Martin Steinegger

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Milot MirditaSeoul National UniversityAdresse e-mail validée de snu.ac.kr
Johannes SödingMax-Planck-Institute for Multidisciplinary Sciences, GöttingenAdresse e-mail validée de mpinat.mpg.de
Burkhard RostProfessor of Computer Science, Technical University MunichAdresse e-mail validée de tum.de
Sergey OvchinnikovMITAdresse e-mail validée de mit.edu
Michael HeinzingerTechnische Universität MünchenAdresse e-mail validée de tum.de
Christian DallagoNVIDIA & Technische Universität MünchenAdresse e-mail validée de tum.de
Ahmed ElnaggarTechnical University of MunichAdresse e-mail validée de tum.de
Steven SalzbergBloomberg Distinguished Professor, Johns Hopkins UniversityAdresse e-mail validée de jhu.edu
Debsindhu BhowmikComputational Scientist, Oak Ridge National LaboratoryAdresse e-mail validée de ornl.gov
Antonio Fernàndez-GuerraCentre for Ancient Environmental GenomicsAdresse e-mail validée de sund.ku.dk
Clovis GaliezGrenoble-Alpes University, Grenoble INP, LJKAdresse e-mail validée de grenoble-inp.fr
Tom O. DelmontCNRS - Genoscope - TARA anvi-OceansAdresse e-mail validée de genoscope.cns.fr
Prof. Dr. Frank Oliver GlöcknerAlfred Wegener Institute Bremerhaven, MARUM, University of BremenAdresse e-mail validée de awi.de
Maria J. MartinEuropean Bioinformatics InstituteAdresse e-mail validée de ebi.ac.uk
Vikram AlvaGroup Leader, Max Planck Institute for BiologyAdresse e-mail validée de tuebingen.mpg.de
Andrei LupasDirector of the Department of Protein Evolution, Max-Planck-Institute for BiologyAdresse e-mail validée de tuebingen.mpg.de
John JumperDeepMindAdresse e-mail validée de google.com
Christof AngermuellerGoogleAdresse e-mail validée de google.com
koray kavukcuogluDeepMindAdresse e-mail validée de kavukcuoglu.org
Demis HassabisDeepMind

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Martin Steinegger

Associate Professor, Seoul National University, Korea

Adresse e-mail validée de snu.ac.kr - Page d'accueil

Bioinformatics Computational Biology


Titre Trier par citations Trier par année Trier par titre	Citée par Citée par	Année
Highly accurate protein structure prediction with AlphaFold J Jumper, R Evans, A Pritzel, T Green, M Figurnov, O Ronneberger, ... Nature, 2021	32069	2021
ColabFold: making protein folding accessible to all M Mirdita, K Schütze, Y Moriwaki, L Heo, S Ovchinnikov, M Steinegger Nature Methods, 679–682, 2022	6369	2022
MMseqs2 enables sensitive protein sequence searching for the analysis of massive data sets M Steinegger, J Söding Nature biotechnology 35 (11), 1026-1028, 2017	2901	2017
ProtTrans: Towards Cracking the Language of Lifes Code Through Self-Supervised Deep Learning and High Performance Computing A Elnaggar, M Heinzinger, C Dallago, G Rehawi, Y Wang, L Jones, ... IEEE Transactions on Pattern Analysis and Machine Intelligence 14 (8), 2021	1777*	2021
Fast and accurate protein structure search with Foldseek M van Kempen, SS Kim, C Tumescheit, M Mirdita, J Lee, CLM Gilchrist, ... Nature Biotechnology 42, 243–246, 2023	1160*	2023
HH-suite3 for fast remote homology detection and deep protein annotation M Steinegger, M Meier, M Mirdita, H Vöhringer, SJ Haunsberger, J Söding BMC Bioinformatics 20, 2019	994	2019
Clustering huge protein sequence sets in linear time M Steinegger, J Söding Nature communications 9 (1), 2542, 2018	775	2018
Uniclust databases of clustered and deeply annotated protein sequences and alignments M Mirdita, L von den Driesch, C Galiez, MJ Martin, J Söding, M Steinegger Nucleic Acids Research, 2016	674	2016
Protein sequence analysis using the MPI bioinformatics toolkit F Gabler, SZ Nam, S Till, M Mirdita, M Steinegger, J Söding, AN Lupas, ... Current Protocols in Bioinformatics 72 (1), e108, 2020	645	2020
AlphaFold Protein Structure Database in 2024: providing structure coverage for over 214 million protein sequences M Varadi, D Bertoni, P Magana, U Paramval, I Pidruchna, ... Nucleic Acids Research, 2023	477	2023
MMseqs2 desktop and local web server app for fast, interactive sequence searches M Mirdita, M Steinegger, J Söding Bioinformatics 35 (16), 2856–2858, 2019	464	2019
Protein-level assembly increases protein sequence recovery from metagenomic samples manyfold M Steinegger, M Mirdita, J Söding Nature Methods 16, 603–606, 2019	409	2019
Applying and improving AlphaFold at CASP14 J Jumper, R Evans, A Pritzel, T Green, M Figurnov, O Ronneberger, ... Proteins: Structure, Function, and Bioinformatics 89 (12), 1711-1721, 2021	360	2021
Metagenome analysis using the Kraken software suite J Lu, N Rincon, DE Wood, FP Breitwieser, C Pockrandt, B Langmead, ... Nature Protocols, 2022	325	2022
High accuracy protein structure prediction using deep learning J Jumper, R Evans, A Pritzel, T Green, M Figurnov, K Tunyasuvunakool, ... Fourteenth critical assessment of techniques for protein structure …, 2020	240*	2020
PredictProtein - Predicting Protein Structure and Function for 29 Years M Bernhofer, C Dallago, T Karl, V Satagopam, M Heinzinger, M Littmann, ... Nucleic Acids Research, 2021	229	2021
MMseqs software suite for fast and deep clustering and searching of large protein sequence sets M Hauser, M Steinegger, J Söding Bioinformatics 32 (9), 1323-1330, 2016	223	2016
Terminating contamination: large-scale search identifies more than 2,000,000 contaminated entries in GenBank M Steinegger, SL Salzberg Genome Biology 21, 2020	194	2020
Fast and sensitive taxonomic assignment to metagenomic contigs M Mirdita, M Steinegger, F Breitwieser, J Söding, E Levy Karin Bioinformatics, 2021	188	2021
Clustering predicted structures at the scale of the known protein universe I Barrio-Hernandez, J Yeo, J Jänes, M Mirdita, CLM Gilchrist, T Wein, ... Nature, 2023	178	2023

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