doi.bio/burkhard_rost


Burkhard Rost

Early Life and Education

Burkhard Rost (b. 1961) is a German researcher and teacher in the field of computational biology and bioinformatics. He studied physics, history, and philosophy at the University of Giessen and Heidelberg, and later psychology at the University of Heidelberg. In 1994, he received his PhD in physics from the University of Heidelberg for his work at the European Molecular Biology Laboratory (EMBL).

Career

Following his PhD, Rost held research internships at EMBL and the European Bioinformatics Institute in Cambridge, UK. He also spent a brief period in the industry at LION Bioscience in Heidelberg. In 1998, he became an assistant professor at the Department of Biochemistry and Molecular Biophysics at Columbia University in New York City. He was promoted to associate professor in 2000. In 2009, he moved to the Technical University of Munich (TUM) as the Chair of Bioinformatics.

At TUM, Rost leads the Department for Computational Biology & Bioinformatics at the Faculty of Informatics. He also chairs the Study Section Bioinformatics Munich, which involves both TUM and the Ludwig Maximilian University of Munich (LMU). From 2007 to 2014, Rost served as President of the International Society for Computational Biology (ISCB).

Rost's research focuses on combining machine learning and evolutionary information to predict and understand various aspects of evolution, protein structure, and protein function. His lab has carried out research in predicting enzymatic activity, interaction partners, subcellular localization, functional effects of point mutations, disordered regions, membrane-spanning segments, secondary structure, solvent accessibility, internal residue-residue contacts, and the clustering of proteins into families.

Rost's current research focus is on predicting the effects of individual mutations, particularly non-synonymous changes in coding regions, i.e., single nucleotide changes (or Single Nucleotide Polymorphisms) that alter the amino acid sequence. He has made his tools and resources available online, including through the first internet server for protein structure prediction and sequence analysis, Predictprotein, launched in 1992.

Rost has authored or co-authored over 200 scientific publications, with his work appearing in leading peer-reviewed journals such as Nature, Science, and PLOS Genetics. He has also been actively involved in organizing international conferences and meetings in the field of computational biology, including the ISMB and CASP meetings.

Awards and Recognition

Google Scholar Profile

Burkhard Rost)

Google Scholar

Burkhard Rost Professor of Computer Science & Computational Biology & Bioinformatics, TUM, Munich http://www.rostlab.org/ The transcriptional landscape of the mammalian genome P Carninci, T Kasukawa, S Katayama, J Gough, MC Frith, N Maeda, … science 309 (5740), 1559-1563, 2005 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=BP3ofxcAAAAJ&citationforview=BP3ofxcAAAAJ:9yKSN-GCB0IC Cited by: 4086

Prediction of protein secondary structure at better than 70% accuracy B Rost, C Sander Journal of molecular biology 232 (2), 584-599, 1993 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=BP3ofxcAAAAJ&citationforview=BP3ofxcAAAAJ:u5HHmVD_uO8C Cited by: 3888

Twilight zone of protein sequence alignments B Rost Protein engineering 12 (2), 85-94, 1999 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=BP3ofxcAAAAJ&citationforview=BP3ofxcAAAAJ:qjMakFHDy7sC Cited by: 2221

Combining evolutionary information and neural networks to predict protein secondary structure B Rost, C Sander Proteins: Structure, Function, and Bioinformatics 19 (1), 55-72, 1994 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=BP3ofxcAAAAJ&citationforview=BP3ofxcAAAAJ:u-x6o8ySG0sC Cited by: 1904

The PredictProtein server B Rost, G Yachdav, J Liu Nucleic acids research 32 (suppl2), W321-W326, 2004 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=BP3ofxcAAAAJ&citationfor_view=BP3ofxcAAAAJ:2osOgNQ5qMEC Cited by: 1849

PHD: Predicting one-dimensional protein structure by profile-based neural networks B Rost Methods in enzymology 266, 525-539, 1996 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=BP3ofxcAAAAJ&citationforview=BP3ofxcAAAAJ:d1gkVwhDpl0C Cited by: 1706

Prottrans: Toward understanding the language of life through self-supervised learning A Elnaggar, M Heinzinger, C Dallago, G Rehawi, Y Wang, L Jones, … IEEE transactions on pattern analysis and machine intelligence 44 (10), 7112 …, 2021 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=BP3ofxcAAAAJ&citationforview=BP3ofxcAAAAJ:qe6vwMD2xtsC Cited by: 1240

A mutation in VPS35, encoding a subunit of the retromer complex, causes late-onset Parkinson disease A Zimprich, A Benet-Pagès, W Struhal, E Graf, SH Eck, MN Offman, … The American Journal of Human Genetics 89 (1), 168-175, 2011 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=BP3ofxcAAAAJ&citationforview=BP3ofxcAAAAJ:lmc2jWPfTJgC Cited by: 1070

A large-scale evaluation of computational protein function prediction P Radivojac, WT Clark, TR Oron, AM Schnoes, T Wittkop, A Sokolov, … Nature methods 10 (3), 221-227, 2013 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=BP3ofxcAAAAJ&citationforview=BP3ofxcAAAAJ:SpbeaW3--B0C Cited by: 1059

Improving the prediction of protein secondary structure in three and eight classes using recurrent neural networks and profiles G Pollastri, D Przybylski, B Rost, P Baldi Proteins: Structure, Function, and Bioinformatics 47 (2), 228-235, 2002 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=BP3ofxcAAAAJ&citationforview=BP3ofxcAAAAJ:Tyk-4Ss8FVUC Cited by: 1001

SNAP: predict effect of non-synonymous polymorphisms on function Y Bromberg, B Rost Nucleic acids research 35 (11), 3823-3835, 2007 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=BP3ofxcAAAAJ&citationforview=BP3ofxcAAAAJ:hC7cP41nSMkC Cited by: 976

PHD-an automatic mail server for protein secondary structure prediction B Rost, C Sander, R Schneider Bioinformatics 10 (1), 53-60, 1994 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=BP3ofxcAAAAJ&citationforview=BP3ofxcAAAAJ:IjCSPb-OGe4C Cited by: 903

Finding nuclear localization signals M Cokol, R Nair, B Rost EMBO reports, 2000 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=BP3ofxcAAAAJ&citationforview=BP3ofxcAAAAJ:Y0pCki6q_DkC Cited by: 894

Topology prediction for helical transmembrane proteins at 86% accuracy–Topology prediction at 86% accuracy B Rost, P Fariselli, R Casadio Protein Science 5 (8), 1704-1718, 1996 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=BP3ofxcAAAAJ&citationforview=BP3ofxcAAAAJ:UeHWp8X0CEIC Cited by: 805

Conservation and prediction of solvent accessibility in protein families B Rost, C Sander Proteins: Structure, Function, and Bioinformatics 20 (3), 216-226, 1994 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=BP3ofxcAAAAJ&citationforview=BP3ofxcAAAAJ:YsMSGLbcyi4C Cited by: 797

A draft network of ligand–receptor-mediated multicellular signalling in human JA Ramilowski, T Goldberg, J Harshbarger, E Kloppmann, M Lizio, … Nature communications 6 (1), 7866, 2015 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=BP3ofxcAAAAJ&citationforview=BP3ofxcAAAAJ:Ehil0879vHcC Cited by: 758

Protein secondary structure prediction continues to rise B Rost Journal of structural biology 134 (2-3), 204-218, 2001 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=BP3ofxcAAAAJ&citationforview=BP3ofxcAAAAJ:eQOLeE2rZwMC Cited by: 738

Improved prediction of protein secondary structure by use of sequence profiles and neural networks. B Rost, C Sander Proceedings of the National Academy of Sciences 90 (16), 7558-7562, 1993 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=BP3ofxcAAAAJ&citationforview=BP3ofxcAAAAJ:W7OEmFMy1HYC Cited by: 717

PredictProtein—an open resource for online prediction of protein structural and functional features G Yachdav, E Kloppmann, L Kajan, M Hecht, T Goldberg, T Hamp, … Nucleic acids research 42 (W1), W337-W343, 2014 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=BP3ofxcAAAAJ&citationforview=BP3ofxcAAAAJ:XvxMoLDsR5gC Cited by: 694

Transmembrane helices predicted at 95% accuracy B Rost, C Sander, R Casadio, P Fariselli Protein Science 4 (3), 521-533, 1995 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=BP3ofxcAAAAJ&citationforview=BP3ofxcAAAAJ:zYLM7Y9cAGgC Cited by: 670

Co-authors

Chris Sander 4R7_wW8AAAAJ

Jinfeng Liu sTtD1jMAAAAJ

Tatyana Goldberg qXqFJZYAAAAJ

Yana Bromberg aL6XtIUAAAAJ

Guy Yachdav UoUkGhUAAAAJ

Gaetano T Montelione, Constellation… mrtpF44AAAAJ

Yanay Ofran xtRXLdkAAAAJ

Avner Schlessinger ejL6TPYAAAAJ

Dariusz Przybylski vlCdCO4AAAAJ

Reinhard Schneider HA9NPoEAAAAJ

Rong Xiao Ph.D. 2HYKBYMAAAAJ

Maximilian Hecht Hk104ucAAAAJ

Martin Steinegger _D9XIZUAAAAJ

Alfonso Valencia 4iB725QAAAAJ

Andrea Schafferhans 3sIfhrUAAAAJ

Seán O'Donoghue BY843RoAAAAJ

Christine Orengo CjQq6yYAAAAJ

Andrej Sali mNWliccAAAAJ

Piero Fariselli W7Z7PPYAAAAJ

Rita Casadio 59uymMgAAAAJ

Google Scholar

Burkhard Rost Professor of Computer Science & Computational Biology & Bioinformatics, TUM, Munich http://www.rostlab.org/ The transcriptional landscape of the mammalian genome P Carninci, T Kasukawa, S Katayama, J Gough, MC Frith, N Maeda, … science 309 (5740), 1559-1563, 2005 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=BP3ofxcAAAAJ&citationforview=BP3ofxcAAAAJ:9yKSN-GCB0IC Cited by: 4086

Prediction of protein secondary structure at better than 70% accuracy B Rost, C Sander Journal of molecular biology 232 (2), 584-599, 1993 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=BP3ofxcAAAAJ&citationforview=BP3ofxcAAAAJ:u5HHmVD_uO8C Cited by: 3888

Twilight zone of protein sequence alignments B Rost Protein engineering 12 (2), 85-94, 1999 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=BP3ofxcAAAAJ&citationforview=BP3ofxcAAAAJ:qjMakFHDy7sC Cited by: 2221

Combining evolutionary information and neural networks to predict protein secondary structure B Rost, C Sander Proteins: Structure, Function, and Bioinformatics 19 (1), 55-72, 1994 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=BP3ofxcAAAAJ&citationforview=BP3ofxcAAAAJ:u-x6o8ySG0sC Cited by: 1904

The PredictProtein server B Rost, G Yachdav, J Liu Nucleic acids research 32 (suppl2), W321-W326, 2004 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=BP3ofxcAAAAJ&citationfor_view=BP3ofxcAAAAJ:2osOgNQ5qMEC Cited by: 1849

PHD: Predicting one-dimensional protein structure by profile-based neural networks B Rost Methods in enzymology 266, 525-539, 1996 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=BP3ofxcAAAAJ&citationforview=BP3ofxcAAAAJ:d1gkVwhDpl0C Cited by: 1706

Prottrans: Toward understanding the language of life through self-supervised learning A Elnaggar, M Heinzinger, C Dallago, G Rehawi, Y Wang, L Jones, … IEEE transactions on pattern analysis and machine intelligence 44 (10), 7112 …, 2021 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=BP3ofxcAAAAJ&citationforview=BP3ofxcAAAAJ:qe6vwMD2xtsC Cited by: 1240

A mutation in VPS35, encoding a subunit of the retromer complex, causes late-onset Parkinson disease A Zimprich, A Benet-Pagès, W Struhal, E Graf, SH Eck, MN Offman, … The American Journal of Human Genetics 89 (1), 168-175, 2011 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=BP3ofxcAAAAJ&citationforview=BP3ofxcAAAAJ:lmc2jWPfTJgC Cited by: 1070

A large-scale evaluation of computational protein function prediction P Radivojac, WT Clark, TR Oron, AM Schnoes, T Wittkop, A Sokolov, … Nature methods 10 (3), 221-227, 2013 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=BP3ofxcAAAAJ&citationforview=BP3ofxcAAAAJ:SpbeaW3--B0C Cited by: 1059

Improving the prediction of protein secondary structure in three and eight classes using recurrent neural networks and profiles G Pollastri, D Przybylski, B Rost, P Baldi Proteins: Structure, Function, and Bioinformatics 47 (2), 228-235, 2002 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=BP3ofxcAAAAJ&citationforview=BP3ofxcAAAAJ:Tyk-4Ss8FVUC Cited by: 1001

SNAP: predict effect of non-synonymous polymorphisms on function Y Bromberg, B Rost Nucleic acids research 35 (11), 3823-3835, 2007 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=BP3ofxcAAAAJ&citationforview=BP3ofxcAAAAJ:hC7cP41nSMkC Cited by: 976

PHD-an automatic mail server for protein secondary structure prediction B Rost, C Sander, R Schneider Bioinformatics 10 (1), 53-60, 1994 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=BP3ofxcAAAAJ&citationforview=BP3ofxcAAAAJ:IjCSPb-OGe4C Cited by: 903

Finding nuclear localization signals M Cokol, R Nair, B Rost EMBO reports, 2000 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=BP3ofxcAAAAJ&citationforview=BP3ofxcAAAAJ:Y0pCki6q_DkC Cited by: 894

Topology prediction for helical transmembrane proteins at 86% accuracy–Topology prediction at 86% accuracy B Rost, P Fariselli, R Casadio Protein Science 5 (8), 1704-1718, 1996 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=BP3ofxcAAAAJ&citationforview=BP3ofxcAAAAJ:UeHWp8X0CEIC Cited by: 805

Conservation and prediction of solvent accessibility in protein families B Rost, C Sander Proteins: Structure, Function, and Bioinformatics 20 (3), 216-226, 1994 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=BP3ofxcAAAAJ&citationforview=BP3ofxcAAAAJ:YsMSGLbcyi4C Cited by: 797

A draft network of ligand–receptor-mediated multicellular signalling in human JA Ramilowski, T Goldberg, J Harshbarger, E Kloppmann, M Lizio, … Nature communications 6 (1), 7866, 2015 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=BP3ofxcAAAAJ&citationforview=BP3ofxcAAAAJ:Ehil0879vHcC Cited by: 758

Protein secondary structure prediction continues to rise B Rost Journal of structural biology 134 (2-3), 204-218, 2001 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=BP3ofxcAAAAJ&citationforview=BP3ofxcAAAAJ:eQOLeE2rZwMC Cited by: 738

Improved prediction of protein secondary structure by use of sequence profiles and neural networks. B Rost, C Sander Proceedings of the National Academy of Sciences 90 (16), 7558-7562, 1993 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=BP3ofxcAAAAJ&citationforview=BP3ofxcAAAAJ:W7OEmFMy1HYC Cited by: 717

PredictProtein—an open resource for online prediction of protein structural and functional features G Yachdav, E Kloppmann, L Kajan, M Hecht, T Goldberg, T Hamp, … Nucleic acids research 42 (W1), W337-W343, 2014 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=BP3ofxcAAAAJ&citationforview=BP3ofxcAAAAJ:XvxMoLDsR5gC Cited by: 694

Transmembrane helices predicted at 95% accuracy B Rost, C Sander, R Casadio, P Fariselli Protein Science 4 (3), 521-533, 1995 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=BP3ofxcAAAAJ&citationforview=BP3ofxcAAAAJ:zYLM7Y9cAGgC Cited by: 670

Co-authors

Chris Sander googlescholarauthorid:4R7wW8AAAAJ

Jinfeng Liu googlescholarauthor_id:sTtD1jMAAAAJ

Tatyana Goldberg googlescholarauthor_id:qXqFJZYAAAAJ

Yana Bromberg googlescholarauthor_id:aL6XtIUAAAAJ

Guy Yachdav googlescholarauthor_id:UoUkGhUAAAAJ

Gaetano T Montelione, Constellation… googlescholarauthor_id:mrtpF44AAAAJ

Yanay Ofran googlescholarauthor_id:xtRXLdkAAAAJ

Avner Schlessinger googlescholarauthor_id:ejL6TPYAAAAJ

Dariusz Przybylski googlescholarauthor_id:vlCdCO4AAAAJ

Reinhard Schneider googlescholarauthor_id:HA9NPoEAAAAJ

Rong Xiao Ph.D. googlescholarauthor_id:2HYKBYMAAAAJ

Maximilian Hecht googlescholarauthor_id:Hk104ucAAAAJ

Martin Steinegger googlescholarauthorid:D9XIZUAAAAJ

Alfonso Valencia googlescholarauthor_id:4iB725QAAAAJ

Andrea Schafferhans googlescholarauthor_id:3sIfhrUAAAAJ

Seán O'Donoghue googlescholarauthor_id:BY843RoAAAAJ

Christine Orengo googlescholarauthor_id:CjQq6yYAAAAJ

Andrej Sali googlescholarauthor_id:mNWliccAAAAJ

Piero Fariselli googlescholarauthor_id:W7Z7PPYAAAAJ

Rita Casadio googlescholarauthor_id:59uymMgAAAAJ

Google Scholar

Burkhard Rost Professor of Computer Science & Computational Biology & Bioinformatics, TUM, Munich http://www.rostlab.org/ The transcriptional landscape of the mammalian genome P Carninci, T Kasukawa, S Katayama, J Gough, MC Frith, N Maeda, … science 309 (5740), 1559-1563, 2005 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=BP3ofxcAAAAJ&citationforview=BP3ofxcAAAAJ:9yKSN-GCB0IC Cited by: 4086

Prediction of protein secondary structure at better than 70% accuracy B Rost, C Sander Journal of molecular biology 232 (2), 584-599, 1993 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=BP3ofxcAAAAJ&citationforview=BP3ofxcAAAAJ:u5HHmVD_uO8C Cited by: 3888

Twilight zone of protein sequence alignments B Rost Protein engineering 12 (2), 85-94, 1999 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=BP3ofxcAAAAJ&citationforview=BP3ofxcAAAAJ:qjMakFHDy7sC Cited by: 2221

Combining evolutionary information and neural networks to predict protein secondary structure B Rost, C Sander Proteins: Structure, Function, and Bioinformatics 19 (1), 55-72, 1994 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=BP3ofxcAAAAJ&citationforview=BP3ofxcAAAAJ:u-x6o8ySG0sC Cited by: 1904

The PredictProtein server B Rost, G Yachdav, J Liu Nucleic acids research 32 (suppl2), W321-W326, 2004 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=BP3ofxcAAAAJ&citationfor_view=BP3ofxcAAAAJ:2osOgNQ5qMEC Cited by: 1849

PHD: Predicting one-dimensional protein structure by profile-based neural networks B Rost Methods in enzymology 266, 525-539, 1996 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=BP3ofxcAAAAJ&citationforview=BP3ofxcAAAAJ:d1gkVwhDpl0C Cited by: 1706

Prottrans: Toward understanding the language of life through self-supervised learning A Elnaggar, M Heinzinger, C Dallago, G Rehawi, Y Wang, L Jones, … IEEE transactions on pattern analysis and machine intelligence 44 (10), 7112 …, 2021 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=BP3ofxcAAAAJ&citationforview=BP3ofxcAAAAJ:qe6vwMD2xtsC Cited by: 1240

A mutation in VPS35, encoding a subunit of the retromer complex, causes late-onset Parkinson disease A Zimprich, A Benet-Pagès, W Struhal, E Graf, SH Eck, MN Offman, … The American Journal of Human Genetics 89 (1), 168-175, 2011 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=BP3ofxcAAAAJ&citationforview=BP3ofxcAAAAJ:lmc2jWPfTJgC Cited by: 1070

A large-scale evaluation of computational protein function prediction P Radivojac, WT Clark, TR Oron, AM Schnoes, T Wittkop, A Sokolov, … Nature methods 10 (3), 221-227, 2013 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=BP3ofxcAAAAJ&citationforview=BP3ofxcAAAAJ:SpbeaW3--B0C Cited by: 1059

Improving the prediction of protein secondary structure in three and eight classes using recurrent neural networks and profiles G Pollastri, D Przybylski, B Rost, P Baldi Proteins: Structure, Function, and Bioinformatics 47 (2), 228-235, 2002 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=BP3ofxcAAAAJ&citationforview=BP3ofxcAAAAJ:Tyk-4Ss8FVUC Cited by: 1001

SNAP: predict effect of non-synonymous polymorphisms on function Y Bromberg, B Rost Nucleic acids research 35 (11), 3823-3835, 2007 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=BP3ofxcAAAAJ&citationforview=BP3ofxcAAAAJ:hC7cP41nSMkC Cited by: 976

PHD-an automatic mail server for protein secondary structure prediction B Rost, C Sander, R Schneider Bioinformatics 10 (1), 53-60, 1994 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=BP3ofxcAAAAJ&citationforview=BP3ofxcAAAAJ:IjCSPb-OGe4C Cited by: 903

Finding nuclear localization signals M Cokol, R Nair, B Rost EMBO reports, 2000 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=BP3ofxcAAAAJ&citationforview=BP3ofxcAAAAJ:Y0pCki6q_DkC Cited by: 894

Topology prediction for helical transmembrane proteins at 86% accuracy–Topology prediction at 86% accuracy B Rost, P Fariselli, R Casadio Protein Science 5 (8), 1704-1718, 1996 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=BP3ofxcAAAAJ&citationforview=BP3ofxcAAAAJ:UeHWp8X0CEIC Cited by: 805

Conservation and prediction of solvent accessibility in protein families B Rost, C Sander Proteins: Structure, Function, and Bioinformatics 20 (3), 216-226, 1994 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=BP3ofxcAAAAJ&citationforview=BP3ofxcAAAAJ:YsMSGLbcyi4C Cited by: 797

A draft network of ligand–receptor-mediated multicellular signalling in human JA Ramilowski, T Goldberg, J Harshbarger, E Kloppmann, M Lizio, … Nature communications 6 (1), 7866, 2015 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=BP3ofxcAAAAJ&citationforview=BP3ofxcAAAAJ:Ehil0879vHcC Cited by: 758

Protein secondary structure prediction continues to rise B Rost Journal of structural biology 134 (2-3), 204-218, 2001 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=BP3ofxcAAAAJ&citationforview=BP3ofxcAAAAJ:eQOLeE2rZwMC Cited by: 738

Improved prediction of protein secondary structure by use of sequence profiles and neural networks. B Rost, C Sander Proceedings of the National Academy of Sciences 90 (16), 7558-7562, 1993 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=BP3ofxcAAAAJ&citationforview=BP3ofxcAAAAJ:W7OEmFMy1HYC Cited by: 717

PredictProtein—an open resource for online prediction of protein structural and functional features G Yachdav, E Kloppmann, L Kajan, M Hecht, T Goldberg, T Hamp, … Nucleic acids research 42 (W1), W337-W343, 2014 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=BP3ofxcAAAAJ&citationforview=BP3ofxcAAAAJ:XvxMoLDsR5gC Cited by: 694

Transmembrane helices predicted at 95% accuracy B Rost, C Sander, R Casadio, P Fariselli Protein Science 4 (3), 521-533, 1995 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=BP3ofxcAAAAJ&citationforview=BP3ofxcAAAAJ:zYLM7Y9cAGgC Cited by: 670

Co-authors

Chris Sander googlescholarauthorid:[chrissander.md][4R7_wW8AAAAJ]

Jinfeng Liu googlescholarauthorid:[jinfengliu.md][sTtD1jMAAAAJ]

Tatyana Goldberg googlescholarauthorid:[tatyanagoldberg.md][qXqFJZYAAAAJ]

Yana Bromberg googlescholarauthorid:[yanabromberg.md][aL6XtIUAAAAJ]

Guy Yachdav googlescholarauthorid:[guyyachdav.md][UoUkGhUAAAAJ]

Gaetano T Montelione, Constellation… googlescholarauthorid:[gaetanotmontelione,constellation….md][mrtpF44AAAAJ]

Yanay Ofran googlescholarauthorid:[yanayofran.md][xtRXLdkAAAAJ]

Avner Schlessinger googlescholarauthorid:[avnerschlessinger.md][ejL6TPYAAAAJ]

Dariusz Przybylski googlescholarauthorid:[dariuszprzybylski.md][vlCdCO4AAAAJ]

Reinhard Schneider googlescholarauthorid:[reinhardschneider.md][HA9NPoEAAAAJ]

Rong Xiao Ph.D. googlescholarauthorid:[rongxiao_ph.d..md][2HYKBYMAAAAJ]

Maximilian Hecht googlescholarauthorid:[maximilianhecht.md][Hk104ucAAAAJ]

Martin Steinegger googlescholarauthorid:[martinsteinegger.md][_D9XIZUAAAAJ]

Alfonso Valencia googlescholarauthorid:[alfonsovalencia.md][4iB725QAAAAJ]

Andrea Schafferhans googlescholarauthorid:[andreaschafferhans.md][3sIfhrUAAAAJ]

Seán O'Donoghue googlescholarauthorid:[seáno'donoghue.md][BY843RoAAAAJ]

Christine Orengo googlescholarauthorid:[christineorengo.md][CjQq6yYAAAAJ]

Andrej Sali googlescholarauthorid:[andrejsali.md][mNWliccAAAAJ]

Piero Fariselli googlescholarauthorid:[pierofariselli.md][W7Z7PPYAAAAJ]

Rita Casadio googlescholarauthorid:[ritacasadio.md][59uymMgAAAAJ]

Google Scholar

Burkhard Rost Professor of Computer Science & Computational Biology & Bioinformatics, TUM, Munich http://www.rostlab.org/ The transcriptional landscape of the mammalian genome P Carninci, T Kasukawa, S Katayama, J Gough, MC Frith, N Maeda, … science 309 (5740), 1559-1563, 2005 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=BP3ofxcAAAAJ&citationforview=BP3ofxcAAAAJ:9yKSN-GCB0IC Cited by: 4086

Prediction of protein secondary structure at better than 70% accuracy B Rost, C Sander Journal of molecular biology 232 (2), 584-599, 1993 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=BP3ofxcAAAAJ&citationforview=BP3ofxcAAAAJ:u5HHmVD_uO8C Cited by: 3888

Twilight zone of protein sequence alignments B Rost Protein engineering 12 (2), 85-94, 1999 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=BP3ofxcAAAAJ&citationforview=BP3ofxcAAAAJ:qjMakFHDy7sC Cited by: 2221

Combining evolutionary information and neural networks to predict protein secondary structure B Rost, C Sander Proteins: Structure, Function, and Bioinformatics 19 (1), 55-72, 1994 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=BP3ofxcAAAAJ&citationforview=BP3ofxcAAAAJ:u-x6o8ySG0sC Cited by: 1904

The PredictProtein server B Rost, G Yachdav, J Liu Nucleic acids research 32 (suppl2), W321-W326, 2004 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=BP3ofxcAAAAJ&citationfor_view=BP3ofxcAAAAJ:2osOgNQ5qMEC Cited by: 1849

PHD: Predicting one-dimensional protein structure by profile-based neural networks B Rost Methods in enzymology 266, 525-539, 1996 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=BP3ofxcAAAAJ&citationforview=BP3ofxcAAAAJ:d1gkVwhDpl0C Cited by: 1706

Prottrans: Toward understanding the language of life through self-supervised learning A Elnaggar, M Heinzinger, C Dallago, G Rehawi, Y Wang, L Jones, … IEEE transactions on pattern analysis and machine intelligence 44 (10), 7112 …, 2021 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=BP3ofxcAAAAJ&citationforview=BP3ofxcAAAAJ:qe6vwMD2xtsC Cited by: 1240

A mutation in VPS35, encoding a subunit of the retromer complex, causes late-onset Parkinson disease A Zimprich, A Benet-Pagès, W Struhal, E Graf, SH Eck, MN Offman, … The American Journal of Human Genetics 89 (1), 168-175, 2011 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=BP3ofxcAAAAJ&citationforview=BP3ofxcAAAAJ:lmc2jWPfTJgC Cited by: 1070

A large-scale evaluation of computational protein function prediction P Radivojac, WT Clark, TR Oron, AM Schnoes, T Wittkop, A Sokolov, … Nature methods 10 (3), 221-227, 2013 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=BP3ofxcAAAAJ&citationforview=BP3ofxcAAAAJ:SpbeaW3--B0C Cited by: 1059

Improving the prediction of protein secondary structure in three and eight classes using recurrent neural networks and profiles G Pollastri, D Przybylski, B Rost, P Baldi Proteins: Structure, Function, and Bioinformatics 47 (2), 228-235, 2002 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=BP3ofxcAAAAJ&citationforview=BP3ofxcAAAAJ:Tyk-4Ss8FVUC Cited by: 1001

SNAP: predict effect of non-synonymous polymorphisms on function Y Bromberg, B Rost Nucleic acids research 35 (11), 3823-3835, 2007 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=BP3ofxcAAAAJ&citationforview=BP3ofxcAAAAJ:hC7cP41nSMkC Cited by: 976

PHD-an automatic mail server for protein secondary structure prediction B Rost, C Sander, R Schneider Bioinformatics 10 (1), 53-60, 1994 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=BP3ofxcAAAAJ&citationforview=BP3ofxcAAAAJ:IjCSPb-OGe4C Cited by: 903

Finding nuclear localization signals M Cokol, R Nair, B Rost EMBO reports, 2000 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=BP3ofxcAAAAJ&citationforview=BP3ofxcAAAAJ:Y0pCki6q_DkC Cited by: 894

Topology prediction for helical transmembrane proteins at 86% accuracy–Topology prediction at 86% accuracy B Rost, P Fariselli, R Casadio Protein Science 5 (8), 1704-1718, 1996 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=BP3ofxcAAAAJ&citationforview=BP3ofxcAAAAJ:UeHWp8X0CEIC Cited by: 805

Conservation and prediction of solvent accessibility in protein families B Rost, C Sander Proteins: Structure, Function, and Bioinformatics 20 (3), 216-226, 1994 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=BP3ofxcAAAAJ&citationforview=BP3ofxcAAAAJ:YsMSGLbcyi4C Cited by: 797

A draft network of ligand–receptor-mediated multicellular signalling in human JA Ramilowski, T Goldberg, J Harshbarger, E Kloppmann, M Lizio, … Nature communications 6 (1), 7866, 2015 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=BP3ofxcAAAAJ&citationforview=BP3ofxcAAAAJ:Ehil0879vHcC Cited by: 758

Protein secondary structure prediction continues to rise B Rost Journal of structural biology 134 (2-3), 204-218, 2001 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=BP3ofxcAAAAJ&citationforview=BP3ofxcAAAAJ:eQOLeE2rZwMC Cited by: 738

Improved prediction of protein secondary structure by use of sequence profiles and neural networks. B Rost, C Sander Proceedings of the National Academy of Sciences 90 (16), 7558-7562, 1993 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=BP3ofxcAAAAJ&citationforview=BP3ofxcAAAAJ:W7OEmFMy1HYC Cited by: 717

PredictProtein—an open resource for online prediction of protein structural and functional features G Yachdav, E Kloppmann, L Kajan, M Hecht, T Goldberg, T Hamp, … Nucleic acids research 42 (W1), W337-W343, 2014 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=BP3ofxcAAAAJ&citationforview=BP3ofxcAAAAJ:XvxMoLDsR5gC Cited by: 694

Transmembrane helices predicted at 95% accuracy B Rost, C Sander, R Casadio, P Fariselli Protein Science 4 (3), 521-533, 1995 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=BP3ofxcAAAAJ&citationforview=BP3ofxcAAAAJ:zYLM7Y9cAGgC Cited by: 670

Co-authors

Chris Sander googlescholarauthorid chrissander.md:4R7_wW8AAAAJ

Jinfeng Liu googlescholarauthorid jinfengliu.md:sTtD1jMAAAAJ

Tatyana Goldberg googlescholarauthorid tatyanagoldberg.md:qXqFJZYAAAAJ

Yana Bromberg googlescholarauthorid yanabromberg.md:aL6XtIUAAAAJ

Guy Yachdav googlescholarauthorid guyyachdav.md:UoUkGhUAAAAJ

Gaetano T Montelione, Constellation… googlescholarauthorid gaetanotmontelione,constellation….md:mrtpF44AAAAJ

Yanay Ofran googlescholarauthorid yanayofran.md:xtRXLdkAAAAJ

Avner Schlessinger googlescholarauthorid avnerschlessinger.md:ejL6TPYAAAAJ

Dariusz Przybylski googlescholarauthorid dariuszprzybylski.md:vlCdCO4AAAAJ

Reinhard Schneider googlescholarauthorid reinhardschneider.md:HA9NPoEAAAAJ

Rong Xiao Ph.D. googlescholarauthorid rongxiao_ph.d..md:2HYKBYMAAAAJ

Maximilian Hecht googlescholarauthorid maximilianhecht.md:Hk104ucAAAAJ

Martin Steinegger googlescholarauthorid martinsteinegger.md:_D9XIZUAAAAJ

Alfonso Valencia googlescholarauthorid alfonsovalencia.md:4iB725QAAAAJ

Andrea Schafferhans googlescholarauthorid andreaschafferhans.md:3sIfhrUAAAAJ

Seán O'Donoghue googlescholarauthorid seáno'donoghue.md:BY843RoAAAAJ

Christine Orengo googlescholarauthorid christineorengo.md:CjQq6yYAAAAJ

Andrej Sali googlescholarauthorid andrejsali.md:mNWliccAAAAJ

Piero Fariselli googlescholarauthorid pierofariselli.md:W7Z7PPYAAAAJ

Rita Casadio googlescholarauthorid ritacasadio.md:59uymMgAAAAJ

Google Scholar

Burkhard Rost

Professor of Computer Science & Computational Biology & Bioinformatics, TUM, Munich

http://www.rostlab.org/

The transcriptional landscape of the mammalian genome P Carninci, T Kasukawa, S Katayama, J Gough, MC Frith, N Maeda, … science 309 (5740), 1559-1563, 2005 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=BP3ofxcAAAAJ&citationforview=BP3ofxcAAAAJ:9yKSN-GCB0IC Cited by: 4086

Prediction of protein secondary structure at better than 70% accuracy B Rost, C Sander Journal of molecular biology 232 (2), 584-599, 1993 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=BP3ofxcAAAAJ&citationforview=BP3ofxcAAAAJ:u5HHmVD_uO8C Cited by: 3888

Twilight zone of protein sequence alignments B Rost Protein engineering 12 (2), 85-94, 1999 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=BP3ofxcAAAAJ&citationforview=BP3ofxcAAAAJ:qjMakFHDy7sC Cited by: 2221

Combining evolutionary information and neural networks to predict protein secondary structure B Rost, C Sander Proteins: Structure, Function, and Bioinformatics 19 (1), 55-72, 1994 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=BP3ofxcAAAAJ&citationforview=BP3ofxcAAAAJ:u-x6o8ySG0sC Cited by: 1904

The PredictProtein server B Rost, G Yachdav, J Liu Nucleic acids research 32 (suppl2), W321-W326, 2004 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=BP3ofxcAAAAJ&citationfor_view=BP3ofxcAAAAJ:2osOgNQ5qMEC Cited by: 1849

PHD: Predicting one-dimensional protein structure by profile-based neural networks B Rost Methods in enzymology 266, 525-539, 1996 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=BP3ofxcAAAAJ&citationforview=BP3ofxcAAAAJ:d1gkVwhDpl0C Cited by: 1706

Prottrans: Toward understanding the language of life through self-supervised learning A Elnaggar, M Heinzinger, C Dallago, G Rehawi, Y Wang, L Jones, … IEEE transactions on pattern analysis and machine intelligence 44 (10), 7112 …, 2021 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=BP3ofxcAAAAJ&citationforview=BP3ofxcAAAAJ:qe6vwMD2xtsC Cited by: 1240

A mutation in VPS35, encoding a subunit of the retromer complex, causes late-onset Parkinson disease A Zimprich, A Benet-Pagès, W Struhal, E Graf, SH Eck, MN Offman, … The American Journal of Human Genetics 89 (1), 168-175, 2011 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=BP3ofxcAAAAJ&citationforview=BP3ofxcAAAAJ:lmc2jWPfTJgC Cited by: 1070

A large-scale evaluation of computational protein function prediction P Radivojac, WT Clark, TR Oron, AM Schnoes, T Wittkop, A Sokolov, … Nature methods 10 (3), 221-227, 2013 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=BP3ofxcAAAAJ&citationforview=BP3ofxcAAAAJ:SpbeaW3--B0C Cited by: 1059

Improving the prediction of protein secondary structure in three and eight classes using recurrent neural networks and profiles G Pollastri, D Przybylski, B Rost, P Baldi Proteins: Structure, Function, and Bioinformatics 47 (2), 228-235, 2002 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=BP3ofxcAAAAJ&citationforview=BP3ofxcAAAAJ:Tyk-4Ss8FVUC Cited by: 1001

SNAP: predict effect of non-synonymous polymorphisms on function Y Bromberg, B Rost Nucleic acids research 35 (11), 3823-3835, 2007 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=BP3ofxcAAAAJ&citationforview=BP3ofxcAAAAJ:hC7cP41nSMkC Cited by: 976

PHD-an automatic mail server for protein secondary structure prediction B Rost, C Sander, R Schneider Bioinformatics 10 (1), 53-60, 1994 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=BP3ofxcAAAAJ&citationforview=BP3ofxcAAAAJ:IjCSPb-OGe4C Cited by: 903

Finding nuclear localization signals M Cokol, R Nair, B Rost EMBO reports, 2000 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=BP3ofxcAAAAJ&citationforview=BP3ofxcAAAAJ:Y0pCki6q_DkC Cited by: 894

Topology prediction for helical transmembrane proteins at 86% accuracy–Topology prediction at 86% accuracy B Rost, P Fariselli, R Casadio Protein Science 5 (8), 1704-1718, 1996 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=BP3ofxcAAAAJ&citationforview=BP3ofxcAAAAJ:UeHWp8X0CEIC Cited by: 805

Conservation and prediction of solvent accessibility in protein families B Rost, C Sander Proteins: Structure, Function, and Bioinformatics 20 (3), 216-226, 1994 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=BP3ofxcAAAAJ&citationforview=BP3ofxcAAAAJ:YsMSGLbcyi4C Cited by: 797

A draft network of ligand–receptor-mediated multicellular signalling in human JA Ramilowski, T Goldberg, J Harshbarger, E Kloppmann, M Lizio, … Nature communications 6 (1), 7866, 2015 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=BP3ofxcAAAAJ&citationforview=BP3ofxcAAAAJ:Ehil0879vHcC Cited by: 758

Protein secondary structure prediction continues to rise B Rost Journal of structural biology 134 (2-3), 204-218, 2001 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=BP3ofxcAAAAJ&citationforview=BP3ofxcAAAAJ:eQOLeE2rZwMC Cited by: 738

Improved prediction of protein secondary structure by use of sequence profiles and neural networks. B Rost, C Sander Proceedings of the National Academy of Sciences 90 (16), 7558-7562, 1993 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=BP3ofxcAAAAJ&citationforview=BP3ofxcAAAAJ:W7OEmFMy1HYC Cited by: 717

PredictProtein—an open resource for online prediction of protein structural and functional features G Yachdav, E Kloppmann, L Kajan, M Hecht, T Goldberg, T Hamp, … Nucleic acids research 42 (W1), W337-W343, 2014 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=BP3ofxcAAAAJ&citationforview=BP3ofxcAAAAJ:XvxMoLDsR5gC Cited by: 694

Transmembrane helices predicted at 95% accuracy B Rost, C Sander, R Casadio, P Fariselli Protein Science 4 (3), 521-533, 1995 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=BP3ofxcAAAAJ&citationforview=BP3ofxcAAAAJ:zYLM7Y9cAGgC Cited by: 670

Co-authors

Chris Sander googlescholarauthorid chrissander.md:4R7_wW8AAAAJ

Jinfeng Liu googlescholarauthorid jinfengliu.md:sTtD1jMAAAAJ

Tatyana Goldberg googlescholarauthorid tatyanagoldberg.md:qXqFJZYAAAAJ

Yana Bromberg googlescholarauthorid yanabromberg.md:aL6XtIUAAAAJ

Guy Yachdav googlescholarauthorid guyyachdav.md:UoUkGhUAAAAJ

Gaetano T Montelione, Constellation… googlescholarauthorid gaetanotmontelione,constellation….md:mrtpF44AAAAJ

Yanay Ofran googlescholarauthorid yanayofran.md:xtRXLdkAAAAJ

Avner Schlessinger googlescholarauthorid avnerschlessinger.md:ejL6TPYAAAAJ

Dariusz Przybylski googlescholarauthorid dariuszprzybylski.md:vlCdCO4AAAAJ

Reinhard Schneider googlescholarauthorid reinhardschneider.md:HA9NPoEAAAAJ

Rong Xiao Ph.D. googlescholarauthorid rongxiao_ph.d..md:2HYKBYMAAAAJ

Maximilian Hecht googlescholarauthorid maximilianhecht.md:Hk104ucAAAAJ

Martin Steinegger googlescholarauthorid martinsteinegger.md:_D9XIZUAAAAJ

Alfonso Valencia googlescholarauthorid alfonsovalencia.md:4iB725QAAAAJ

Andrea Schafferhans googlescholarauthorid andreaschafferhans.md:3sIfhrUAAAAJ

Seán O'Donoghue googlescholarauthorid seáno'donoghue.md:BY843RoAAAAJ

Christine Orengo googlescholarauthorid christineorengo.md:CjQq6yYAAAAJ

Andrej Sali googlescholarauthorid andrejsali.md:mNWliccAAAAJ

Piero Fariselli googlescholarauthorid pierofariselli.md:W7Z7PPYAAAAJ

Rita Casadio googlescholarauthorid ritacasadio.md:59uymMgAAAAJ

Youtube Videos

Youtube Title: Personalized health -- harnessing the power of diversity | Burkhard Rost | TEDxTUM

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Youtube Channel Name: TEDx Talks

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Personalized health -- harnessing the power of diversity | Burkhard Rost | TEDxTUM

Youtube Title: Burkhard Rost : Artificial Intelligence captures language of life written in proteins

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Youtube Channel Name: Centre International de Rencontres Mathématiques

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Burkhard Rost : Artificial Intelligence captures language of life written in proteins

Youtube Title: Artificial Intelligence captures language of life… - Burkhard Rost - 3D-SIG - ISMB/ECCB 2023

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Youtube Channel Name: ISCB

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Artificial Intelligence captures language of life... - Burkhard Rost - 3D-SIG - ISMB/ECCB 2023

Youtube Title: Burkhard Rost on how machine learning boosts protein and genetic studies

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Youtube Channel Name: Academic Influence

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Burkhard Rost on how machine learning boosts protein and genetic studies

Youtube Title: Computational Biologist Prof. Burkhard Rost

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Computational Biologist Prof. Burkhard Rost

Youtube Title: Prof. Burkhard Rost

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Prof. Burkhard Rost

Youtube Title: Questions to Humboldt Professor Burkhard Rost

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Questions to Humboldt Professor Burkhard Rost

Youtube Title: Burkhard Rost - Artificial Intelligence captures language of life written in protein

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Youtube Channel Name: Accademia delle Scienze dell'Istituto di Bologna

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Burkhard Rost - Artificial Intelligence captures language of life written in protein

Youtube Title: Burkhard Rost talks with Karina about finding your own path in biology

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Youtube Channel Name: Academic Influence

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Burkhard Rost talks with Karina about finding your own path in biology

Youtube Title: Burkhard Rost - Alexander von Humboldt Professorship 2009 (EN)

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Youtube Channel Name: Alexander von Humboldt-Stiftung

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Burkhard Rost - Alexander von Humboldt Professorship 2009 (EN)

Youtube Title: Der Bioinformatiker Prof. Burkhard Rost

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Youtube Channel Name: TUMuenchen

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Der Bioinformatiker Prof. Burkhard Rost

Youtube Title: Keynote by Prof. Burkhard Rost -- #BLAHmuc Live Stream, Tuesday 20th

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Youtube Channel Name: ROSTLAB

Youtube Channel Link: https://www.youtube.com/@ROSTLAB

Keynote by Prof. Burkhard Rost -- #BLAHmuc Live Stream, Tuesday 20th

Youtube Title: Artificial Intelligence captures Language of Life written in proteins | Prof. Dr. Burkhard Rost

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Youtube Channel Name: BdOSN

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Artificial Intelligence captures Language of Life written in proteins | Prof. Dr. Burkhard Rost

Youtube Title: Fragen an Humboldt-Professor Burkhard Rost

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Youtube Channel Name: Alexander von Humboldt-Stiftung

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Fragen an Humboldt-Professor Burkhard Rost

Youtube Title: Protein Prediction 1 for Computer Scientists - Lecture 10, Membrane Structure Prediction

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Protein Prediction 1 for Computer Scientists - Lecture 10, Membrane Structure Prediction

Youtube Title: Protein Prediction 1 for Bioinformaticians - Lecture 6, Secondary Structure Prediction

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Protein Prediction 1 for Bioinformaticians - Lecture 6, Secondary Structure Prediction

Youtube Title: Protein Prediction 2 for Computer Scientists - Lecture 2, Introduction to protein function

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Protein Prediction 2 for Computer Scientists - Lecture 2, Introduction to protein function

Youtube Title: Protein Prediction 1 for Computer Scientists – Lecture 1, Intro into Protein Structure

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Protein Prediction 1 for Computer Scientists – Lecture 1, Intro into Protein Structure

Youtube Title: Protein Prediction 2 for Bioinformaticians – Lecture 1, Introduction

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Protein Prediction 2 for Bioinformaticians – Lecture 1, Introduction

Youtube Title: Protein Prediction for Computer Scientists - Lecture 2, Structure

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Protein Prediction for Computer Scientists - Lecture 2, Structure

Wikipedia

Burkhard Rost

Summary: Burkhard Rost is a scientist leading the Department for Computational Biology & Bioinformatics at the Faculty of Informatics of the Technical University of Munich (TUM). Rost chairs the Study Section Bioinformatics Munich involving the TUM and the Ludwig Maximilian University of Munich (LMU) in Munich. From 2007-2014 Rost was President of the International Society for Computational Biology (ISCB).

URL: https://en.wikipedia.org/wiki/Burkhard_Rost

Page ID: 38463183

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Content: Burkhard Rost is a scientist leading the Department for Computational Biology & Bioinformatics at the Faculty of Informatics of the Technical University of Munich (TUM). Rost chairs the Study Section Bioinformatics Munich involving the TUM and the Ludwig Maximilian University of Munich (LMU) in Munich. From 2007-2014 Rost was President of the International Society for Computational Biology (ISCB).

Career Rost originally started his scientific career as theoretical physicist. After studying physics at the University of Giessen and physics, history, philosophy, and psychology at the University of Heidelberg, Rost received his PhD at the University Heidelberg for his work at the European Molecular Biology Laboratory (EMBL) in 1994. Following research internships at EMBL and the European Bioinformatics Institute in Cambridge (UK), in 1998, he became assistant professor at the Department of Biochemistry and Molecular Biophysics in the College of Surgeons and Physicians of the CU Medical Center of Columbia University in the City of New York. In 2000, he became associate professor at Columbia University and in 2009 he accepted an appointment to the Chair of Bioinformatics at the Technical University of Munich. He is a member of the New York Academy of Sciences and has been President of ISCB, the International Society for Computational Biology from 2007-2014. As of 2021, Rost has authored or co-authored over 300 scientific publications with a Google Scholar h-index of 100.

Research Rost research has focused on combining Machine Learning and evolutionary information to predict aspects of critical importance to advance our understanding of evolution, protein structure and protein function. Examples of research carried out in his lab includes the prediction of enzymatic activity (ECGO), interaction partners (ISIS, DISIS, PiNAT), subcellular localization (LOCtree, LOCnet, PredictNLS), functional effects of point mutations/SNPs (SNAP), disordered regions (MD, NORSnet, Ucon), membrane spanning segments (PROF/PHDhtm), secondary structure (PROF/PHD, RePROF, DSSPcont), solvent accessibility (PROF/PHD, RePROF), internal residue-residue contacts (PROFcon) and the clustering of proteins into families (CHOP). His current focus is on predicting the effects of individual mutations mostly on the level of non-synonymous changes in coding regions, i.e. single nucleotide changes (or Single Nucleotide Polymorphisms) that alter the amino acid sequence. His group has been dedicated to making their tools available online as demonstrated through the first internet server for protein structure prediction and sequence analysis, Predictprotein, that was launched in 1992, and has been continuously in service ever since. Rost's work has been published in leading peer reviewed scientific journals including Nature, Science, PLOS Genetics.

ISCB In 2007 Rost was elected president of the International Society for Computational Biology (ISCB), taking over from Michael Gribskov. Rost served as president until 2014; his successor was Alfonso Valencia.

Conferences Rost has co-chaired the largest annual meeting in computational biology ISMB, Intelligent Systems for Molecular Biology, in 2007 (Vienna), 2008 (Toronto), 2011 (Vienna), 2012 (Long Beach). He has initiated and been involved in the organization of several series of international conferences outside the usual northern hemisphere, namely ISCB Africa (2010: Bamako, Mali; 2011: Cape Town, South Africa; 2013: Tunis, Tunisia) in cooperation with the African Society for Bioinformatics and Computational Biology, ISCB Latin America (2010: Montevideo, Uruguay; 2012: Santiago de Chile, Chile; 2014: Rio de Janeiro, Brazil), and most recently ISCB Asia (2011: Kuala Lumpur, Malaysia; 2012: Shen Zhen, China). Rost has also been a co-organizer of the Critical Assessment of protein Structure Prediction (CASP) meetings from 2002-2008 (CASP4-CASP8).

Awards and honors Rost was awarded the Professorship of the Alexander von Humboldt Foundation in 2009. He was made a Fellow of the ISCB in 2015. In 2016, he was awarded the Outstanding Contribution to ISCB.

References External links Rostlab web site Burkhard Rost at TEDx: Personalized health: harnessing the power of diversity TEDx) Alexander von Humboldt Award