Reading between the genes: interpreting non-coding DNA in high-throughput

Joanne Berghout^1,†, Yves A. Lussier^1,†, Francesca Vitali^1,†, Martha L. Bulyk^2,†, Maricel G. Kann^3,†, Jason H. Moore^4,†

¹Center for Biomedical Informatics and Biostatistics, Dept. of Medicine, University of Arizona
²Division of Genetics, Dept. of Medicine & Dept. of Pathology, Brigham and Women's Hospital and Harvard Medical School
³Dept. of Biological Sciences, University of Maryland
⁴Institute for Biomedical Informatics, University of Pennsylvania
^†Authors contributed equally to this work
Email: jberghout@email.arizona.edu, yves@email.arizona.edu, francescavitali@email.arizona.edu, mlbulyk@genetics.med.harvard.edu, mkann@umbc.edu, jhmoore@upenn.edu

Pacific Symposium on Biocomputing 24:444-448(2019)

© 2019 World Scientific
Open Access chapter published by World Scientific Publishing Company and distributed under the terms of the Creative Commons Attribution (CC BY) 4.0 License.

Abstract

Identifying functional elements and predicting mechanistic insight from non-coding DNA and non- coding variation remains a challenge. Advances in genome-scale, high-throughput technology, however, have brought these answers closer within reach than ever, though there is still a need for new computational approaches to analysis and integration. This workshop aims to explore these resources and new computational methods applied to regulatory elements, chromatin interactions, non-protein-coding genes, and other non-coding DNA.