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Bio
My name is Sean Whalen. Here's my curriculum vitae and LinkedIn profile. I'm a research scientist applying machine learning to problems in computational biology and computer security, with recent emphasis on the former. I work with Katie Pollard at UCSF's Gladstone Institutes on genome-wide prediction of enhancer gene targets across diverse cell lines in order to disover causal SNPs and de novo mutations located within distal regulatory regions. Using this knowledge, we hope to identify the genes underlying poorly understood diseases as well as better understand the regulatory regions driving diseases where the causal genes are already known.
I was previously a postdoctoral fellow in computational biology at the Mount Sinai Institute for Genomics and Multiscale Biology headed by Eric Schadt. I worked with Gaurav Pandey primarily on applications of ensemble learning — combining multiple (often thousands) of machine learning classifiers — to build predictive models in various areas of genetics and genomics including genetic interactions, synergistic drug interactions, and protein function. As late entrants into the contest, we were the 4th place team in the 2013 DREAM Toxicogenetics Challenge.
I was also part of a team working on enhanced genotyping of the human leukocyte antigen (HLA) region using long read DNA sequencing technology in combination with error-correcting techniques utilizing short read technologies that make independent systematic errors. This work has several applications including improved compatibility between bone marrow donors and recipients. Our team recently pitched to a panel of venture capitalists and was awarded funding as part of a Sinai initiative to commercialize translational research.
I'm a recent transplant into the field, having finished a postdoctoral position during 2012 in the Intrusion Detection Systems lab at Columbia University with Salvatore Stolfo where I worked on anomaly detection and cloud security for DARPA's Mission-oriented Resilient Clouds initiative. In 2011 I finished my I3P postdoctoral fellowship at Lawrence Berkeley National Lab in the Computational Research Division where I developed several methods for anomaly detection in high performance computing systems with Sean Peisert and David Bailey.
I enjoy inter-disciplinary work involving machine learning, statistics, and network theory. I'm also interested in information visualization and virtual reality, having previously developed a complex networks visualization tool with head tracking and gesture recognition for the KeckCAVES project. I completed my Ph.D. at the University of California, Davis in 2010 and was fortunate to be jointly advised by Matt Bishop (Computer Security) and Jim Crutchfield (Physics).
My partner and frequent collaborator is Sophie Engle, currently an Assistant Professor of Computer Science at the University of San Francisco.
Research Interests
Papers共 56 篇Author StatisticsCo-AuthorSimilar Experts
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Science (New York, N.Y.)no. 6698 (2024): eadh0559-eadh0559
bioRxiv : the preprint server for biology (2023)
Neuronno. 6 (2023): 857-873.e8
bioRxiv (Cold Spring Harbor Laboratory) (2022)
Eirene Markenscoff-Papadimitriou,Fadya Binyameen,Sean Whalen,James D. Price,Lim K,Rinaldo Catta-Preta, Pai El,Xin Mu, Dongqing Xu, Pollard Ks,A. Nord, State Mw,
bioRxiv (Cold Spring Harbor Laboratory) (2021)
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