Martin Steinegger is an Assistant Professor of Bioinformatics at the Seoul National University. He received his Ph.D. from the Technical University Munich in collaboration with Dr. Johannes Söding at the Max Planck Institute for Biophysical Chemistry.
Steinegger's research focuses on leveraging big data and machine learning algorithms to develop computational methods for analysing complex genomic and proteomic data. He is an expert in large-scale sequence data analysis and method development, with a particular interest in metagenomics, protein structure prediction, and pathogen detection.
Martin Steinegger Associate Professor, Seoul National University, Korea http://steineggerlab.com/ Highly accurate protein structure prediction with AlphaFold J Jumper, R Evans, A Pritzel, T Green, M Figurnov, O Ronneberger, … Nature, 2021 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=D9XIZUAAAAJ&citationforview=D9XIZUAAAAJ:TQgYirikUcIC Cited by: 24355
ColabFold: making protein folding accessible to all M Mirdita, K Schütze, Y Moriwaki, L Heo, S Ovchinnikov, M Steinegger Nature Methods, 679–682, 2022 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=D9XIZUAAAAJ&citationforview=D9XIZUAAAAJ:RGFaLdJalmkC Cited by: 4585
MMseqs2 enables sensitive protein sequence searching for the analysis of massive data sets M Steinegger, J Söding Nature biotechnology 35 (11), 1026-1028, 2017 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=D9XIZUAAAAJ&citationforview=D9XIZUAAAAJ:YsMSGLbcyi4C Cited by: 2178
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 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=D9XIZUAAAAJ&citationforview=D9XIZUAAAAJ:R3hNpaxXUhUC Cited by: 1240
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 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=D9XIZUAAAAJ&citationforview=D9XIZUAAAAJ:5nxA0vEk-isC Cited by: 844
Clustering huge protein sequence sets in linear time M Steinegger, J Söding Nature communications 9 (1), 2542, 2018 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=D9XIZUAAAAJ&citationforview=D9XIZUAAAAJ:WF5omc3nYNoC Cited by: 659
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 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=D9XIZUAAAAJ&citationforview=D9XIZUAAAAJ:_xSYboBqXhAC Cited by: 633
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 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=D9XIZUAAAAJ&citationforview=D9XIZUAAAAJ:2osOgNQ5qMEC Cited by: 588
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 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=D9XIZUAAAAJ&citationforview=D9XIZUAAAAJ:4DMP91E08xMC Cited by: 533
MMseqs2 desktop and local web server app for fast, interactive sequence searches M Mirdita, M Steinegger, J Söding Bioinformatics 35 (16), 2856–2858, 2019 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=D9XIZUAAAAJ&citationforview=D9XIZUAAAAJ:roLk4NBRz8UC Cited by: 355
Protein-level assembly increases protein sequence recovery from metagenomic samples manyfold M Steinegger, M Mirdita, J Söding Nature Methods 16, 603–606, 2019 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=D9XIZUAAAAJ&citationforview=D9XIZUAAAAJ:UebtZRa9Y70C Cited by: 330
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 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=D9XIZUAAAAJ&citationforview=D9XIZUAAAAJ:TFP_iSt0sucC Cited by: 290
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 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=D9XIZUAAAAJ&citationforview=D9XIZUAAAAJ:HDshCWvjkbEC Cited by: 225
Metagenome analysis using the Kraken software suite J Lu, N Rincon, DE Wood, FP Breitwieser, C Pockrandt, B Langmead, … Nature Protocols, 2022 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=D9XIZUAAAAJ&citationforview=D9XIZUAAAAJ:M05iB0D1s5AC Cited by: 203
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 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=D9XIZUAAAAJ&citationforview=D9XIZUAAAAJ:hC7cP41nSMkC Cited by: 184
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 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=D9XIZUAAAAJ&citationforview=D9XIZUAAAAJ:d1gkVwhDpl0C Cited by: 179
Terminating contamination: large-scale search identifies more than 2,000,000 contaminated entries in GenBank M Steinegger, SL Salzberg Genome Biology 21, 2020 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=D9XIZUAAAAJ&citationforview=D9XIZUAAAAJ:KlAtU1dfN6UC Cited by: 165
Fast and sensitive taxonomic assignment to metagenomic contigs M Mirdita, M Steinegger, F Breitwieser, J Söding, E Levy Karin Bioinformatics, 2021 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=D9XIZUAAAAJ&citationforview=D9XIZUAAAAJ:ZeXyd9-uunAC Cited by: 139
ProtTrans: Towards cracking the language of Life’s code through self-supervised deep learning and high performance computing. arXiv 2020 A Elnaggar, M Heinzinger, C Dallago, G Rihawi, Y Wang, L Jones, … arXiv preprint arXiv:2007.06225, 2020 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=D9XIZUAAAAJ&citationforview=D9XIZUAAAAJ:b0M2c_1WBrUC Cited by: 97
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 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=D9XIZUAAAAJ&citationforview=D9XIZUAAAAJ:UxriW0iASnsC Cited by: 95
Milot Mirdita jaTEO_QAAAAJ
Johannes Söding xjYIe80AAAAJ
Burkhard Rost BP3ofxcAAAAJ
Michael Heinzinger yXtPl58AAAAJ
Sergey Ovchinnikov 8KJ9gf4AAAAJ
Christian Dallago 4q0fNGAAAAAJ
Steven Salzberg sUVeH-4AAAAJ
Ahmed Elnaggar fadCsRsAAAAJ
Debsindhu Bhowmik nHwDs_sAAAAJ
Clovis Galiez vmTnjSYAAAAJ
Antonio Fernàndez-Guerra wA7Hrk8AAAAJ
Tom O. Delmont _uZfiVUAAAAJ
Prof. Dr. Frank Oliver Glöckner BmzoT3QAAAAJ
Maria J. Martin kYxN8kQAAAAJ
Vikram Alva nY7NEcYAAAAJ
Andrei Lupas FwQEo_8AAAAJ
John Jumper a5goOh8AAAAJ
Christof Angermueller OXZC0mQAAAAJ
Demis Hassabis dYpPMQEAAAAJ
David Silver -8DNE4UAAAAJ
Martin Steinegger Associate Professor, Seoul National University, Korea http://steineggerlab.com/ Highly accurate protein structure prediction with AlphaFold J Jumper, R Evans, A Pritzel, T Green, M Figurnov, O Ronneberger, … Nature, 2021 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=D9XIZUAAAAJ&citationforview=D9XIZUAAAAJ:TQgYirikUcIC Cited by: 24355
ColabFold: making protein folding accessible to all M Mirdita, K Schütze, Y Moriwaki, L Heo, S Ovchinnikov, M Steinegger Nature Methods, 679–682, 2022 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=D9XIZUAAAAJ&citationforview=D9XIZUAAAAJ:RGFaLdJalmkC Cited by: 4585
MMseqs2 enables sensitive protein sequence searching for the analysis of massive data sets M Steinegger, J Söding Nature biotechnology 35 (11), 1026-1028, 2017 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=D9XIZUAAAAJ&citationforview=D9XIZUAAAAJ:YsMSGLbcyi4C Cited by: 2178
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 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=D9XIZUAAAAJ&citationforview=D9XIZUAAAAJ:R3hNpaxXUhUC Cited by: 1240
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 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=D9XIZUAAAAJ&citationforview=D9XIZUAAAAJ:5nxA0vEk-isC Cited by: 844
Clustering huge protein sequence sets in linear time M Steinegger, J Söding Nature communications 9 (1), 2542, 2018 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=D9XIZUAAAAJ&citationforview=D9XIZUAAAAJ:WF5omc3nYNoC Cited by: 659
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 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=D9XIZUAAAAJ&citationforview=D9XIZUAAAAJ:_xSYboBqXhAC Cited by: 633
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 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=D9XIZUAAAAJ&citationforview=D9XIZUAAAAJ:2osOgNQ5qMEC Cited by: 588
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 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=D9XIZUAAAAJ&citationforview=D9XIZUAAAAJ:4DMP91E08xMC Cited by: 533
MMseqs2 desktop and local web server app for fast, interactive sequence searches M Mirdita, M Steinegger, J Söding Bioinformatics 35 (16), 2856–2858, 2019 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=D9XIZUAAAAJ&citationforview=D9XIZUAAAAJ:roLk4NBRz8UC Cited by: 355
Protein-level assembly increases protein sequence recovery from metagenomic samples manyfold M Steinegger, M Mirdita, J Söding Nature Methods 16, 603–606, 2019 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=D9XIZUAAAAJ&citationforview=D9XIZUAAAAJ:UebtZRa9Y70C Cited by: 330
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 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=D9XIZUAAAAJ&citationforview=D9XIZUAAAAJ:TFP_iSt0sucC Cited by: 290
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 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=D9XIZUAAAAJ&citationforview=D9XIZUAAAAJ:HDshCWvjkbEC Cited by: 225
Metagenome analysis using the Kraken software suite J Lu, N Rincon, DE Wood, FP Breitwieser, C Pockrandt, B Langmead, … Nature Protocols, 2022 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=D9XIZUAAAAJ&citationforview=D9XIZUAAAAJ:M05iB0D1s5AC Cited by: 203
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 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=D9XIZUAAAAJ&citationforview=D9XIZUAAAAJ:hC7cP41nSMkC Cited by: 184
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 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=D9XIZUAAAAJ&citationforview=D9XIZUAAAAJ:d1gkVwhDpl0C Cited by: 179
Terminating contamination: large-scale search identifies more than 2,000,000 contaminated entries in GenBank M Steinegger, SL Salzberg Genome Biology 21, 2020 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=D9XIZUAAAAJ&citationforview=D9XIZUAAAAJ:KlAtU1dfN6UC Cited by: 165
Fast and sensitive taxonomic assignment to metagenomic contigs M Mirdita, M Steinegger, F Breitwieser, J Söding, E Levy Karin Bioinformatics, 2021 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=D9XIZUAAAAJ&citationforview=D9XIZUAAAAJ:ZeXyd9-uunAC Cited by: 139
ProtTrans: Towards cracking the language of Life’s code through self-supervised deep learning and high performance computing. arXiv 2020 A Elnaggar, M Heinzinger, C Dallago, G Rihawi, Y Wang, L Jones, … arXiv preprint arXiv:2007.06225, 2020 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=D9XIZUAAAAJ&citationforview=D9XIZUAAAAJ:b0M2c_1WBrUC Cited by: 97
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 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=D9XIZUAAAAJ&citationforview=D9XIZUAAAAJ:UxriW0iASnsC Cited by: 95
Milot Mirdita googlescholarauthorid:jaTEOQAAAAJ
Johannes Söding googlescholarauthor_id:xjYIe80AAAAJ
Burkhard Rost googlescholarauthor_id:BP3ofxcAAAAJ
Michael Heinzinger googlescholarauthor_id:yXtPl58AAAAJ
Sergey Ovchinnikov googlescholarauthor_id:8KJ9gf4AAAAJ
Christian Dallago googlescholarauthor_id:4q0fNGAAAAAJ
Steven Salzberg googlescholarauthor_id:sUVeH-4AAAAJ
Ahmed Elnaggar googlescholarauthor_id:fadCsRsAAAAJ
Debsindhu Bhowmik googlescholarauthorid:nHwDssAAAAJ
Clovis Galiez googlescholarauthor_id:vmTnjSYAAAAJ
Antonio Fernàndez-Guerra googlescholarauthor_id:wA7Hrk8AAAAJ
Tom O. Delmont googlescholarauthorid:uZfiVUAAAAJ
Prof. Dr. Frank Oliver Glöckner googlescholarauthor_id:BmzoT3QAAAAJ
Maria J. Martin googlescholarauthor_id:kYxN8kQAAAAJ
Vikram Alva googlescholarauthor_id:nY7NEcYAAAAJ
Andrei Lupas googlescholarauthorid:FwQEo8AAAAJ
John Jumper googlescholarauthor_id:a5goOh8AAAAJ
Christof Angermueller googlescholarauthor_id:OXZC0mQAAAAJ
Demis Hassabis googlescholarauthor_id:dYpPMQEAAAAJ
David Silver googlescholarauthor_id:-8DNE4UAAAAJ
Martin Steinegger Associate Professor, Seoul National University, Korea http://steineggerlab.com/ Highly accurate protein structure prediction with AlphaFold J Jumper, R Evans, A Pritzel, T Green, M Figurnov, O Ronneberger, … Nature, 2021 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=D9XIZUAAAAJ&citationforview=D9XIZUAAAAJ:TQgYirikUcIC Cited by: 24355
ColabFold: making protein folding accessible to all M Mirdita, K Schütze, Y Moriwaki, L Heo, S Ovchinnikov, M Steinegger Nature Methods, 679–682, 2022 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=D9XIZUAAAAJ&citationforview=D9XIZUAAAAJ:RGFaLdJalmkC Cited by: 4585
MMseqs2 enables sensitive protein sequence searching for the analysis of massive data sets M Steinegger, J Söding Nature biotechnology 35 (11), 1026-1028, 2017 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=D9XIZUAAAAJ&citationforview=D9XIZUAAAAJ:YsMSGLbcyi4C Cited by: 2178
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 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=D9XIZUAAAAJ&citationforview=D9XIZUAAAAJ:R3hNpaxXUhUC Cited by: 1240
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 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=D9XIZUAAAAJ&citationforview=D9XIZUAAAAJ:5nxA0vEk-isC Cited by: 844
Clustering huge protein sequence sets in linear time M Steinegger, J Söding Nature communications 9 (1), 2542, 2018 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=D9XIZUAAAAJ&citationforview=D9XIZUAAAAJ:WF5omc3nYNoC Cited by: 659
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 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=D9XIZUAAAAJ&citationforview=D9XIZUAAAAJ:_xSYboBqXhAC Cited by: 633
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 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=D9XIZUAAAAJ&citationforview=D9XIZUAAAAJ:2osOgNQ5qMEC Cited by: 588
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 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=D9XIZUAAAAJ&citationforview=D9XIZUAAAAJ:4DMP91E08xMC Cited by: 533
MMseqs2 desktop and local web server app for fast, interactive sequence searches M Mirdita, M Steinegger, J Söding Bioinformatics 35 (16), 2856–2858, 2019 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=D9XIZUAAAAJ&citationforview=D9XIZUAAAAJ:roLk4NBRz8UC Cited by: 355
Protein-level assembly increases protein sequence recovery from metagenomic samples manyfold M Steinegger, M Mirdita, J Söding Nature Methods 16, 603–606, 2019 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=D9XIZUAAAAJ&citationforview=D9XIZUAAAAJ:UebtZRa9Y70C Cited by: 330
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 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=D9XIZUAAAAJ&citationforview=D9XIZUAAAAJ:TFP_iSt0sucC Cited by: 290
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 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=D9XIZUAAAAJ&citationforview=D9XIZUAAAAJ:HDshCWvjkbEC Cited by: 225
Metagenome analysis using the Kraken software suite J Lu, N Rincon, DE Wood, FP Breitwieser, C Pockrandt, B Langmead, … Nature Protocols, 2022 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=D9XIZUAAAAJ&citationforview=D9XIZUAAAAJ:M05iB0D1s5AC Cited by: 203
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 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=D9XIZUAAAAJ&citationforview=D9XIZUAAAAJ:hC7cP41nSMkC Cited by: 184
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 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=D9XIZUAAAAJ&citationforview=D9XIZUAAAAJ:d1gkVwhDpl0C Cited by: 179
Terminating contamination: large-scale search identifies more than 2,000,000 contaminated entries in GenBank M Steinegger, SL Salzberg Genome Biology 21, 2020 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=D9XIZUAAAAJ&citationforview=D9XIZUAAAAJ:KlAtU1dfN6UC Cited by: 165
Fast and sensitive taxonomic assignment to metagenomic contigs M Mirdita, M Steinegger, F Breitwieser, J Söding, E Levy Karin Bioinformatics, 2021 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=D9XIZUAAAAJ&citationforview=D9XIZUAAAAJ:ZeXyd9-uunAC Cited by: 139
ProtTrans: Towards cracking the language of Life’s code through self-supervised deep learning and high performance computing. arXiv 2020 A Elnaggar, M Heinzinger, C Dallago, G Rihawi, Y Wang, L Jones, … arXiv preprint arXiv:2007.06225, 2020 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=D9XIZUAAAAJ&citationforview=D9XIZUAAAAJ:b0M2c_1WBrUC Cited by: 97
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 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=D9XIZUAAAAJ&citationforview=D9XIZUAAAAJ:UxriW0iASnsC Cited by: 95
Milot Mirdita googlescholarauthorid milotmirdita.md:jaTEO_QAAAAJ
Johannes Söding googlescholarauthorid johannessöding.md:xjYIe80AAAAJ
Burkhard Rost googlescholarauthorid burkhardrost.md:BP3ofxcAAAAJ
Michael Heinzinger googlescholarauthorid michaelheinzinger.md:yXtPl58AAAAJ
Sergey Ovchinnikov googlescholarauthorid sergeyovchinnikov.md:8KJ9gf4AAAAJ
Christian Dallago googlescholarauthorid christiandallago.md:4q0fNGAAAAAJ
Steven Salzberg googlescholarauthorid stevensalzberg.md:sUVeH-4AAAAJ
Ahmed Elnaggar googlescholarauthorid ahmedelnaggar.md:fadCsRsAAAAJ
Debsindhu Bhowmik googlescholarauthorid debsindhubhowmik.md:nHwDs_sAAAAJ
Clovis Galiez googlescholarauthorid clovisgaliez.md:vmTnjSYAAAAJ
Antonio Fernàndez-Guerra googlescholarauthorid antoniofernàndez-guerra.md:wA7Hrk8AAAAJ
Tom O. Delmont googlescholarauthorid tomo.delmont.md:uZfiVUAAAAJ
Prof. Dr. Frank Oliver Glöckner googlescholarauthorid prof.dr.frankoliver_glöckner.md:BmzoT3QAAAAJ
Maria J. Martin googlescholarauthorid mariaj._martin.md:kYxN8kQAAAAJ
Vikram Alva googlescholarauthorid vikramalva.md:nY7NEcYAAAAJ
Andrei Lupas googlescholarauthorid andreilupas.md:FwQEo_8AAAAJ
John Jumper googlescholarauthorid johnjumper.md:a5goOh8AAAAJ
Christof Angermueller googlescholarauthorid christofangermueller.md:OXZC0mQAAAAJ
Demis Hassabis googlescholarauthorid demishassabis.md:dYpPMQEAAAAJ
David Silver googlescholarauthorid davidsilver.md:-8DNE4UAAAAJ
Martin Steinegger
Associate Professor, Seoul National University, Korea
http://steineggerlab.com/
Highly accurate protein structure prediction with AlphaFold J Jumper, R Evans, A Pritzel, T Green, M Figurnov, O Ronneberger, … Nature, 2021 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=D9XIZUAAAAJ&citationforview=D9XIZUAAAAJ:TQgYirikUcIC
ColabFold: making protein folding accessible to all M Mirdita, K Schütze, Y Moriwaki, L Heo, S Ovchinnikov, M Steinegger Nature Methods, 679–682, 2022 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=D9XIZUAAAAJ&citationforview=D9XIZUAAAAJ:RGFaLdJalmkC
MMseqs2 enables sensitive protein sequence searching for the analysis of massive data sets M Steinegger, J Söding Nature biotechnology 35 (11), 1026-1028, 2017 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=D9XIZUAAAAJ&citationforview=D9XIZUAAAAJ:YsMSGLbcyi4C
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 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=D9XIZUAAAAJ&citationforview=D9XIZUAAAAJ:R3hNpaxXUhUC
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 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=D9XIZUAAAAJ&citationforview=D9XIZUAAAAJ:5nxA0vEk-isC
Clustering huge protein sequence sets in linear time M Steinegger, J Söding Nature communications 9 (1), 2542, 2018 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=D9XIZUAAAAJ&citationforview=D9XIZUAAAAJ:WF5omc3nYNoC
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 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=D9XIZUAAAAJ&citationforview=D9XIZUAAAAJ:_xSYboBqXhAC
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 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=D9XIZUAAAAJ&citationforview=D9XIZUAAAAJ:2osOgNQ5qMEC
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 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=D9XIZUAAAAJ&citationforview=D9XIZUAAAAJ:4DMP91E08xMC
MMseqs2 desktop and local web server app for fast, interactive sequence searches M Mirdita, M Steinegger, J Söding Bioinformatics 35 (16), 2856–2858, 2019 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=D9XIZUAAAAJ&citationforview=D9XIZUAAAAJ:roLk4NBRz8UC
Protein-level assembly increases protein sequence recovery from metagenomic samples manyfold M Steinegger, M Mirdita, J Söding Nature Methods 16, 603–606, 2019 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=D9XIZUAAAAJ&citationforview=D9XIZUAAAAJ:UebtZRa9Y70C
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 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=D9XIZUAAAAJ&citationforview=D9XIZUAAAAJ:TFP_iSt0sucC
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 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=D9XIZUAAAAJ&citationforview=D9XIZUAAAAJ:HDshCWvjkbEC
Metagenome analysis using the Kraken software suite J Lu, N Rincon, DE Wood, FP Breitwieser, C Pockrandt, B Langmead, … Nature Protocols, 2022 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=D9XIZUAAAAJ&citationforview=D9XIZUAAAAJ:M05iB0D1s5AC
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 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=D9XIZUAAAAJ&citationforview=D9XIZUAAAAJ:hC7cP41nSMkC
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 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=D9XIZUAAAAJ&citationforview=D9XIZUAAAAJ:d1gkVwhDpl0C
Terminating contamination: large-scale search identifies more than 2,000,000 contaminated entries in GenBank M Steinegger, SL Salzberg Genome Biology 21, 2020 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=D9XIZUAAAAJ&citationforview=D9XIZUAAAAJ:KlAtU1dfN6UC
Fast and sensitive taxonomic assignment to metagenomic contigs M Mirdita, M Steinegger, F Breitwieser, J Söding, E Levy Karin Bioinformatics, 2021 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=D9XIZUAAAAJ&citationforview=D9XIZUAAAAJ:ZeXyd9-uunAC
ProtTrans: Towards cracking the language of Life’s code through self-supervised deep learning and high performance computing. arXiv 2020 A Elnaggar, M Heinzinger, C Dallago, G Rihawi, Y Wang, L Jones, … arXiv preprint arXiv:2007.06225, 2020 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=D9XIZUAAAAJ&citationforview=D9XIZUAAAAJ:b0M2c_1WBrUC
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 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=D9XIZUAAAAJ&citationforview=D9XIZUAAAAJ:UxriW0iASnsC
Milot Mirdita googlescholarauthorid milotmirdita.md:jaTEO_QAAAAJ
Johannes Söding googlescholarauthorid johannessöding.md:xjYIe80AAAAJ
Burkhard Rost googlescholarauthorid burkhardrost.md:BP3ofxcAAAAJ
Michael Heinzinger googlescholarauthorid michaelheinzinger.md:yXtPl58AAAAJ
Sergey Ovchinnikov googlescholarauthorid sergeyovchinnikov.md:8KJ9gf4AAAAJ
Christian Dallago googlescholarauthorid christiandallago.md:4q0fNGAAAAAJ
Steven Salzberg googlescholarauthorid stevensalzberg.md:sUVeH-4AAAAJ
Ahmed Elnaggar googlescholarauthorid ahmedelnaggar.md:fadCsRsAAAAJ
Debsindhu Bhowmik googlescholarauthorid debsindhubhowmik.md:nHwDs_sAAAAJ
Clovis Galiez googlescholarauthorid clovisgaliez.md:vmTnjSYAAAAJ
Antonio Fernàndez-Guerra googlescholarauthorid antoniofernàndez-guerra.md:wA7Hrk8AAAAJ
Tom O. Delmont googlescholarauthorid tomo.delmont.md:uZfiVUAAAAJ
Prof. Dr. Frank Oliver Glöckner googlescholarauthorid prof.dr.frankoliver_glöckner.md:BmzoT3QAAAAJ
Maria J. Martin googlescholarauthorid mariaj._martin.md:kYxN8kQAAAAJ
Vikram Alva googlescholarauthorid vikramalva.md:nY7NEcYAAAAJ
Andrei Lupas googlescholarauthorid andreilupas.md:FwQEo_8AAAAJ
John Jumper googlescholarauthorid johnjumper.md:a5goOh8AAAAJ
Christof Angermueller googlescholarauthorid christofangermueller.md:OXZC0mQAAAAJ
Demis Hassabis googlescholarauthorid demishassabis.md:dYpPMQEAAAAJ
David Silver googlescholarauthorid davidsilver.md:-8DNE4UAAAAJ
Summary: Martin Steinegger (born February 15, 1972) is a Swiss professional ice hockey defenceman. He played in the Nationalliga A for EHC Biel and SC Bern. He won the Swiss-A championship in 1997 and 2004 with SC Bern.
URL: https://en.wikipedia.org/wiki/Martin_Steinegger
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Content: Martin Steinegger (born February 15, 1972) is a Swiss professional ice hockey defenceman. He played in the Nationalliga A for EHC Biel and SC Bern. He won the Swiss-A championship in 1997 and 2004 with SC Bern.
International Play On April 24, 2006 Steinegger played his 200th game for the Swiss national team.
Career statistics Regular season and playoffs International External links Biographical information and career statistics from Eliteprospects.com, or Eurohockey.com, or The Internet Hockey Database