars

Fresh ink, massive impact

Researchers

1
Benjamin Buchfink
Max Planck Institute for Biology
2
Typhaine Paysan‐Lafosse
European Bioinformatics Institute
3
Matthias Blum
European Bioinformatics Institute
4
Lars Gabriel
Universitätsmedizin Greifswald
5
Tomer Tsaban
Hebrew University of Jerusalem
6
Hugo Dalla-Torre
Institut Supérieur d'Électronique de Paris
7
Vineet Thumuluri
University of California San Diego
8
Gustaf Ahdritz
Columbia University
9
Diego del Alamo
PDL BioPharma (United States)
10
Devlina Chakravarty
National Institutes of Health

Papers

1
InterPro: the protein sequence classification resource in 2025
Nucleic Acids Research|2024
885 cit.
2
BRAKER3: Fully automated genome annotation using RNA-seq and protein evidence with GeneMark-ETP, AUGUSTUS, and TSEBRA
Genome Research|2024
556 cit.
3
Nucleotide Transformer: building and evaluating robust foundation models for human genomics
Nature Methods|2024
380 cit.
4
OpenFold: retraining AlphaFold2 yields new insights into its learning mechanisms and capacity for generalization
Nature Methods|2024
289 cit.
5
The Pfam protein families database: embracing AI/ML
Nucleic Acids Research|2024
267 cit.
6
AlphaFold predictions of fold-switched conformations are driven by structure memorization
Nature Communications|2024
142 cit.
7
Tiberius: end-to-end deep learning with an HMM for gene prediction
Bioinformatics|2024
36 cit.
8
BPS2026 – Conserved patterns vs. rational design: Fold-switching pathways in a phage tail protein
Biophysical Journal|2026
0 cit.
9
Accurate <i>ab initio</i> gene prediction in eukaryotes with Tiberius in multiple clades
bioRxiv (Cold Spring Harbor Laboratory)|2026
0 cit.
10
InterProScan 6: a modern large-scale protein function annotation pipeline
Bioinformatics Advances|2026
0 cit.

Emerging Leaders

Drafting the new consensus

Researchers

1
Martin Steinegger
Institute of Molecular Biology
2
Sergey Ovchinnikov
Massachusetts Institute of Technology
3
Jian Zhang
Shandong Agricultural University
4
Douglas Teodoro
University of Geneva
5
Brian Hie
Palo Alto Institute
6
Hajk‐Georg Drost
Max Planck Institute for Biology
7
Alexander Rives
New York Consortium in Evolutionary Primatology
8
Halil Akin
Lokman Hekim Üniversitesi
9
Roshan Rao
Chan Zuckerberg Biohub San Francisco
10
Watshara Shoombuatong
Mahidol University

Papers

1
ColabFold: making protein folding accessible to all
Nature Methods|2022
9.7k cit.
2
UniProt: the Universal Protein Knowledgebase in 2023
Nucleic Acids Research|2022
7k cit.
3
Evolutionary-scale prediction of atomic-level protein structure with a language model
Science|2023
4.9k cit.
4
Fast and accurate protein structure search with Foldseek
Nature Biotechnology|2023
2.4k cit.
5
Simulating 500 million years of evolution with a language model
Science|2025
603 cit.
6
Efficient evolution of human antibodies from general protein language models
Nature Biotechnology|2023
450 cit.
7
Sequence modeling and design from molecular to genome scale with Evo
Science|2024
427 cit.
8
Clustering predicted structures at the scale of the known protein universe
Nature|2023
365 cit.
9
State-of-the-Art Estimation of Protein Model Accuracy Using AlphaFold
Physical Review Letters|2022
267 cit.
10
Evolutionary velocity with protein language models predicts evolutionary dynamics of diverse proteins
Cell Systems|2022
159 cit.

Current Senior Leaders

Wrote the book, still writing it

Researchers

1
Toby J. Gibson
European Molecular Biology Laboratory
2
Demis Hassabis
Google DeepMind (United Kingdom)
3
Qing‐Yu He
Jinan University
4
Kuo‐Chen Chou
The Gordon Life Science Institute
5
Erik L. L. Sonnhammer
Science for Life Laboratory
6
Gunnar von Heijne
Stockholm University
7
Søren Brunak
University of Copenhagen
8
Matthias Mann
Max Planck Institute of Biochemistry
9
Daniel H. Huson
University of Tübingen
10
Adam Godzik
University of California, Riverside

Papers

1
CLUSTAL W: improving the sensitivity of progressive multiple sequence alignment through sequence weighting, position-specific gap penalties and weight matrix choice
Nucleic Acids Research|1994
64.9k cit.
2
Highly accurate protein structure prediction with AlphaFold
Nature|2021
45.2k cit.
3
clusterProfiler: an R Package for Comparing Biological Themes Among Gene Clusters
OMICS A Journal of Integrative Biology|2012
38.3k cit.
4
Human-level control through deep reinforcement learning
Nature|2015
30k cit.
5
Mastering the game of Go with deep neural networks and tree search
Nature|2016
15.8k cit.
6
MaxQuant enables high peptide identification rates, individualized p.p.b.-range mass accuracies and proteome-wide protein quantification
Nature Biotechnology|2008
15.7k cit.
7
Fast and sensitive protein alignment using DIAMOND
Nature Methods|2014
15.2k cit.
8
Predicting transmembrane protein topology with a hidden markov model: application to complete genomes11Edited by F. Cohen
Journal of Molecular Biology|2001
13k cit.
9
Cd-hit: a fast program for clustering and comparing large sets of protein or nucleotide sequences
Bioinformatics|2006
12.1k cit.
10
Mastering the game of Go without human knowledge
Nature|2017
9.2k cit.

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