Interdisciplinary Application of Data Science, lessons learned from protein engineering, drug Discovery, and pathology

Date

Aug 6, 2024

Time

1:00 PM - 3:00 PM

Speaker

Dennis Della Corte

Affiliation

Physics and Astronomy Department, Brigham Young University

Series

TUD nanoSeminar

Language

en

Main Topic

Physik

Other Topics

Physik

Host

Arezoo Dianat

Description

This presentation highlights interdisciplinary applications of data science methods across protein engineering, drug discovery, and pathology. Case studies from protein design will show how computational modeling accelerates the design-build-test cycle. Examples from drug discovery will illustrate using machine learning to extract insights from chemical and biological data to streamline therapy development. Applications to pathology datasets will demonstrate how data integration and deep learning enable enhanced disease diagnosis and biomarker discovery. Common principles and challenges in applying data science will be discussed, providing perspectives into how data science drives scientific innovation in diverse fields.
 
 Relevant References
 A probabilistic view of protein stability, conformational specificity, and design., Stern JA, Free TJ, Stern KL, Gardiner S, Dalley NA, Bundy BC, Price JL, Wingate D, Della Corte D. Nature Scientific Reports, 2023 
 
 TrIP─Transformer Interatomic Potential Predicts Realistic Energy Surface Using Physical Bias, Bryce E. Hedelius, Damon Tingey, and Dennis Della Corte, Journal of Chemical Theory and Computation, 2024 
 MILCDock: Machine Learning Enhanced Consensus Docking for Virtual Screening in Drug Discovery, Connor J. Morris, Jacob A. Stern, Brenden Stark, Max Christopherson, and Dennis Della Corte, Journal of Chemical Information and Modeling, 2022
 Don't fear the artificial intelligence: a systematic review of machine learning for prostate cancer detection in pathology, Frewing, A., Gibson, A. B., Robertson, R., Urie, P. M., & Della Corte, D., Archives of Pathology & Laboratory Medicine, 2024

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Last modified: Aug 7, 2024, 7:38:15 AM