• S. Aiche, T. Sachsenberg, E. Kenar, M. Walzer, B. Wiswedel, T. Kristl, M. Boyles, A. Duschl, C. G. Huber, M. R. Berthold, and others, “Workflows for automated downstream data analysis and visualization in large-scale computational mass spectrometry,” Proteomics, vol. 15, iss. 8, p. 1443–1447, 2015.
    [Bibtex]
    @article{aiche2015workflows,
    title={Workflows for automated downstream data analysis and visualization in large-scale computational mass spectrometry},
    author={Aiche, Stephan and Sachsenberg, Timo and Kenar, Erhan and Walzer, Mathias and Wiswedel, Bernd and Kristl, Theresa and Boyles, Matthew and Duschl, Albert and Huber, Christian G and Berthold, Michael R and others},
    journal={Proteomics},
    volume={15},
    number={8},
    pages={1443--1447},
    year={2015}
    }
  • F. Aicheler, J. Li, M. Hoene, R. Lehmann, G. Xu, and O. Kohlbacher, “Retention Time Prediction Improves Identification in Nontargeted Lipidomics Approaches,” Analytical chemistry, vol. 87, iss. 15, p. 7698–7704, 2015.
    [Bibtex]
    @article{aicheler2015retention,
    title={Retention Time Prediction Improves Identification in Nontargeted Lipidomics Approaches},
    author={Aicheler, Fabian and Li, Jia and Hoene, Miriam and Lehmann, Rainer and Xu, Guowang and Kohlbacher, Oliver},
    journal={Analytical chemistry},
    volume={87},
    number={15},
    pages={7698--7704},
    year={2015},
    publisher={American Chemical Society}
    }
  • C. Ranninger, M. Rurik, A. Limonciel, S. Ruzek, R. Reischl, A. Wilmes, P. Jennings, P. Hewitt, W. Dekant, O. Kohlbacher, and others, “Nephron Toxicity Profiling via Untargeted Metabolome Analysis Employing a High Performance Liquid Chromatography-Mass Spectrometry-based Experimental and Computational Pipeline,” Journal of Biological Chemistry, vol. 290, iss. 31, p. 19121–19132, 2015.
    [Bibtex]
    @article{ranninger2015nephron,
    title={Nephron Toxicity Profiling via Untargeted Metabolome Analysis Employing a High Performance Liquid Chromatography-Mass Spectrometry-based Experimental and Computational Pipeline},
    author={Ranninger, Christina and Rurik, Marc and Limonciel, Alice and Ruzek, Silke and Reischl, Roland and Wilmes, Anja and Jennings, Paul and Hewitt, Philip and Dekant, Wolfgang and Kohlbacher, Oliver and others},
    journal={Journal of Biological Chemistry},
    volume={290},
    number={31},
    pages={19121--19132},
    year={2015},
    publisher={ASBMB}
    }
  • H. L. Röst, U. Schmitt, R. Aebersold, and L. Malmström, “Fast and efficient XML data access for next-generation mass spectrometry,” PloS one, vol. 10, iss. 4, p. e0125108, 2015.
    [Bibtex]
    @article{rost2015fast,
    title={Fast and efficient XML data access for next-generation mass spectrometry},
    author={R{\"o}st, Hannes L and Schmitt, Uwe and Aebersold, Ruedi and Malmstr{\"o}m, Lars},
    journal={PloS one},
    volume={10},
    number={4},
    pages={e0125108},
    year={2015},
    publisher={Public Library of Science}
    }
  • H. L. Röst, G. Rosenberger, R. Aebersold, and L. Malmström, “Efficient visualization of high-throughput targeted proteomics experiments: TAPIR,” Bioinformatics, p. btv152, 2015.
    [Bibtex]
    @article{rost2015efficient,
    title={Efficient visualization of high-throughput targeted proteomics experiments: TAPIR},
    author={R{\"o}st, Hannes L and Rosenberger, George and Aebersold, Ruedi and Malmstr{\"o}m, Lars},
    journal={Bioinformatics},
    pages={btv152},
    year={2015},
    publisher={Oxford Univ Press}
    }
  • L. Nilse, F. C. Sigloch, M. L. Biniossek, and O. Schilling, “Toward improved peptide feature detection in quantitative proteomics using stable isotope labeling,” PROTEOMICS-Clinical Applications, vol. 9, iss. 7-8, p. 706–714, 2015.
    [Bibtex]
    @article{nilse2015toward,
    title={Toward improved peptide feature detection in quantitative proteomics using stable isotope labeling},
    author={Nilse, Lars and Sigloch, Florian Christoph and Biniossek, Martin L and Schilling, Oliver},
    journal={PROTEOMICS-Clinical Applications},
    volume={9},
    number={7-8},
    pages={706--714},
    year={2015}
    }
  • H. L. Röst, G. Rosenberger, P. Navarro, L. Gillet, S. M. Miladinović, O. T. Schubert, W. Wolski, B. C. Collins, J. Malmström, L. Malmström, and others, “OpenSWATH enables automated, targeted analysis of data-independent acquisition MS data,” Nature biotechnology, vol. 32, iss. 3, p. 219–223, 2014.
    [Bibtex]
    @article{rost2014openswath,
    title={OpenSWATH enables automated, targeted analysis of data-independent acquisition MS data},
    author={R{\"o}st, Hannes L and Rosenberger, George and Navarro, Pedro and Gillet, Ludovic and Miladinovi{\'c}, Sa{\v{s}}a M and Schubert, Olga T and Wolski, Witold and Collins, Ben C and Malmstr{\"o}m, Johan and Malmstr{\"o}m, Lars and others},
    journal={Nature biotechnology},
    volume={32},
    number={3},
    pages={219--223},
    year={2014},
    publisher={Nature Publishing Group}
    }
  • H. L. Röst, U. Schmitt, R. Aebersold, and L. Malmström, “pyOpenMS: A Python-based interface to the OpenMS mass-spectrometry algorithm library,” Proteomics, vol. 14, iss. 1, p. 74–77, 2014.
    [Bibtex]
    @article{rost2014pyopenms,
    title={pyOpenMS: A Python-based interface to the OpenMS mass-spectrometry algorithm library},
    author={R{\"o}st, Hannes L and Schmitt, Uwe and Aebersold, Ruedi and Malmstr{\"o}m, Lars},
    journal={Proteomics},
    volume={14},
    number={1},
    pages={74--77},
    year={2014},
    publisher={Wiley Online Library}
    }
  • E. Kenar, H. Franken, S. Forcisi, K. Wörmann, H. Häring, R. Lehmann, P. Schmitt-Kopplin, A. Zell, and O. Kohlbacher, “Automated Label-free Quantification of Metabolites from Liquid Chromatography–Mass Spectrometry Data,” Molecular & Cellular Proteomics, vol. 13, iss. 1, p. 348–359, 2014.
    [Bibtex]
    @article{kenar2014automated,
    title={Automated Label-free Quantification of Metabolites from Liquid Chromatography--Mass Spectrometry Data},
    author={Kenar, Erhan and Franken, Holger and Forcisi, Sara and W{\"o}rmann, Kilian and H{\"a}ring, Hans-Ulrich and Lehmann, Rainer and Schmitt-Kopplin, Philippe and Zell, Andreas and Kohlbacher, Oliver},
    journal={Molecular \& Cellular Proteomics},
    volume={13},
    number={1},
    pages={348--359},
    year={2014},
    publisher={ASBMB}
    }
  • T. Sachsenberg, F. Herbst, M. Taubert, R. Kermer, N. Jehmlich, M. von Bergen, J. Seifert, and O. Kohlbacher, “MetaProSIP: automated inference of stable isotope incorporation rates in proteins for functional metaproteomics,” Journal of proteome research, vol. 14, iss. 2, p. 619–627, 2014.
    [Bibtex]
    @article{sachsenberg2014metaprosip,
    title={MetaProSIP: automated inference of stable isotope incorporation rates in proteins for functional metaproteomics},
    author={Sachsenberg, Timo and Herbst, Florian-Alexander and Taubert, Martin and Kermer, Ren{\'e} and Jehmlich, Nico and von Bergen, Martin and Seifert, Jana and Kohlbacher, Oliver},
    journal={Journal of proteome research},
    volume={14},
    number={2},
    pages={619--627},
    year={2014},
    publisher={American Chemical Society}
    }
  • K. Kramer, T. Sachsenberg, B. M. Beckmann, S. Qamar, K. Boon, M. W. Hentze, O. Kohlbacher, and H. Urlaub, “Photo-cross-linking and high-resolution mass spectrometry for assignment of RNA-binding sites in RNA-binding proteins,” Nature methods, vol. 11, iss. 10, p. 1064–1070, 2014.
    [Bibtex]
    @article{kramer2014photo,
    title={Photo-cross-linking and high-resolution mass spectrometry for assignment of RNA-binding sites in RNA-binding proteins},
    author={Kramer, Katharina and Sachsenberg, Timo and Beckmann, Benedikt M and Qamar, Saadia and Boon, Kum-Loong and Hentze, Matthias W and Kohlbacher, Oliver and Urlaub, Henning},
    journal={Nature methods},
    volume={11},
    number={10},
    pages={1064--1070},
    year={2014},
    publisher={Nature Publishing Group}
    }
  • J. Griss, A. R. Jones, T. Sachsenberg, M. Walzer, L. Gatto, J. Hartler, G. G. Thallinger, R. M. Salek, C. Steinbeck, N. Neuhauser, and others, “The mzTab data exchange format: communicating mass-spectrometry-based proteomics and metabolomics experimental results to a wider audience,” Molecular & Cellular Proteomics, vol. 13, iss. 10, p. 2765–2775, 2014.
    [Bibtex]
    @article{griss2014mztab,
    title={The mzTab data exchange format: communicating mass-spectrometry-based proteomics and metabolomics experimental results to a wider audience},
    author={Griss, Johannes and Jones, Andrew R and Sachsenberg, Timo and Walzer, Mathias and Gatto, Laurent and Hartler, J{\"u}rgen and Thallinger, Gerhard G and Salek, Reza M and Steinbeck, Christoph and Neuhauser, Nadin and others},
    journal={Molecular \& Cellular Proteomics},
    volume={13},
    number={10},
    pages={2765--2775},
    year={2014},
    publisher={ASBMB}
    }
  • M. Walzer, L. E. Pernas, S. Nasso, W. Bittremieux, S. Nahnsen, P. Kelchtermans, P. Pichler, H. W. van den Toorn, A. Staes, J. Vandenbussche, and others, “qcML: an exchange format for quality control metrics from mass spectrometry experiments,” Molecular & Cellular Proteomics, vol. 13, iss. 8, p. 1905–1913, 2014.
    [Bibtex]
    @article{walzer2014qcml,
    title={qcML: an exchange format for quality control metrics from mass spectrometry experiments},
    author={Walzer, Mathias and Pernas, Lucia Espona and Nasso, Sara and Bittremieux, Wout and Nahnsen, Sven and Kelchtermans, Pieter and Pichler, Peter and van den Toorn, Henk WP and Staes, An and Vandenbussche, Jonathan and others},
    journal={Molecular \& Cellular Proteomics},
    volume={13},
    number={8},
    pages={1905--1913},
    year={2014},
    publisher={American Society for Biochemistry and Molecular Biology}
    }
  • H. Weisser, S. Nahnsen, J. Grossmann, L. Nilse, A. Quandt, H. Brauer, M. Sturm, E. Kenar, O. Kohlbacher, R. Aebersold, and others, “An automated pipeline for high-throughput label-free quantitative proteomics,” Journal of proteome research, vol. 12, iss. 4, p. 1628–1644, 2013.
    [Bibtex]
    @article{weisser2013automated,
    title={An automated pipeline for high-throughput label-free quantitative proteomics},
    author={Weisser, Hendrik and Nahnsen, Sven and Grossmann, Jonas and Nilse, Lars and Quandt, Andreas and Brauer, Hendrik and Sturm, Marc and Kenar, Erhan and Kohlbacher, Oliver and Aebersold, Ruedi and others},
    journal={Journal of proteome research},
    volume={12},
    number={4},
    pages={1628--1644},
    year={2013},
    publisher={ACS Publications}
    }
  • M. Walzer, D. Qi, G. Mayer, J. Uszkoreit, M. Eisenacher, T. Sachsenberg, F. F. Gonzalez-Galarza, J. Fan, C. Bessant, E. W. Deutsch, and others, “The mzQuantML Data Standard for Mass Spectrometry–based Quantitative Studies in Proteomics,” Molecular & Cellular Proteomics, vol. 12, iss. 8, p. 2332–2340, 2013.
    [Bibtex]
    @article{walzer2013mzquantml,
    title={The mzQuantML Data Standard for Mass Spectrometry--based Quantitative Studies in Proteomics},
    author={Walzer, Mathias and Qi, Da and Mayer, Gerhard and Uszkoreit, Julian and Eisenacher, Martin and Sachsenberg, Timo and Gonzalez-Galarza, Faviel F and Fan, Jun and Bessant, Conrad and Deutsch, Eric W and others},
    journal={Molecular \& Cellular Proteomics},
    volume={12},
    number={8},
    pages={2332--2340},
    year={2013},
    publisher={ASBMB}
    }
  • J. Junker, C. Bielow, A. Bertsch, M. Sturm, K. Reinert, and O. Kohlbacher, “TOPPAS: a graphical workflow editor for the analysis of high-throughput proteomics data,” Journal of proteome research, vol. 11, iss. 7, p. 3914–3920, 2012.
    [Bibtex]
    @article{junker2012toppas,
    title={TOPPAS: a graphical workflow editor for the analysis of high-throughput proteomics data},
    author={Junker, Johannes and Bielow, Chris and Bertsch, Andreas and Sturm, Marc and Reinert, Knut and Kohlbacher, Oliver},
    journal={Journal of proteome research},
    volume={11},
    number={7},
    pages={3914--3920},
    year={2012},
    publisher={ACS Publications}
    }
  • S. Nahnsen and O. Kohlbacher, “In silico design of targeted SRM-based experiments,” BMC bioinformatics, vol. 13, iss. Suppl 16, p. S8, 2012.
    [Bibtex]
    @article{nahnsen2012silico,
    title={In silico design of targeted SRM-based experiments},
    author={Nahnsen, Sven and Kohlbacher, Oliver},
    journal={BMC bioinformatics},
    volume={13},
    number={Suppl 16},
    pages={S8},
    year={2012},
    publisher={BioMed Central Ltd}
    }
  • A. Bertsch, C. Gröpl, K. Reinert, and O. Kohlbacher, “OpenMS and TOPP: open source software for LC-MS data analysis,” Data Mining in Proteomics: From Standards to Applications, p. 353–367, 2011.
    [Bibtex]
    @article{bertsch2011openms,
    title={OpenMS and TOPP: open source software for LC-MS data analysis},
    author={Bertsch, Andreas and Gr{\"o}pl, Clemens and Reinert, Knut and Kohlbacher, Oliver},
    journal={Data Mining in Proteomics: From Standards to Applications},
    pages={353--367},
    year={2011},
    publisher={Humana Press}
    }
  • S. Nahnsen, A. Bertsch, J. Rahnenführer, A. Nordheim, and O. Kohlbacher, “Probabilistic consensus scoring improves tandem mass spectrometry peptide identification,” Journal of proteome research, vol. 10, iss. 8, p. 3332–3343, 2011.
    [Bibtex]
    @article{nahnsen2011probabilistic,
    title={Probabilistic consensus scoring improves tandem mass spectrometry peptide identification},
    author={Nahnsen, Sven and Bertsch, Andreas and Rahnenführer, Jörg and Nordheim, Alfred and Kohlbacher, Oliver},
    journal={Journal of proteome research},
    volume={10},
    number={8},
    pages={3332--3343},
    year={2011},
    publisher={ACS Publications}
    }
  • C. Bielow, S. Aiche, S. Andreotti, and K. Reinert, “MSSimulator: Simulation of mass spectrometry data,” Journal of proteome research, vol. 10, iss. 7, p. 2922–2929, 2011.
    [Bibtex]
    @article{bielow2011mssimulator,
    title={MSSimulator: Simulation of mass spectrometry data},
    author={Bielow, Chris and Aiche, Stephan and Andreotti, Sandro and Reinert, Knut},
    journal={Journal of proteome research},
    volume={10},
    number={7},
    pages={2922--2929},
    year={2011},
    publisher={ACS Publications}
    }
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