Original paper
Graph embedding and unsupervised learning predict genomic sub-compartments from HiC chromatin interaction data
Abstract
Chromatin interaction studies can reveal how the genome is organized into spatially confined sub-compartments in the nucleus. However, accurately identifying sub-compartments from chromatin interaction data remains a challenge in computational biology. Here, we present Sub-Compartment Identifier (SCI), an algorithm that uses graph embedding followed by unsupervised learning to predict sub-compartments using Hi-C chromatin interaction data. We...
Paper Details
Title
Graph embedding and unsupervised learning predict genomic sub-compartments from HiC chromatin interaction data
Published Date
Mar 3, 2020
Journal
Volume
11
Issue
1
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Notes
History