Article

A general framework for predicting the transcriptomic consequences of non-coding variation

2018-03-10

Abstract excerpt

<h4>ABSTRACT</h4> Genome wide association studies (GWASs) for complex traits have implicated thousands of genetic loci. Most GWAS-nominated variants lie in noncoding regions, complicating the systematic translation of these findings into functional understanding. Here, we leverage convolutional neural networks to assist in this challenge. Our computational framework, peaBrain, models the transcriptional machinery...

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Literature Corpus work: 4bf11784-bd16-5fe7-be05-0e6eb82ce452
DOI: 10.1101/279323

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