Held annually by the International Society for Computational Biology (ISCB), the conference brings together researchers from universities all over the world.
Julian’s research involves developing statistical methods for studying complex traits in genome-wide studies, in particular, detecting interactions between genetic variants. His talk was entitled “Leveraging the Genetic Correlation between Traits Improves the Detection of Epistasis in Genome-wide Association Studies,” and was co-authored by Alan Denadel, CCMB Ph.D. student; Daniel Weinreich, Director of CCMB; and Lorin Crawford, Associate Professor of Biostatistics with a core faculty appointment in CCMB and Principal Researcher at Microsoft Research.
The number of abstracts selected to give oral presentations at the ISMB conference is very low relative to the number of submissions. “I was nervous but also excited [to give the talk] because it was such a big opportunity for me to share my work,” says Stamp of his experience at the conference. "The most exciting insight I think is that we showed that we can detect causal genetic variants by leveraging correlations of epistatic variance components that are due to a shared genetic architecture in complex traits. This shared architecture may be hidden when only looking at trait covariance."