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Samaras P, Schmidt T, Frejno M, Gessulat S, Reinecke M, Jarzab A, Zecha J, Mergner J, Giansanti P, Ehrlich HC, Aiche S, Rank J, Kienegger H, Krcmar H, Kuster B, Wilhelm M. ProteomicsDB: a multi-omics and multi-organism resource for life science research. Nucleic Acids Res 2020; 48:D1153-D1163. [PMID: 31665479 PMCID: PMC7145565 DOI: 10.1093/nar/gkz974] [Citation(s) in RCA: 79] [Impact Index Per Article: 19.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2019] [Revised: 10/11/2019] [Accepted: 10/15/2019] [Indexed: 11/22/2022] Open
Abstract
ProteomicsDB (https://www.ProteomicsDB.org) started as a protein-centric in-memory database for the exploration of large collections of quantitative mass spectrometry-based proteomics data. The data types and contents grew over time to include RNA-Seq expression data, drug-target interactions and cell line viability data. In this manuscript, we summarize new developments since the previous update that was published in Nucleic Acids Research in 2017. Over the past two years, we have enriched the data content by additional datasets and extended the platform to support protein turnover data. Another important new addition is that ProteomicsDB now supports the storage and visualization of data collected from other organisms, exemplified by Arabidopsis thaliana. Due to the generic design of ProteomicsDB, all analytical features available for the original human resource seamlessly transfer to other organisms. Furthermore, we introduce a new service in ProteomicsDB which allows users to upload their own expression datasets and analyze them alongside with data stored in ProteomicsDB. Initially, users will be able to make use of this feature in the interactive heat map functionality as well as the drug sensitivity prediction, but ultimately will be able to use all analytical features of ProteomicsDB in this way.
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Affiliation(s)
- Patroklos Samaras
- Chair of Proteomics and Bioanalytics, Technical University of Munich (TUM), Freising, Bavaria, Germany
| | - Tobias Schmidt
- Chair of Proteomics and Bioanalytics, Technical University of Munich (TUM), Freising, Bavaria, Germany
| | - Martin Frejno
- Chair of Proteomics and Bioanalytics, Technical University of Munich (TUM), Freising, Bavaria, Germany
| | - Siegfried Gessulat
- Chair of Proteomics and Bioanalytics, Technical University of Munich (TUM), Freising, Bavaria, Germany.,Innovation Center Network, SAP SE, Potsdam, Germany
| | - Maria Reinecke
- Chair of Proteomics and Bioanalytics, Technical University of Munich (TUM), Freising, Bavaria, Germany.,German Cancer Consortium (DKTK), Partner Site Munich, Munich, Germany.,German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Anna Jarzab
- Chair of Proteomics and Bioanalytics, Technical University of Munich (TUM), Freising, Bavaria, Germany
| | - Jana Zecha
- Chair of Proteomics and Bioanalytics, Technical University of Munich (TUM), Freising, Bavaria, Germany
| | - Julia Mergner
- Chair of Proteomics and Bioanalytics, Technical University of Munich (TUM), Freising, Bavaria, Germany
| | - Piero Giansanti
- Chair of Proteomics and Bioanalytics, Technical University of Munich (TUM), Freising, Bavaria, Germany
| | | | | | - Johannes Rank
- Chair for Information Systems, Technical University of Munich (TUM), Garching, Germany.,SAP University Competence Center, Technical University of Munich (TUM), Garching, Germany
| | - Harald Kienegger
- Chair for Information Systems, Technical University of Munich (TUM), Garching, Germany.,SAP University Competence Center, Technical University of Munich (TUM), Garching, Germany
| | - Helmut Krcmar
- Chair for Information Systems, Technical University of Munich (TUM), Garching, Germany.,SAP University Competence Center, Technical University of Munich (TUM), Garching, Germany
| | - Bernhard Kuster
- Chair of Proteomics and Bioanalytics, Technical University of Munich (TUM), Freising, Bavaria, Germany.,Bavarian Biomolecular Mass Spectrometry Center (BayBioMS), Technical University of Munich (TUM), Freising, Bavaria, Germany
| | - Mathias Wilhelm
- Chair of Proteomics and Bioanalytics, Technical University of Munich (TUM), Freising, Bavaria, Germany
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Schmidt T, Samaras P, Frejno M, Gessulat S, Barnert M, Kienegger H, Krcmar H, Schlegl J, Ehrlich HC, Aiche S, Kuster B, Wilhelm M. ProteomicsDB. Nucleic Acids Res 2019; 46:D1271-D1281. [PMID: 29106664 PMCID: PMC5753189 DOI: 10.1093/nar/gkx1029] [Citation(s) in RCA: 153] [Impact Index Per Article: 30.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2017] [Accepted: 10/22/2017] [Indexed: 01/01/2023] Open
Abstract
ProteomicsDB (https://www.ProteomicsDB.org) is a protein-centric in-memory database for the exploration of large collections of quantitative mass spectrometry-based proteomics data. ProteomicsDB was first released in 2014 to enable the interactive exploration of the first draft of the human proteome. To date, it contains quantitative data from 78 projects totalling over 19k LC–MS/MS experiments. A standardized analysis pipeline enables comparisons between multiple datasets to facilitate the exploration of protein expression across hundreds of tissues, body fluids and cell lines. We recently extended the data model to enable the storage and integrated visualization of other quantitative omics data. This includes transcriptomics data from e.g. NCBI GEO, protein–protein interaction information from STRING, functional annotations from KEGG, drug-sensitivity/selectivity data from several public sources and reference mass spectra from the ProteomeTools project. The extended functionality transforms ProteomicsDB into a multi-purpose resource connecting quantification and meta-data for each protein. The rich user interface helps researchers to navigate all data sources in either a protein-centric or multi-protein-centric manner. Several options are available to download data manually, while our application programming interface enables accessing quantitative data systematically.
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Affiliation(s)
- Tobias Schmidt
- Chair of Proteomics and Bioanalytics, Technical University of Munich (TUM), Freising, 85354 Bavaria, Germany
| | - Patroklos Samaras
- Chair of Proteomics and Bioanalytics, Technical University of Munich (TUM), Freising, 85354 Bavaria, Germany
| | - Martin Frejno
- Chair of Proteomics and Bioanalytics, Technical University of Munich (TUM), Freising, 85354 Bavaria, Germany
| | - Siegfried Gessulat
- Chair of Proteomics and Bioanalytics, Technical University of Munich (TUM), Freising, 85354 Bavaria, Germany.,Innovation Center Network, SAP SE, Potsdam 14469, Germany
| | - Maximilian Barnert
- Chair for Information Systems, Technical University of Munich (TUM), Garching 85748, Germany.,SAP University Competence Center, Technical University of Munich (TUM), Garching 85748, Germany
| | - Harald Kienegger
- Chair for Information Systems, Technical University of Munich (TUM), Garching 85748, Germany.,SAP University Competence Center, Technical University of Munich (TUM), Garching 85748, Germany
| | - Helmut Krcmar
- Chair for Information Systems, Technical University of Munich (TUM), Garching 85748, Germany.,SAP University Competence Center, Technical University of Munich (TUM), Garching 85748, Germany
| | | | | | - Stephan Aiche
- Innovation Center Network, SAP SE, Potsdam 14469, Germany
| | - Bernhard Kuster
- Chair of Proteomics and Bioanalytics, Technical University of Munich (TUM), Freising, 85354 Bavaria, Germany.,Bavarian Biomolecular Mass Spectrometry Center (BayBioMS), Technical University of Munich (TUM), Freising, 85354 Bavaria, Germany
| | - Mathias Wilhelm
- Chair of Proteomics and Bioanalytics, Technical University of Munich (TUM), Freising, 85354 Bavaria, Germany
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