GeneSurrounder: network-based identification of disease genes in expression data
Abstract Background A key challenge of identifying disease–associated genes is analyzing transcriptomic data in the context of regulatory networks that control cellular processes in order to capture multi-gene interactions and yield mechanistically interpretable results. One existing category of ana...
Main Authors: | , |
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Format: | Article |
Language: | English |
Published: |
BMC
2019-05-01
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Series: | BMC Bioinformatics |
Subjects: | |
Online Access: | http://link.springer.com/article/10.1186/s12859-019-2829-y |