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Technical University of Munich

Daniela Klaproth-Andrade

Positions

2020 - presentPhD student in the Chair of Computational Molecular Medicine, TUM, Germany
2019 - 2020Master thesis in the Chair of Computational Molecular Medicine, TUM, Germany
2019 - 2020Tutor in "Data Analysis and Visualization in R", TUM, Germany
2018 - 2019Student position at ProSiebenSat1
2017Bachelor Thesis in the Chair of Discrete Mathematics, Optimization an Convexity, TUM, Germany
2016 - 2018Tutor in "Discrete Structures", TUM, Germany

Education

2017 - 2020M.Sc in Data Engineering & Analytics, TUM, Germany
2014 - 2017B.Sc in Computer Science, TUM, Germany

Publications

  • Gwenneth Straub, Varun Ananth, William E. Fondrie, Chris Hsu, Daniela Klaproth-Andrade, Michael Riffle, Justin Sanders, Bo Wen, Lingwen Xu, Melih Yilmaz, Michael J. MacCoss, Sewoong Oh, Wout Bittremieux, William Stafford Noble. Improvements to Casanovo, a deep learning de novo peptide sequencer. bioRxiv, 2025
  • Daniela Klaproth-Andrade, Yanik Bruns, Wassim Gabriel, Christian Nix, Valter Bergant, Andreas Pichlmair, Mathias Wilhelm, Julien Gagneur. Modanovo: A Unified Model for Post-Translational Modification-Aware de Novo Sequencing Using Experimental Spectra from in Vivo and Synthetic Peptides. bioRxiv, 2025
  • Daniela Klaproth-Andrade*, Ines Scheller*, Georgios Tsitsiridis, Stefan Loipfinger, Christian Mertes, Dmitrii Smirnov, Holger Prokisch, Vicente Yépez, Julien Gagneur. PROTRIDER: Protein abundance outlier detection from mass spectrometry-based proteomics data with a conditional autoencoder. bioRxiv, 2025
  • Daniela Klaproth-Andrade, Johannes Hingerl, Yanik Bruns, Nicholas H. Smith, Jakob Träuble, Mathias Wilhelm@, Julien Gagneur@. Deep learning-driven fragment ion series classification enables highly precise and sensitive de novo peptide sequencing. Nature Communications, 2024
  • Vicente A. Yépez, Christian Mertes, Michaela F. Müller, Daniela S. Andrade, Leonhard Wachutka, Laure Frésard, Mirjana Gusic, Ines Scheller, Patricia F. Goldberg, Holger Prokisch, Julien Gagneur. Detection of aberrant events in RNA-seq data. Nature Protocols, 2021
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