Democratizing Data-Driven Biology by Overcoming the Metadata Bottleneck
Join University of Colorado’s Dr. Arjun Krishnan as he discusses how machine learning and natural language processing can contribute to making public -omics data more accessible.
Dr. Krishnan will also present the recent work from his group, the Krishnan Lab, to address these two challenges that contribute to under-used data:
- Unstructured metadata: sample descriptions contain information about their source in the form of ambiguous plain text.
- Missing metadata: sample descriptions frequently miss key, basic pieces of information about their source.
The Krishnan Lab works in the areas of computational biology and biomedical data science at the University of Colorado Anschutz Medical Campus.
The Data Science Seminar Series presents talks from innovators in the cancer research and informatics communities both within and outside of NCI.
Dr. Krishnan is an associate professor at the University of Colorado and a group leader at the Krishan Lab. He works on developing computational approaches to study the genetic basis of biomedical phenomena relevant to human health and disease. Dr. Krishnan is primarily interested in bridging the gap between large-scale genomic/clinical data and actionable biological insights using statistical and machine learning approaches.