| Democratizing Data-Driven Biology to Unravel Complex Diseases Mechanisms |
| Arjun Krishnan |
| March 22, 2023, Wednesday, 3:00 PM - 4:00 PM EDT |
| Abstract Publicly available massive data collections contain valuable signals that can help fill critical gaps in our biomedical knowledge about the molecular mechanisms underlying complex traits and diseases. Our group's goal is to enable biomedical researches to effectively reuse these data - e.g., omics profiles, molecular networks, knowledgebases, unstructured text corpora, and genetic associations - to gain nuanced insights into the heterogeneous traits/disease. We do so by developing integrative machine learning approaches and tools that work to improve every stage of data-driven biology: harmonizing and integrating heterogeneous genomic and genetic data, reconstructing genome-scale networks for data and knowledge representation, transferring information across species, natural language processing to annotate omics data, and developing open software and interactive webservers. The approaches that we develop are highly general, thus applicable to a wide range of biological phenomena in both human and model organisms. In this talk, I will provide an overview of our work in these areas by highlighting some specific projects. |
| Bio Dr Krishnan's group develops computational approaches that take advantage of massive public data collections to build predictive and interpretable models of genes, molecular networks, and tissue mechanisms that underlie the heterogeneity of complex diseases. In addition to biomedical data science and machine learning, he is passionate about open science, research training, and creating diverse and inclusive learning environments. |