Proceedings of the EuBIC Winter School 2019

Overview

Journal EuPA Open Proteom

Specialty Biology

Date 2020 Jan 1

PMID 31890545

Authors

Dominik Kopczynski

Wout Bittremieux

David Bouyssie

Viktoria Dorfer

Marie Locard-Paulet

Bart Van Puyvelde

Veit Schwammle

Alessio Soggiu

Sander Willems

Julian Uszkoreit

Affiliations

Soon will be listed here.

Abstract

The 2019 European Bioinformatics Community (EuBIC) Winter School was held from January 15th to January 18th 2019 in Zakopane, Poland. This year's meeting was the third of its kind and gathered international researchers in the field of (computational) proteomics to discuss (mainly) challenges in proteomics quantification and data independent acquisition (DIA). Here, we present an overview of the scientific program of the 2019 EuBIC Winter School. Furthermore, we can already give a small outlook to the upcoming EuBIC 2020 Developer's Meeting.

References

Gupta S, Ahadi S, Zhou W, Rost H . DIAlignR Provides Precise Retention Time Alignment Across Distant Runs in DIA and Targeted Proteomics. Mol Cell Proteomics. 2019; 18(4):806-817. PMC: 6442363. DOI: 10.1074/mcp.TIR118.001132. View

Degroeve S, Maddelein D, Martens L . MS2PIP prediction server: compute and visualize MS2 peak intensity predictions for CID and HCD fragmentation. Nucleic Acids Res. 2015; 43(W1):W326-30. PMC: 4489309. DOI: 10.1093/nar/gkv542. View

Uszkoreit J, Maerkens A, Perez-Riverol Y, Meyer H, Marcus K, Stephan C . PIA: An Intuitive Protein Inference Engine with a Web-Based User Interface. J Proteome Res. 2015; 14(7):2988-97. DOI: 10.1021/acs.jproteome.5b00121. View

Doncheva N, Morris J, Gorodkin J, Jensen L . Cytoscape StringApp: Network Analysis and Visualization of Proteomics Data. J Proteome Res. 2018; 18(2):623-632. PMC: 6800166. DOI: 10.1021/acs.jproteome.8b00702. View

Zolg D, Wilhelm M, Schnatbaum K, Zerweck J, Knaute T, Delanghe B . Building ProteomeTools based on a complete synthetic human proteome. Nat Methods. 2017; 14(3):259-262. PMC: 5868332. DOI: 10.1038/nmeth.4153. View

Turewicz M, Kohl M, Ahrens M, Mayer G, Uszkoreit J, Naboulsi W . BioInfra.Prot: A comprehensive proteomics workflow including data standardization, protein inference, expression analysis and data publication. J Biotechnol. 2017; 261:116-125. DOI: 10.1016/j.jbiotec.2017.06.005. View

. UniProt: a worldwide hub of protein knowledge. Nucleic Acids Res. 2018; 47(D1):D506-D515. PMC: 6323992. DOI: 10.1093/nar/gky1049. View

Meier F, Brunner A, Koch S, Koch H, Lubeck M, Krause M . Online Parallel Accumulation-Serial Fragmentation (PASEF) with a Novel Trapped Ion Mobility Mass Spectrometer. Mol Cell Proteomics. 2018; 17(12):2534-2545. PMC: 6283298. DOI: 10.1074/mcp.TIR118.000900. View

Szklarczyk D, Gable A, Lyon D, Junge A, Wyder S, Huerta-Cepas J . STRING v11: protein-protein association networks with increased coverage, supporting functional discovery in genome-wide experimental datasets. Nucleic Acids Res. 2018; 47(D1):D607-D613. PMC: 6323986. DOI: 10.1093/nar/gky1131. View

10.

Giudice G, Petsalaki E . Proteomics and phosphoproteomics in precision medicine: applications and challenges. Brief Bioinform. 2017; 20(3):767-777. PMC: 6585152. DOI: 10.1093/bib/bbx141. View

11.

Gessulat S, Schmidt T, Zolg D, Samaras P, Schnatbaum K, Zerweck J . Prosit: proteome-wide prediction of peptide tandem mass spectra by deep learning. Nat Methods. 2019; 16(6):509-518. DOI: 10.1038/s41592-019-0426-7. View

12.

Frohlich H, Balling R, Beerenwinkel N, Kohlbacher O, Kumar S, Lengauer T . From hype to reality: data science enabling personalized medicine. BMC Med. 2018; 16(1):150. PMC: 6109989. DOI: 10.1186/s12916-018-1122-7. View

13.

Piening B, Zhou W, Contrepois K, Rost H, Gu Urban G, Mishra T . Integrative Personal Omics Profiles during Periods of Weight Gain and Loss. Cell Syst. 2018; 6(2):157-170.e8. PMC: 6021558. DOI: 10.1016/j.cels.2017.12.013. View

14.

Gabriels R, Martens L, Degroeve S . Updated MS²PIP web server delivers fast and accurate MS² peak intensity prediction for multiple fragmentation methods, instruments and labeling techniques. Nucleic Acids Res. 2019; 47(W1):W295-W299. PMC: 6602496. DOI: 10.1093/nar/gkz299. View

15.

Petsalaki E, Helbig A, Gopal A, Pasculescu A, Roth F, Pawson T . SELPHI: correlation-based identification of kinase-associated networks from global phospho-proteomics data sets. Nucleic Acids Res. 2015; 43(W1):W276-82. PMC: 4489257. DOI: 10.1093/nar/gkv459. View

16.

Schmidt T, Samaras P, Frejno M, Gessulat S, Barnert M, Kienegger H . ProteomicsDB. Nucleic Acids Res. 2017; 46(D1):D1271-D1281. PMC: 5753189. DOI: 10.1093/nar/gkx1029. View

17.

Geladaki A, Britovsek N, Breckels L, Smith T, Vennard O, Mulvey C . Combining LOPIT with differential ultracentrifugation for high-resolution spatial proteomics. Nat Commun. 2019; 10(1):331. PMC: 6338729. DOI: 10.1038/s41467-018-08191-w. View

18.

Willems S, Bouyssie D, David M, Locard-Paulet M, Mechtler K, Schwammle V . Proceedings of the EuBIC Winter School 2017. J Proteomics. 2017; 161:78-80. DOI: 10.1016/j.jprot.2017.04.001. View

19.

Uszkoreit J, Perez-Riverol Y, Eggers B, Marcus K, Eisenacher M . Protein Inference Using PIA Workflows and PSI Standard File Formats. J Proteome Res. 2018; 18(2):741-747. DOI: 10.1021/acs.jproteome.8b00723. View

20.

Navarro P, Kuharev J, Gillet L, Bernhardt O, MacLean B, Rost H . A multicenter study benchmarks software tools for label-free proteome quantification. Nat Biotechnol. 2016; 34(11):1130-1136. PMC: 5120688. DOI: 10.1038/nbt.3685. View