Anant Madabhushi, PhD

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When: Friday, December 6th, 2024, 10am-11am EST

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Title:  Sequence-based deep learning models for understanding gene regulation and disease genetics

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Abstract: 

Traditional biology generally looks at only a few aspects of an organism at a time and

attempts to molecularly dissect diseases and study them part by part with the hope that the sum of knowledge of parts would help explain the operation of the whole. Rarely has this been a successful strategy to understand the causes and cures for complex diseases. The motivation

for a systems based approach to disease understanding aims to understand how large numbers of interrelated health variables, gene expression profiling, its cellular architecture and

microenvironment, as seen in its histological image features, its 3 dimensional tissue

architecture and vascularization, as seen in dynamic contrast enhanced (DCE) MRI, and its

metabolic features, as seen by Magnetic Resonance Spectroscopy (MRS) or Positron Emission

Tomography (PET), result in emergence of definable phenotypes. Within our group has been

developing novel computerized knowledge alignment, representation, and fusion tools for

integrating and correlating heterogeneous biological data spanning different spatial and

temporal scales, modalities, and functionalities. These tools include computerized feature

analysis methods for extracting subvisual attributes for characterizing disease appearance and

behavior on radiographic (radiomics) and digitized pathology images (pathomics). In this talk I

will discuss the development work in our group on new radiomic and pathomic approaches for

capturing intra-tumoral heterogeneity and modeling tumor appearance. I will also focus my talk on how these radiomic and pathomic approaches can be applied to predicting disease outcome, recurrence, progression and response to therapy in the context of prostate, brain, rectal, oropharyngeal, and lung cancers. Additionally I will also discuss some recent work on looking at use of pathomics in the context of racial health disparity and creation of more precise and tailored prognostic and response prediction models.

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Bio:

Dr. Anant Madabhushi is the Robert W Woodruff Professor of Biomedical Engineering; and on the faculty in the Departments of Pathology, Biomedical Informatics, and Radiology and Imaging Sciences at Emory University. He is also a Research Health Scientist at the Atlanta Veterans Administration Medical Center. Dr. Madabhushi has authored more than 475 peer-reviewed publications and more than 100 patents issued or pending. He is a, Fellow of the American Institute of Medical and Biological Engineering (AIMBE), and the Institute for Electrical and Electronic Engineers (IEEE) and the National Academy of Inventors (NAI). His work on "Smart Imaging Computers for Identifying lung cancer patients who need chemotherapy" was called out by Prevention Magazine as one of the top 10 medical breakthroughs of 2018. In 2019, Nature Magazine hailed him as one of 5 scientists developing "offbeat and innovative approaches for cancer research". Dr. Madabhushi was named to The Pathologist’s Power List in 2019, 2020, 2021 and 2022.