Epiviz: Interactive Visual Analytics for Functional Genomics Data Benjamin Harvey, Phd

“Epiviz: Interactive Visual Analytics for Functional Genomics Data” Benjamin Harvey, PhD Student, Computer Science University of Maryland at College Park

Thursday, Nov. 13, 2014 @ 3:30 – 4:45 PM, CSB - Room 210

Florin Chelaru is a CS PhD candidate at the University of Maryland, working in the Center for Bioinformatics and Computational Biology. I specialize on problems of Big Data in high throughput sequencing. My latest project is Epiviz (http://epiviz.cbcb.umd.edu, http://dx.doi.org/10.1038/nmeth.3038), a visualization tool for functional genomics data. In the past I worked on other Big Data, ML problems, as part of Facebook’s spam detection team, Rocket Fuel’s AI team, or Microsoft’s Bing Search team. I received my Bachelor’s degree in Computer Science from University Al. I. Cuza of Iasi, Romania.

Abstract: Big Data visualization through genome browsers is a fundamental aspect of the analysis of genomic experimental results. Commonly, the data visualized in these tools is the output of analyses performed in powerful computing environments like R/Bioconductor or Python. Two essential aspects of data analysis, disjoint algorithmic analysis and interactive visualization, are usually treated as distinct. In current technologies these are not integrated within one tool, but rather, one precedes the other. Recent technological advances in web-based data visualization have made it possible for interactive visualization tools to tightly integrate with powerful algorithmic tools, without being restricted to one such tool in particular. We introduce a series of design principles for interactive visualization of large complex data, with application in functional genomics, centered on providing tight-knit integration with computational and statistical analyses. These methods are implemented over Epiviz (http://epiviz.cbcb.umd.edu), an application featuring an interactive, open-ended integration with computing environments. Combined with an interactive web- based design, this facilitates the reproducible dissemination of interactive data analyses of high-throughput functional genomics experiments, in a user-friendly platform.

Contact Dr. Soo-Yeon Ji ([email protected]) if you have any question.