Lennart Martens

Further involvements

• Mon, Oct 21

  • Poster presentation
  • iP-20

  Expanding proteomics horizons through metadata

   Multiomics Approaches
• Tue, Oct 22

  • Poster presentation
  • P-II-0512

  Expanding proteomics horizons through metadata

   Multiomics Approaches
• Tue, Oct 22

  • Poster presentation
  • P-II-0545

  Precision through Networks: AI-driven Targeting of Protein-Protein Interactions in Lysosomal Storage Disorders

   Multiomics Approaches
• Tue, Oct 22

  • Poster presentation
  • P-II-0458

  IM2Deep predicts collisional cross-sections of modified and multiconformational peptide ions

   New Technology: AI and Bioinformatics in Mass Spectrometry
• Tue, Oct 22

  • Poster presentation
  • P-II-0494

  The benefit of in silico predicted spectral libraries in data-independent acquisition data analysis workflows

   New Technology: AI and Bioinformatics in Mass Spectrometry
• Tue, Oct 22

  • Poster presentation
  • P-II-0468

  TIMSrescore: timsTOF-optimized PSM rescoring boosts identification rates for immunopeptidomics

   New Technology: AI and Bioinformatics in Mass Spectrometry
• Tue, Oct 22

  • Poster presentation
  • P-II-0481

  Enhancing peptide-spectrum match identification: leveraging mokapot with nonlinear machine learning algorithms to increase PSMs, with consideration for false positives

   New Technology: AI and Bioinformatics in Mass Spectrometry
• Tue, Oct 22

  16:30 – 16:42 10 Min. 2 Min.

  • Oral presentation
  • OP-63

  MoDPA: investigating diseases through modification-dependent protein associations

   Data Integration: With Bioinformatics to Biological Knowledge
• Wed, Oct 23

  11:05 – 11:17 10 Min. 2 Min.

  • Oral presentation
  • OP-68

  PTMs and proteoforms shaping tissue proteomes

   Data Integration: With Bioinformatics to Biological Knowledge
• Wed, Oct 23

  • Poster presentation
  • P-III-0823

  AlphaFold3 and protein modifications: obvious strengths and significant challenges

   Data Integration: With Bioinformatics to Biological Knowledge
• Wed, Oct 23

  • Poster presentation
  • P-III-1100

  Fine tuning of ddaPASEF methods improves the immunopeptidomics coverage and throughput, which is further boosted by ML-assisted rescoring

   Immunopeptidomics