Artificial intelligence in proteomics

In recent years the increasing analytical capabilities of mass spectrometry has demonstrated the power to generate huge amounts of data, but the spectra are complex, often containing fragments from multiple co-isolated peptides. In order to deeply mine these proteomic data sets and confidently maximise the number of peptide-spectrum matches (PSMs), new approaches utilising artificial intelligence are needed. The CHIMERYS™ search engine allows for a more complete analysis of both new and existing proteomics data sets by uncovering more unique peptide identifications, improving protein coverage and quantitation capabilities. This enhancement enables more efficient data acquisition schemes for increased sample throughput and instrument utilization.

Presentations:

Deep learning boosts sensitivity of mass spectrometry-based immunopeptidomics

• Presenter: Prof. Dr. Mathias Wilhelm, Computational Mass Spectrometry, Technical University of Munich, Germany

CHIMERYS® - An AI-driven leap forward in peptide identification

• Presenter: Dr. Martin Frejno, Co-Founder, CEO, MSAID GmbH, Garching/Muinch, Germany

TBC

• Presenter: Karl Mechtler, Head of Protein Chemistry Facility, Research Institute of Molecular Pathology, Austria

Learning points:

• Latest advances in proteomics data analysis
• Latest advances in proteomics mass spectrometry
• Optimising strategies to maximise research performance with confidence

Who should attend:

• Researchers in proteomics labs
• Researchers in structural biology labs
• Laboratory directors, managers and technicians interested in state-of-the-art protein analysis

Presenter: Prof. Dr. Mathias Wilhelm (Computational Mass Spectrometry, Technical University of Munich)

Mathias Wilhelmstudied bioinformatics (B.Sc.) and informatics in the natural sciences (M.Sc.) at the University Bielefeld. After an employment at the Harvard Medical School in the Children’s Hospital Boston inthe group of Dr. Hanno Steen, he started his PhD in computational proteomics at theTechnical Univeristy of Munich. In 2017, he became the bioinformatics group leader at theChair of Proteomics and Bioanalytics. Today,heleadsthe group for Computational Mass Spectrometry in Freisingat the Technical Univeristy of Munich.They investigate how mass spectrometric data can be better understood, made usable for the broad scientific community and how findings from it can be translated into research and clinical practice. To this end, they developplatforms and toolsfor scientists to evaluate, analyze and interpret their own data in an integrative manner. For this, they uses state-of-the-art methods from computer science, such asin-memory databases (e.g.ProteomicsDB) andneural networks (e.g. Prosit).

Presenter: Dr. Martin Frejno (Co-Founder, CEO, MSAID GmbH, Garching /Muinch, Germany)

Martin obtained his DPhil in Oncology in the group of Prof. Stefan Knapp at the University of Oxford in collaboration with Prof. Bernhard Kuster at the Technical University of Munich in Germany. During his studies, he focused on the pharmacoproteomic characterization of human colon and rectal cancer and subsequently broadened the scope of his research to bioinformatics and the large-scale characterization of cell line phosphoproteomes during a PostDoc in Prof. Bernhard Kuster’s laboratory. Together with colleagues from the Kuster lab, Martin incorporated MSAID with the goal of aiding mass spectrometry-based proteomics with artificial intelligence. As MSAID’s managing director, Martin will talk about how innovative software leveraging artificial intelligence can solve the long-standing problem of chimeric spectra in mass spectrometry-based proteomics.

Presenter: Karl Mechtler (Head of Protein Chemistry Facility, Research Institute of Molecular Pathology)

Karl Mechtler established one of the first Proteomics Core Facility in Austria in 2000, which is embedded in the Campus Vienna Biocenter and available to scientists from the Research Institute of Molecular Pathology (IMP), the Institute of Molecular Biotechnology (IMBA), and the Gregor Mendel Institute (GMI) today. He is developing methods for the analysis of protein post-translational modifications (phosphorylated arginine, glycoproteomics), algorithms for qualitative and quantitative MS data analysis that are increasingly used by proteomics labs worldwide. He is the co-author of more than 180 publications including contributions in Nature, Cell, and Science. The main research areas cover Proteomics, Mass Spectrometry, and Bioinformatics with specialization PTMs, cross-linking MS, single-cell proteomics, protein identification and quantification, etc.