• R. Starke, K. Oliphant, N. Jehmlich, S. S. Schäpe, T. Sachsenberg, O. Kohlbacher, E. Allen-Vercoe, and M. von Bergen, “Tracing incorporation of heavy water into proteins for species-specific metabolic activity in complex communities,” Journal of Proteomics, p. 103791, 2020.
    [Bibtex]
    @article{starke2020tracing,
    title={Tracing incorporation of heavy water into proteins for species-specific metabolic activity in complex communities},
    author={Starke, Robert and Oliphant, Kaitlyn and Jehmlich, Nico and Sch{\"a}pe, Stephanie Serena and Sachsenberg, Timo and Kohlbacher, Oliver and Allen-Vercoe, Emma and von Bergen, Martin},
    journal={Journal of Proteomics},
    pages={103791},
    year={2020},
    publisher={Elsevier}
    }
  • O. Alka, T. Sachsenberg, L. Bichmann, J. Pfeuffer, H. Weisser, S. Wein, E. Netz, M. Rurik, O. Kohlbacher, and H. Röst, “OpenMS and KNIME for Mass Spectrometry Data Processing,” in Processing Metabolomics and Proteomics Data with Open Software, , 2020, p. 201–231.
    [Bibtex]
    @incollection{alka2020openms,
    title={OpenMS and KNIME for Mass Spectrometry Data Processing},
    author={Alka, Oliver and Sachsenberg, Timo and Bichmann, Leon and Pfeuffer, Julianus and Weisser, Hendrik and Wein, Samuel and Netz, Eugen and Rurik, Marc and Kohlbacher, Oliver and R{\"o}st, Hannes},
    booktitle={Processing Metabolomics and Proteomics Data with Open Software},
    pages={201--231},
    year={2020}
    }
  • S. Wein, B. Andrews, T. Sachsenberg, H. Santos-Rosa, O. Kohlbacher, T. Kouzarides, B. A. Garcia, and H. Weisser, “A computational platform for high-throughput analysis of RNA sequences and modifications by mass spectrometry,” Nature communications, vol. 11, iss. 1, p. 1–12, 2020.
    [Bibtex]
    @article{wein2020computational,
    title={A computational platform for high-throughput analysis of RNA sequences and modifications by mass spectrometry},
    author={Wein, Samuel and Andrews, Byron and Sachsenberg, Timo and Santos-Rosa, Helena and Kohlbacher, Oliver and Kouzarides, Tony and Garcia, Benjamin A and Weisser, Hendrik},
    journal={Nature communications},
    volume={11},
    number={1},
    pages={1--12},
    year={2020},
    publisher={Nature Publishing Group}
    }
  • M. Rurik, O. Alka, F. Aicheler, and O. Kohlbacher, “Metabolomics Data Processing Using OpenMS,” in Computational Methods and Data Analysis for Metabolomics, Springer, 2020, p. 49–60.
    [Bibtex]
    @incollection{rurik2020metabolomics,
    title={Metabolomics Data Processing Using OpenMS},
    author={Rurik, Marc and Alka, Oliver and Aicheler, Fabian and Kohlbacher, Oliver},
    booktitle={Computational Methods and Data Analysis for Metabolomics},
    pages={49--60},
    year={2020},
    publisher={Springer}
    }
  • K. Jeong, J. Kim, M. Gaikwad, S. N. Hidayah, L. Heikaus, H. Schlüter, and O. Kohlbacher, “FLASHDeconv: Ultrafast, high-quality feature deconvolution for top-down proteomics,” Cell Systems, vol. 10, iss. 2, p. 213–218, 2020.
    [Bibtex]
    @article{jeong2020flashdeconv,
    title={FLASHDeconv: Ultrafast, high-quality feature deconvolution for top-down proteomics},
    author={Jeong, Kyowon and Kim, Jihyung and Gaikwad, Manasi and Hidayah, Siti Nurul and Heikaus, Laura and Schl{\"u}ter, Hartmut and Kohlbacher, Oliver},
    journal={Cell Systems},
    volume={10},
    number={2},
    pages={213--218},
    year={2020},
    publisher={Elsevier}
    }
  • J. Pfeuffer, T. Sachsenberg, T. M. Dijkstra, O. Serang, K. Reinert, and O. Kohlbacher, “EPIFANY-A method for efficient high-confidence protein inference,” Journal of proteome research, p. 734327, 2019.
    [Bibtex]
    @article{pfeuffer2019epifany,
    title={EPIFANY-A method for efficient high-confidence protein inference},
    author={Pfeuffer, Julianus and Sachsenberg, Timo and Dijkstra, Tjeerd MH and Serang, Oliver and Reinert, Knut and Kohlbacher, Oliver},
    journal={Journal of proteome research},
    pages={734327},
    year={2019},
    publisher={Cold Spring Harbor Laboratory}
    }
  • N. Hulstaert, J. Shofstahl, T. Sachsenberg, M. Walzer, H. Barsnes, L. Martens, and Y. Perez-Riverol, “ThermoRawFileParser: Modular, Scalable, and Cross-Platform RAW File Conversion,” Journal of proteome research, vol. 19, iss. 1, p. 537–542, 2019.
    [Bibtex]
    @article{hulstaert2019thermorawfileparser,
    title={ThermoRawFileParser: Modular, Scalable, and Cross-Platform RAW File Conversion},
    author={Hulstaert, Niels and Shofstahl, Jim and Sachsenberg, Timo and Walzer, Mathias and Barsnes, Harald and Martens, Lennart and Perez-Riverol, Yasset},
    journal={Journal of proteome research},
    volume={19},
    number={1},
    pages={537--542},
    year={2019},
    publisher={ACS Publications}
    }
  • L. Bichmann, A. Nelde, M. Ghosh, L. Heumos, C. Mohr, A. Peltzer, L. Kuchenbecker, T. Sachsenberg, J. S. Walz, S. Stevanović, and others, “MHCquant: Automated and reproducible data analysis for immunopeptidomics,” Journal of proteome research, vol. 18, iss. 11, p. 3876–3884, 2019.
    [Bibtex]
    @article{bichmann2019mhcquant,
    title={MHCquant: Automated and reproducible data analysis for immunopeptidomics},
    author={Bichmann, Leon and Nelde, Annika and Ghosh, Michael and Heumos, Lukas and Mohr, Christopher and Peltzer, Alexander and Kuchenbecker, Leon and Sachsenberg, Timo and Walz, Juliane S and Stevanović, Stefan and others},
    journal={Journal of proteome research},
    volume={18},
    number={11},
    pages={3876--3884},
    year={2019},
    publisher={ACS Publications}
    }
  • M. W. Löffler, C. Mohr, L. Bichmann, L. K. Freudenmann, M. Walzer, C. M. Schroeder, N. Trautwein, F. J. Hilke, R. S. Zinser, L. Mühlenbruch, and others, “Multi-omics discovery of exome-derived neoantigens in hepatocellular carcinoma,” Genome medicine, vol. 11, iss. 1, p. 28, 2019.
    [Bibtex]
    @article{loffler2019multi,
    title={Multi-omics discovery of exome-derived neoantigens in hepatocellular carcinoma},
    author={L{\"o}ffler, Markus W and Mohr, Christopher and Bichmann, Leon and Freudenmann, Lena Katharina and Walzer, Mathias and Schroeder, Christopher M and Trautwein, Nico and Hilke, Franz J and Zinser, Raphael S and M{\"u}hlenbruch, Lena and others},
    journal={Genome medicine},
    volume={11},
    number={1},
    pages={28},
    year={2019},
    publisher={BioMed Central}
    }
  • A. Marcu, L. Bichmann, L. Kuchenbecker, L. Backert, D. J. Kowalewski, L. K. Freudenmann, M. W. Löffler, M. Lübke, J. S. Walz, J. Velz, and others, “The HLA Ligand Atlas. A resource of natural HLA ligands presented on benign tissues,” BioRxiv, p. 778944, 2019.
    [Bibtex]
    @article{marcu2019hla,
    title={The HLA Ligand Atlas. A resource of natural HLA ligands presented on benign tissues},
    author={Marcu, Ana and Bichmann, Leon and Kuchenbecker, Leon and Backert, Linus and Kowalewski, Daniel J and Freudenmann, Lena Katharina and L{\"o}ffler, Markus W and L{\"u}bke, Maren and Walz, Juliane S and Velz, Julia and others},
    journal={BioRxiv},
    pages={778944},
    year={2019},
    publisher={Cold Spring Harbor Laboratory}
    }
  • B. Gruening, O. Sallou, P. Moreno, F. da Veiga Leprevost, H. Ménager, D. S{o}ndergaard, H. Röst, T. Sachsenberg, B. O’Connor, F. Madeira, and others, “Recommendations for the packaging and containerizing of bioinformatics software,” F1000Research, vol. 7, 2018.
    [Bibtex]
    @article{gruening2018recommendations,
    title={Recommendations for the packaging and containerizing of bioinformatics software},
    author={Gruening, Bjorn and Sallou, Olivier and Moreno, Pablo and da Veiga Leprevost, Felipe and M{\'e}nager, Herv{\'e} and S{\o}ndergaard, Dan and R{\"o}st, Hannes and Sachsenberg, Timo and O'Connor, Brian and Madeira, F{\'a}bio and others},
    journal={F1000Research},
    volume={7},
    year={2018}
    }
  • A. Kahles, K. Lehmann, N. C. Toussaint, M. Hüser, S. G. Stark, T. Sachsenberg, O. Stegle, O. Kohlbacher, C. Sander, S. J. Caesar-Johnson, and others, “Comprehensive analysis of alternative splicing across tumors from 8,705 patients,” Cancer cell, vol. 34, iss. 2, p. 211–224, 2018.
    [Bibtex]
    @article{kahles2018comprehensive,
    title={Comprehensive analysis of alternative splicing across tumors from 8,705 patients},
    author={Kahles, Andr{\'e} and Lehmann, Kjong-Van and Toussaint, Nora C and H{\"u}ser, Matthias and Stark, Stefan G and Sachsenberg, Timo and Stegle, Oliver and Kohlbacher, Oliver and Sander, Chris and Caesar-Johnson, Samantha J and others},
    journal={Cancer cell},
    volume={34},
    number={2},
    pages={211--224},
    year={2018},
    publisher={Elsevier}
    }
  • J. A. Vizcaíno, G. Mayer, S. R. Perkins, H. Barsnes, M. Vaudel, Y. Perez-Riverol, T. Ternent, J. Uszkoreit, M. Eisenacher, L. Fischer, and others, “The mzIdentML data standard version 1.2, supporting advances in proteome informatics,” Molecular & Cellular Proteomics, p. mcp–M117, 2017.
    [Bibtex]
    @article{vizcaino2017mzidentml,
    title={The mzIdentML data standard version 1.2, supporting advances in proteome informatics},
    author={Vizca{\'i}no, Juan Antonio and Mayer, Gerhard and Perkins, Simon R and Barsnes, Harald and Vaudel, Marc and Perez-Riverol, Yasset and Ternent, Tobias and Uszkoreit, Julian and Eisenacher, Martin and Fischer, Lutz and others},
    journal={Molecular \& Cellular Proteomics},
    pages={mcp--M117},
    year={2017},
    publisher={ASBMB}
    }
  • E. Audain, J. Uszkoreit, T. Sachsenberg, J. Pfeuffer, X. Liang, H. Hermjakob, A. Sanchez, M. Eisenacher, K. Reinert, D. L. Tabb, and others, “In-depth analysis of protein inference algorithms using multiple search engines and well-defined metrics,” Journal of proteomics, vol. 150, p. 170–182, 2017.
    [Bibtex]
    @article{audain2017depth,
    title={In-depth analysis of protein inference algorithms using multiple search engines and well-defined metrics},
    author={Audain, Enrique and Uszkoreit, Julian and Sachsenberg, Timo and Pfeuffer, Julianus and Liang, Xiao and Hermjakob, Henning and Sanchez, Aniel and Eisenacher, Martin and Reinert, Knut and Tabb, David L and others},
    journal={Journal of proteomics},
    volume={150},
    pages={170--182},
    year={2017},
    publisher={Elsevier}
    }
  • H. L. Röst, R. Aebersold, and O. T. Schubert, “Automated SWATH data analysis using targeted extraction of ion chromatograms,” Proteomics: Methods and Protocols, p. 289–307, 2017.
    [Bibtex]
    @article{rost2017automated,
    title={Automated SWATH data analysis using targeted extraction of ion chromatograms},
    author={R{\"o}st, Hannes L and Aebersold, Ruedi and Schubert, Olga T},
    journal={Proteomics: Methods and Protocols},
    pages={289--307},
    year={2017},
    publisher={Springer New York}
    }
  • F. da Veiga Leprevost, B. A. Grüning, S. Alves Aflitos, H. L. Röst, J. Uszkoreit, H. Barsnes, M. Vaudel, P. Moreno, L. Gatto, J. Weber, and others, “BioContainers: an open-source and community-driven framework for software standardization,” Bioinformatics, p. btx192, 2017.
    [Bibtex]
    @article{da2017biocontainers,
    title={BioContainers: an open-source and community-driven framework for software standardization},
    author={da Veiga Leprevost, Felipe and Gr{\"u}ning, Bj{\"o}rn A and Alves Aflitos, Saulo and R{\"o}st, Hannes L and Uszkoreit, Julian and Barsnes, Harald and Vaudel, Marc and Moreno, Pablo and Gatto, Laurent and Weber, Jonas and others},
    journal={Bioinformatics},
    pages={btx192},
    year={2017},
    publisher={Oxford University Press}
    }
  • [DOI] H. Weisser and J. S. Choudhary, “Targeted feature detection for data-dependent shotgun proteomics,” Journal of Proteome Research, 2017.
    [Bibtex]
    @article{weisser2017targeted,
    title={Targeted feature detection for data-dependent shotgun proteomics},
    author={Weisser, Hendrik and Choudhary, Jyoti S},
    journal={Journal of Proteome Research},
    year={2017},
    publisher={ACS Publications},
    doi={10.1021/acs.jproteome.7b00248}
    }
  • [DOI] J. Pfeuffer, T. Sachsenberg, O. Alka, M. Walzer, A. Fillbrunn, L. Nilse, O. Schilling, K. Reinert, and O. Kohlbacher, “OpenMS – A platform for reproducible analysis of mass spectrometry data,” Journal of Biotechnology, 2017.
    [Bibtex]
    @article{pfeuffer2017denbi,
    title = "OpenMS – A platform for reproducible analysis of mass spectrometry data",
    journal = "Journal of Biotechnology",
    volume = "",
    number = "",
    pages = "",
    year = "2017",
    note = "",
    issn = "0168-1656",
    doi = "10.1016/j.jbiotec.2017.05.016",
    url = "http://www.sciencedirect.com/science/article/pii/S0168165617302511",
    author = "Julianus Pfeuffer and Timo Sachsenberg and Oliver Alka and Mathias Walzer and Alexander Fillbrunn and Lars Nilse and Oliver Schilling and Knut Reinert and Oliver Kohlbacher"
    }
  • H. L. Rost, T. Sachsenberg, S. Aiche, C. Bielow, H. Weisser, F. Aicheler, S. Andreotti, H. Ehrlich, P. Gutenbrunner, E. Kenar, X. Liang, S. Nahnsen, L. Nilse, J. Pfeuffer, G. Rosenberger, M. Rurik, U. Schmitt, J. Veit, M. Walzer, D. Wojnar, W. E. Wolski, O. Schilling, J. S. Choudhary, L. Malmstrom, R. Aebersold, K. Reinert, and O. Kohlbacher, “OpenMS: a flexible open-source software platform for mass spectrometry data analysis,” Nat Meth, vol. 13, iss. 9, pp. 741-748, 2016.
    [Bibtex]
    @article{Rost2016,
    author = {Rost, Hannes L and Sachsenberg, Timo and Aiche, Stephan and Bielow, Chris and Weisser, Hendrik and Aicheler, Fabian and Andreotti, Sandro and Ehrlich, Hans-Christian and Gutenbrunner, Petra and Kenar, Erhan and Liang, Xiao and Nahnsen, Sven and Nilse, Lars and Pfeuffer, Julianus and Rosenberger, George and Rurik, Marc and Schmitt, Uwe and Veit, Johannes and Walzer, Mathias and Wojnar, David and Wolski, Witold E and Schilling, Oliver and Choudhary, Jyoti S and Malmstrom, Lars and Aebersold, Ruedi and Reinert, Knut and Kohlbacher, Oliver},
    title = {OpenMS: a flexible open-source software platform for mass spectrometry data analysis},
    year = {2016},
    URL = {http://dx.doi.org/10.1038/nmeth.3959},
    abstract = {High-resolution mass spectrometry (MS) has become an important tool in the life sciences, contributing to the diagnosis and understanding of human diseases, elucidating biomolecular structural information and characterizing cellular signaling networks. However, the rapid growth in the volume and complexity of MS data makes transparent, accurate and reproducible analysis difficult. We present OpenMS 2.0 (http://www.openms.de), a robust, open-source, cross-platform software specifically designed for the flexible and reproducible analysis of high-throughput MS data. The extensible OpenMS software implements common mass spectrometric data processing tasks through a well-defined application programming interface in C++ and Python and through standardized open data formats. OpenMS additionally provides a set of 185 tools and ready-made workflows for common mass spectrometric data processing tasks, which enable users to perform complex quantitative mass spectrometric analyses with ease.},
    journal = {Nat Meth},
    volume = {13},
    number = {9},
    pages = {741-748},
    note = {Perspective}
    }
  • J. Veit, T. Sachsenberg, A. Chernev, F. Aicheler, H. Urlaub, and O. Kohlbacher, “LFQProfiler and RNPxl: Open-Source Tools for Label-Free Quantification and Protein–RNA Cross-Linking Integrated into Proteome Discoverer,” Journal of Proteome Research, vol. 15, iss. 9, p. 3441–3448, 2016.
    [Bibtex]
    @article{veit2016lfqprofiler,
    title={LFQProfiler and RNPxl: Open-Source Tools for Label-Free Quantification and Protein--RNA Cross-Linking Integrated into Proteome Discoverer},
    author={Veit, Johannes and Sachsenberg, Timo and Chernev, Aleksandar and Aicheler, Fabian and Urlaub, Henning and Kohlbacher, Oliver},
    journal={Journal of Proteome Research},
    volume={15},
    number={9},
    pages={3441--3448},
    year={2016},
    publisher={ACS Publications}
    }
  • P. Navarro, J. Kuharev, L. C. Gillet, O. M. Bernhardt, B. MacLean, H. L. Röst, S. A. Tate, C. Tsou, L. Reiter, U. Distler, and others, “A multi-center study benchmarks software tools for label-free proteome quantification,” Nature biotechnology, vol. 34, iss. 11, p. 1130, 2016.
    [Bibtex]
    @article{navarro2016multi,
    title={A multi-center study benchmarks software tools for label-free proteome quantification},
    author={Navarro, Pedro and Kuharev, J{\"o}rg and Gillet, Ludovic C and Bernhardt, Oliver M and MacLean, Brendan and R{\"o}st, Hannes L and Tate, Stephen A and Tsou, Chih-Chiang and Reiter, Lukas and Distler, Ute and others},
    journal={Nature biotechnology},
    volume={34},
    number={11},
    pages={1130},
    year={2016},
    publisher={Europe PMC Funders}
    }
  • [DOI] H. Weisser, J. C. Wright, J. M. Mudge, P. Gutenbrunner, and J. S. Choudhary, “Flexible Data Analysis Pipeline for High-Confidence Proteogenomics,” Journal of Proteome Research, vol. 15, iss. 12, p. 4686–4695, 2016.
    [Bibtex]
    @article{weisser2016flexible,
    title={Flexible Data Analysis Pipeline for High-Confidence Proteogenomics},
    author={Weisser, Hendrik and Wright, James C and Mudge, Jonathan M and Gutenbrunner, Petra and Choudhary, Jyoti S},
    journal={Journal of Proteome Research},
    volume={15},
    number={12},
    pages={4686--4695},
    year={2016},
    publisher={ACS Publications},
    doi={10.1021/acs.jproteome.6b00765}
    }
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