"AI in Proteomics"
AI is these days supporting most layers of proteomics workflows: signal processing, identification, classification, correlation and 3D structure prediction and we would like you to cover the following topic of classification, biomarkers and multi-omics with AI.
Speakers:
- Ornella Cominetti Allende (Nestlé)
- Mathias Wilhelm (TUM)
- An-Phi Nguyen (Biognosys)
The format will be ~20 minutes presentation followed by a panel discussion with 2 other spe
Upon registration you can attend an extra workshop on Friday 16th of May at 8:00 am until 9:30 am.
IMPORTANT: Please click the corresponding option during registration and add a short text explaining your interest to attend.
About our guests
Ornella Cominetti Allende (Nestlé)
Ornella Cominetti is a Senior Omics Data Specialist at the Nestlé Institute of Food Safety & Analytical Sciences of Nestlé Research, focusing on leveraging multi-omics data with a focus on proteomics for nutrition and health research. She obtained her doctorate from the Department of Mathematics of the University of Oxford.
Mathias Wilhelm (Technical University of Munich)
Mathias Wilhelm studied 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 in the group of Dr. Hanno Steen, he started his PhD in computational proteomics at the TUM. His dissertation was on "An in-memory platform for the exploration and analysis of big data in biology" - now known as ProteomicsDB. In 2017, he became the bioinformatics group leader at the Chair of Proteomics and Bioanalytics. In 2021, Mathias Wilhelm was appointed to the professorship for Computational Mass Spectrometry at TUM. He is a co-founder of the biotech companies OmicScouts GmbH (now a subsidiary of Momentum Biotechnologies) and MSAID GmbH, both opperating in the field of proteomics.
An-Phi Nguyen (Biognosys AG)
An-phi Nguyen obtained his Bachelor’s Degree in Applied Math at the Politecnico di Milano, and his Master’s Degree in Computational Sciences at ETH Zurich. During his PhD studies at IBM Research Zurich and ETH Zurich, he focused on interpretability for deep learning models, i.e. techniques to inspect and explain the decision process of AI models. Example applications include generating explanations for a model for T-cell receptor binding prediction, or for an automated clinical triage model. Currently, he is co-leading the AI team at Biognosys to boost LC-MS data analysis pipelines with AI capabilities.
