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on resistance mechanisms in breast cancer, glioblastomas, colon cancer, and lung cancer. Advancing precision oncology through machine-learning models: We integrate multimodal patient data, including multiomic
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Medicine, and member of the City of Hope Comprehensive Cancer. The Perry laboratory uses structural biology approaches, together with small molecule and fragment-based drug discovery, computer-aided drug
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. The research program embraces team science drawing from i.e., implementation science, data science, geospatial, epidemiological, and machine learning approaches to better understand broad contexts including
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applying interpretable AI / machine learning / deep learning / information-theoretic methods and algorithms in the context of multiscale biological networks, ranging from molecules (protein chemistry) to
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candidate, you will: Develop and apply Bayesian Network machine learning methods to analyze the dynamics of G-protein coupled receptors to uncover allosteric regulation that enables design of allosteric
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of extension for at least 3 years. The research program embraces team science drawing from i.e., implementation science, data science, geospatial, epidemiological, and machine learning approaches to better