publication . Article . Contribution for newspaper or weekly magazine . 2019

Proceedings of the EuBIC Winter School 2019.

Dominik Kopczynski; Veit Schwämmle; Sander Willems; Wout Bittremieux; Marie Locard-Paulet; David Bouyssié; Bart Van Puyvelde; Viktoria Dorfer; Julian Uszkoreit; Alessio Soggiu;
Open Access
  • Published: 01 Mar 2019
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. Keywords: EuBIC, Computational proteomics, Bioinformatics, Protein quantification, Date independent acquisition
doi: 10.1016/j.euprot.2019.07.002
pmc: PMC6924290
pmid: 31890545
Subjects
free text keywords: Biochemistry, Chemistry, Computer. Automation, Genetics, QH426-470, EuBIC, Computational proteomics, Bioinformatics, Protein quantification, Date independent acquisition, /dk/atira/pure/researchoutput/pubmedpublicationtype/D016428, Journal Article, Article, Engineering, business.industry, business, Data science, Quantitative proteomics
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26 references, page 1 of 2

Willems, S., Bouyssié, D., David, M., Locard-Paulet, M., Mechtler, K., Schwämmle, V., Uszkoreit, J., Vaudel, M., Dorfer, V.. Proceedings of the EuBIC Winter School 2017. J. Proteomics. 2017; 161: 78-80 [PubMed]

Willems, S., Bouyssié, D., Deforce, D., Dorfer, V., Gorshkov, V., Kopczynski, D., Laukens, K., Locard-Paulet, M., Schwämmle, V., Uszkoreit, J., Valkenborg, D., Vaudel, M., Bittremieux, W.. Proceedings of the EuBIC developer’s meeting 2018. J. Proteomics. 2018; 187: 25-27 [PubMed]

Turewicz, M., Kohl, M., Ahrens, M., Mayer, G., Uszkoreit, J., Naboulsi, W., Bracht, T., Megger, D.A., Sitek, B., Marcus, K., Eisenacher, M.. BioInfra.Prot: A comprehensive proteomics workflow including data standardization, protein inference, expression analysis and data publication. J. Biotechnol.. 2017; 261: 116-125 [PubMed]

Consortium, U.. UniProt: a worldwide hub of protein knowledge. Nucleic Acids Res.. 2019; 47: D506-D515 [OpenAIRE] [PubMed]

Berthold, M.R., Cebron, N., Dill, F., Gabriel, T.R., Kotter, T., Meinl, T., Ohl, P., Sieb, C., Thiel, K., Wiswedel, B.. KNIME: the konstanz information miner. Data Anal. Mach. Learning App.. 2008: 319-326

Uszkoreit, J., Maerkens, A., Perez-Riverol, Y., Meyer, H.E., Marcus, K., Stephan, C., Kohlbacher, O., Eisenacher, M.. PIA: an intuitive protein inference engine with a web-based user interface. J. Proteome Res.. 2015; 14: 2988-2997 [PubMed]

Uszkoreit, J., Perez-Riverol, Y., Eggers, B., Marcus, K., Eisenacher, M.. Protein inference using PIA workflows and PSI standard file formats. J. Proteome Res.. 2019; 18: 741-747 [PubMed]

Navarro, P., Kuharev, J., Gillet, L.C., Bernhardt, O.M., MacLean, B., Röst, H.L., Tate, S.A., Tsou, C.C., Reiter, L., Distler, U., Rosenberger, G., Perez-Riverol, Y., Nesvizhskii, A.I., Aebersold, R., Tenzer, S.. A multicenter study benchmarks software tools for label- free proteome quantification. Nat. Biotechnol.. 2016; 34: 1130-1136 [OpenAIRE] [PubMed]

Doncheva, N.T., Morris, J.H., Gorodkin, J., Jensen, L.J.. Cytoscape StringApp: Network Analysis and Visualization of Proteomics Data. J. Proteome Res.. 2019; 18: 623-632 [OpenAIRE] [PubMed]

Schmidt, T., Samaras, P., Frejno, M., Gessulat, S., Barnert, M., Kienegger, H., Krcmar, H., Schlegl, J., Ehrlich, H.C., Aiche, S., Kuster, B., Wilhelm, M.. ProteomicsDB. Nucleic Acids Res.. 2018; 46: D1271-D1281 [OpenAIRE] [PubMed]

Petsalaki, E., Helbig, A.O., Gopal, A., Pasculescu, A., Roth, F.P., Pawson, T.. SELPHI: correlation-based identification of kinase-associated networks from global phospho-proteomics data sets. Nucleic Acids Res.. 2015; 43: W276-282 [OpenAIRE] [PubMed]

Wichmann, C., Meier, F., Virreira Winter, S., Brunner, A.D., Cox, J., Mann, M.. MaxQuant.Live Enables Global Targeting of More Than 25,000 Peptides. Mol. Cell Proteomics. 2019; 18: 982-994 [PubMed]

Searle, B.C., Pino, L.K., Egertson, J.D., Ting, Y.S., Lawrence, R.T., MacLean, B.X., Villén, J., MacCoss, M.J.. Chromatogram libraries improve peptide detection and quantification by data independent acquisition mass spectrometry. Nat. Commun.. 2018; 9: 5128 [OpenAIRE] [PubMed]

Gupta, S., Ahadi, S., Zhou, W., Röst, H.. DIAlignR Provides Precise Retention Time Alignment Across Distant Runs in DIA and Targeted Proteomics. Mol. Cell Proteomics. 2019; 18: 806-817 [OpenAIRE] [PubMed]

Piening, B.D., Zhou, W., Contrepois, K., Röst, H., Gu Urban, G.J., Mishra, T., Hanson, B.M., Bautista, E.J., Leopold, S., Yeh, C.Y., Spakowicz, D., Banerjee, I., Chen, C., Kukurba, K., Perelman, D., Craig, C., Colbert, E., Salins, D., Rego, S., Lee, S., Zhang, C., Wheeler, J., Sailani, M.R., Liang, L., Abbott, C., Gerstein, M., Mardinoglu, A., Smith, U., Rubin, D.L., Pitteri, S., Sodergren, E., McLaughlin, T.L., Weinstock, G.M., Snyder, M.P.. Integrative personal omics profiles during periods of weight gain and loss. Cell Syst.. 2018; 6: 157-170 [OpenAIRE] [PubMed]

26 references, page 1 of 2
Related research
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. Keywords: EuBIC, Computational proteomics, Bioinformatics, Protein quantification, Date independent acquisition
doi: 10.1016/j.euprot.2019.07.002
pmc: PMC6924290
pmid: 31890545
Subjects
free text keywords: Biochemistry, Chemistry, Computer. Automation, Genetics, QH426-470, EuBIC, Computational proteomics, Bioinformatics, Protein quantification, Date independent acquisition, /dk/atira/pure/researchoutput/pubmedpublicationtype/D016428, Journal Article, Article, Engineering, business.industry, business, Data science, Quantitative proteomics
Related Organizations
View more
Download fromView all 7 versions
ZENODO
Article . 2019
Provider: ZENODO
EuPA Open Proteomics
Article . 2019
Provider: Crossref
EuPA Open Proteomics
Article
Provider: UnpayWall
EuPA Open Proteomics
Article
Provider: Microsoft Academic Graph
View more
26 references, page 1 of 2

Willems, S., Bouyssié, D., David, M., Locard-Paulet, M., Mechtler, K., Schwämmle, V., Uszkoreit, J., Vaudel, M., Dorfer, V.. Proceedings of the EuBIC Winter School 2017. J. Proteomics. 2017; 161: 78-80 [PubMed]

Willems, S., Bouyssié, D., Deforce, D., Dorfer, V., Gorshkov, V., Kopczynski, D., Laukens, K., Locard-Paulet, M., Schwämmle, V., Uszkoreit, J., Valkenborg, D., Vaudel, M., Bittremieux, W.. Proceedings of the EuBIC developer’s meeting 2018. J. Proteomics. 2018; 187: 25-27 [PubMed]

Turewicz, M., Kohl, M., Ahrens, M., Mayer, G., Uszkoreit, J., Naboulsi, W., Bracht, T., Megger, D.A., Sitek, B., Marcus, K., Eisenacher, M.. BioInfra.Prot: A comprehensive proteomics workflow including data standardization, protein inference, expression analysis and data publication. J. Biotechnol.. 2017; 261: 116-125 [PubMed]

Consortium, U.. UniProt: a worldwide hub of protein knowledge. Nucleic Acids Res.. 2019; 47: D506-D515 [OpenAIRE] [PubMed]

Berthold, M.R., Cebron, N., Dill, F., Gabriel, T.R., Kotter, T., Meinl, T., Ohl, P., Sieb, C., Thiel, K., Wiswedel, B.. KNIME: the konstanz information miner. Data Anal. Mach. Learning App.. 2008: 319-326

Uszkoreit, J., Maerkens, A., Perez-Riverol, Y., Meyer, H.E., Marcus, K., Stephan, C., Kohlbacher, O., Eisenacher, M.. PIA: an intuitive protein inference engine with a web-based user interface. J. Proteome Res.. 2015; 14: 2988-2997 [PubMed]

Uszkoreit, J., Perez-Riverol, Y., Eggers, B., Marcus, K., Eisenacher, M.. Protein inference using PIA workflows and PSI standard file formats. J. Proteome Res.. 2019; 18: 741-747 [PubMed]

Navarro, P., Kuharev, J., Gillet, L.C., Bernhardt, O.M., MacLean, B., Röst, H.L., Tate, S.A., Tsou, C.C., Reiter, L., Distler, U., Rosenberger, G., Perez-Riverol, Y., Nesvizhskii, A.I., Aebersold, R., Tenzer, S.. A multicenter study benchmarks software tools for label- free proteome quantification. Nat. Biotechnol.. 2016; 34: 1130-1136 [OpenAIRE] [PubMed]

Doncheva, N.T., Morris, J.H., Gorodkin, J., Jensen, L.J.. Cytoscape StringApp: Network Analysis and Visualization of Proteomics Data. J. Proteome Res.. 2019; 18: 623-632 [OpenAIRE] [PubMed]

Schmidt, T., Samaras, P., Frejno, M., Gessulat, S., Barnert, M., Kienegger, H., Krcmar, H., Schlegl, J., Ehrlich, H.C., Aiche, S., Kuster, B., Wilhelm, M.. ProteomicsDB. Nucleic Acids Res.. 2018; 46: D1271-D1281 [OpenAIRE] [PubMed]

Petsalaki, E., Helbig, A.O., Gopal, A., Pasculescu, A., Roth, F.P., Pawson, T.. SELPHI: correlation-based identification of kinase-associated networks from global phospho-proteomics data sets. Nucleic Acids Res.. 2015; 43: W276-282 [OpenAIRE] [PubMed]

Wichmann, C., Meier, F., Virreira Winter, S., Brunner, A.D., Cox, J., Mann, M.. MaxQuant.Live Enables Global Targeting of More Than 25,000 Peptides. Mol. Cell Proteomics. 2019; 18: 982-994 [PubMed]

Searle, B.C., Pino, L.K., Egertson, J.D., Ting, Y.S., Lawrence, R.T., MacLean, B.X., Villén, J., MacCoss, M.J.. Chromatogram libraries improve peptide detection and quantification by data independent acquisition mass spectrometry. Nat. Commun.. 2018; 9: 5128 [OpenAIRE] [PubMed]

Gupta, S., Ahadi, S., Zhou, W., Röst, H.. DIAlignR Provides Precise Retention Time Alignment Across Distant Runs in DIA and Targeted Proteomics. Mol. Cell Proteomics. 2019; 18: 806-817 [OpenAIRE] [PubMed]

Piening, B.D., Zhou, W., Contrepois, K., Röst, H., Gu Urban, G.J., Mishra, T., Hanson, B.M., Bautista, E.J., Leopold, S., Yeh, C.Y., Spakowicz, D., Banerjee, I., Chen, C., Kukurba, K., Perelman, D., Craig, C., Colbert, E., Salins, D., Rego, S., Lee, S., Zhang, C., Wheeler, J., Sailani, M.R., Liang, L., Abbott, C., Gerstein, M., Mardinoglu, A., Smith, U., Rubin, D.L., Pitteri, S., Sodergren, E., McLaughlin, T.L., Weinstock, G.M., Snyder, M.P.. Integrative personal omics profiles during periods of weight gain and loss. Cell Syst.. 2018; 6: 157-170 [OpenAIRE] [PubMed]

26 references, page 1 of 2
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