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Professor Olga Vitek has a deep understanding of statistics, machine learning, and computational biology. She puts her know-how to work to develop computational tools enabling high-quality proteomic analysis and systems biology approaches. She hopes to apply these tools to the quantitative analysis of large-scale mass spectrometry-based investigations and thereby advance our understanding of organismal function. In this episode, Parag and Professor Vitek discuss:
- Why statistics is important for experimental design
- How statistics and AI can help researchers understand biology
- Gaps keeping us from using AI and statistics to their maximum potential in biology
Resources
Statistical methods for studies of biomolecular systems website
- Olga’s personal lab website
- Gyori and Vitek, 2024 discuss how AI can be used to interpret proteomics data and its biological meaning.
A Bayesian Active Learning Experimental Design for Inferring Signaling Networks
- Ness et al., 2018 show how statistical methods can guide the selection of experiments that optimally enhance understanding
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