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Imaging-Omic correlation studies utilizing CPTAC data (September 9, 2019)
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<iframe src="https://player.vimeo.com/video/359314175" width="640" height="400" frameborder="0" allow="autoplay; fullscreen" allowfullscreen></iframe> |
Agenda & Slides
1) Dr. Olivier Gevaert is an assistant professor at Stanford University focused on developing machine-learning methods for biomedical decision support from multi-scale data. His lab lab develops machine learning methods including Bayesian, kernel methods, regularized regression and deep learning to integrate, clinical, molecular and biomedical image data. His presentation will show an example of how to process proteomic data from CPTAC Phase 2 projects (breast, ovarian and colorectal) with emphasis on how to use, preprocess and subsequently model proteomic data using bioinformatics algorithms. He will show an example of linking protein data to DNA methylation and mRNA gene expression data, and how proteomic data can be integrated with medical image data. (Download the slides)
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