Identifying Cancer Subtypes from miRNA-TF-mRNA Regulatory Networks and Expression Data.

ABSTRACT:

Background

Identifying cancer subtypes is an important component of the personalised medicine framework. An increasing number of computational methods have been developed to identify cancer subtypes. However, existing methods rarely use information from gene regulatory networks to facilitate the subtype identification. It is widely accepted that gene regulatory networks play crucial roles in understanding the mechanisms of diseases. Different cancer subtypes are likely caused by different regulatory mechanisms. Therefore, there are great opportunities for developing methods that can utilise network information in identifying cancer subtypes.

Results

In this paper, we propose a method, weighted similarity network fusion (WSNF), to utilise the information in the complex miRNA-

SUBMITTER: Xu T 

PROVIDER: S-EPMC4818025 | biostudies-literature | 2016

REPOSITORIES: biostudies-literature