Journal article

circuitSNPs: Predicting genetic effects using a Neural Network to model regulatory modules of DNase-seq footprints

Alexander Shanku, Anthony Findley, Cynthia Kalita, Heejung Shim, Francesca Luca, Roger Pique-Regi

Cold Spring Harbor Laboratory | Published : 2018


Motivation Identifying and characterizing the function of non coding regions in the genome, and the genetic variants disrupting gene regulation, is a challenging question in genetics. Through the use of high throughput experimental assays that provide information about the chromatin state within a cell, coupled with modern computational approaches, much progress has been made towards this goal, yet we still lack a comprehensive characterization of the regulatory grammar. We propose a new method that combines sequence and chromatin accessibility information through a neural network framework with the goal of determining and annotating the effect of genetic variants on regulation of chromatin ..

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University of Melbourne Researchers

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