The PsychENCODE project.

Abstract

Department

Description

Provenance

Citation

Published Version (Please cite this version)

10.1038/nn.4156

Publication Info

PsychENCODE Consortium, Schahram Akbarian, Chunyu Liu, James A Knowles, Flora M Vaccarino, Peggy J Farnham, Gregory E Crawford, Andrew E Jaffe, et al. (2015). The PsychENCODE project. Nat Neurosci, 18(12). pp. 1707–1712. 10.1038/nn.4156 Retrieved from https://hdl.handle.net/10161/13706.

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Scholars@Duke

Crawford

Gregory E. Crawford

Professor in Pediatrics

My primary research interest is understanding how the genome is regulated.  The human genome contains approximately 25,000 genes, which are encoded in ~2% of the genome. The overarching goal of my research program is to identify and characterize how these genes are turned on and off in different cell types, tissues, development states, environmental responses, diseases, and individuals. By understanding where all gene regulatory elements are located, how they work to regulate gene expression, and how non-coding variants within these regions affect function, my research program can address a number of important basic and clinical questions.

Reddy

Timothy E Reddy

Associate Professor of Biostatistics & Bioinformatics,
Wray

Gregory Allan Wray

Professor of Biology

I study the evolution of genes and genomes with the broad aim of understanding the origins of biological diversity. My approach focuses on changes in the expression of genes using both empirical and computational approaches and spans scales of biological organization from single nucleotides through gene networks to entire genomes. At the finer end of this spectrum of scale, I am focusing on understanding the functional consequences and fitness components of specific genetic variants within regulatory sequences of several genes associated with ecologically relevant traits. At the other end of the scale, I am developing molecular and analytical methods to detect changes in gene function throughout entire genomes, including statistical frameworks for detecting natural selection on regulatory elements and empirical approaches to identify functional variation in transcriptional regulation. At intermediate scales, I am investigating functional variation within a dense gene network in the context of wild populations and natural perturbations. My research leverages the advantages of several different model systems, but primarily focuses on sea urchins and primates (including humans).


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