You are invited to join us on Thursday, October 5th, from 10 A.M - 11 A.M. for a virtual seminar by Jeremy J. Yang, Ph.D.

Topic: Evidence Evaluation in Biomedical Knowledge Graphs for Pharmaceutical Discovery

Synopsis:

In this seminar, Dr. Yang will describe several biomedical data science research projects from diverse domains, involving teams comprised of contributors from UNM and elsewhere, which share a common theme of evidence evaluation for pharmaceutical discovery. What is the strongest biomedical evidence about a disease for discovery of novel pharmaceutical therapies? This is a fundamental challenge for biomedical scientists, but also translates to a parallel question for data science: Can we systematically assemble and query biomedical knowledge graphs in a computational discovery platform guided by rational, algorithmic measures of relevance and confidence, facilitating scientific discovery? And, how have continuing waves of scientific and technological progress, in an era of bigger and bigger data, informed and empowered these inquiries?

Learning objectives:

  • Participants will be able to explain the meaning of "knowledge graph"
  • Participants will be able to describe how data can be aggregated to rationally measure evidence

Please email BLCarroll@salud.unm.edu to request Zoom info.