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Stephan Aiche
Researcher at Free University of Berlin
Publications - 15
Citations - 2224
Stephan Aiche is an academic researcher from Free University of Berlin. The author has contributed to research in topics: Workflow & Workflow engine. The author has an hindex of 12, co-authored 15 publications receiving 1524 citations.
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Journal ArticleDOI
The target landscape of clinical kinase drugs
Susan Klaeger,Susan Klaeger,Stephanie Heinzlmeir,Stephanie Heinzlmeir,Mathias Wilhelm,Harald Polzer,Harald Polzer,Binje Vick,Paul-Albert Koenig,Maria Reinecke,Maria Reinecke,Benjamin Ruprecht,Svenja Petzoldt,Svenja Petzoldt,Chen Meng,Jana Zecha,Jana Zecha,Katrin Reiter,Katrin Reiter,Huichao Qiao,Dominic Helm,Heiner Koch,Heiner Koch,Melanie Schoof,G. Canevari,Elena Casale,Stefania Re Depaolini,Annette Feuchtinger,Zhixiang Wu,Tobias Schmidt,Lars Rueckert,Wilhelm Becker,Jan Huenges,Anne-Kathrin Garz,Bjoern-Oliver Gohlke,Bjoern-Oliver Gohlke,Daniel P Zolg,Gian Kayser,Tõnu Vooder,Tõnu Vooder,Robert Preissner,Robert Preissner,Hannes Hahne,Neeme Tõnisson,Neeme Tõnisson,Karl Kramer,Katharina Götze,Florian Bassermann,Judith Schlegl,Hans-Christian Ehrlich,Stephan Aiche,Axel Walch,Philipp A. Greif,Philipp A. Greif,Sabine Schneider,Eduard R. Felder,Juergen Ruland,Guillaume Médard,Irmela Jeremias,Karsten Spiekermann,Karsten Spiekermann,Bernhard Kuster +61 more
TL;DR: A comprehensive analysis of 243 kinase inhibitors that are either approved for use or in clinical trials provides an open-access resource of target summaries that could help researchers develop better drugs, understand how existing drugs work, and design more effective clinical trials.
Journal ArticleDOI
Prosit: proteome-wide prediction of peptide tandem mass spectra by deep learning.
Siegfried Gessulat,Tobias Schmidt,Daniel P Zolg,Patroklos Samaras,Karsten Schnatbaum,Johannes Zerweck,Tobias Knaute,Julia Rechenberger,Bernard Delanghe,Andreas Huhmer,Ulf Reimer,Hans-Christian Ehrlich,Stephan Aiche,Bernhard Kuster,Mathias Wilhelm +14 more
TL;DR: A deep learning–based tool, Prosit, predicts high-quality peptide tandem mass spectra, improving peptide-identification performance compared with that of traditional proteomics analysis methods.
Journal ArticleDOI
OpenMS: a flexible open-source software platform for mass spectrometry data analysis
Hannes L. Röst,Hannes L. Röst,Timo Sachsenberg,Stephan Aiche,Chris Bielow,Hendrik Weisser,Fabian Aicheler,Sandro Andreotti,Hans-Christian Ehrlich,Petra Gutenbrunner,Erhan Kenar,Xiao Liang,Sven Nahnsen,Lars Nilse,Julianus Pfeuffer,George Rosenberger,Marc Rurik,Uwe Schmitt,Johannes Veit,Mathias Walzer,David Wojnar,Witold Wolski,Oliver Schilling,Jyoti S. Choudhary,Lars Malmström,Lars Malmström,Ruedi Aebersold,Ruedi Aebersold,Knut Reinert,Knut Reinert,Oliver Kohlbacher +30 more
TL;DR: OpenMS 2.0 is presented, a robust, open-source, cross-platform software specifically designed for the flexible and reproducible analysis of high-throughput MS data.
Journal ArticleDOI
Building ProteomeTools based on a complete synthetic human proteome
Daniel P Zolg,Mathias Wilhelm,Karsten Schnatbaum,Johannes Zerweck,Tobias Knaute,Bernard Delanghe,Derek J. Bailey,Siegfried Gessulat,Hans-Christian Ehrlich,Maximilian Weininger,Peng Yu,Judith Schlegl,Karl Kramer,Tobias Schmidt,Ulrike Kusebauch,Eric W. Deutsch,Ruedi Aebersold,Ruedi Aebersold,Robert L. Moritz,Holger Wenschuh,Thomas Moehring,Stephan Aiche,Andreas Huhmer,Ulf Reimer,Bernhard Kuster,Bernhard Kuster +25 more
TL;DR: ProteomeTools, a project building molecular and digital tools from the human proteome to facilitate biomedical research, is described and the generation and multimodal liquid chromatography–tandem mass spectrometry analysis of >330,000 synthetic tryptic peptides representing essentially all canonical human gene products is reported.
Journal ArticleDOI
ProteomicsDB: a multi-omics and multi-organism resource for life science research.
Patroklos Samaras,Tobias Schmidt,Martin Frejno,Siegfried Gessulat,Maria Reinecke,Maria Reinecke,Maria Reinecke,Anna Jarzab,Jana Zecha,Julia Mergner,Piero Giansanti,Hans-Christian Ehrlich,Stephan Aiche,Johannes Rank,Harald Kienegger,Helmut Krcmar,Bernhard Kuster,Mathias Wilhelm +17 more
TL;DR: A new service in ProteomicsDB is introduced which allows users to upload their own expression datasets and analyze them alongside with data stored in ProeomicsDB, and supports the storage and visualization of data collected from other organisms, exemplified by Arabidopsis thaliana.