Learning pair-wise gene functional similarity by multiplex gene expression maps.

ABSTRACT:

Background

The relationships between the gene functional similarity and gene expression profile, and between gene function annotation and gene sequence have been studied extensively. However, not much work has considered the connection between gene functions and location of a gene's expression in the mammalian tissues. On the other hand, although unsupervised learning methods have been commonly used in functional genomics, supervised learning cannot be directly applied to a set of normal genes without having a target (class) attribute.

Results

Here, we propose a supervised learning methodology to predict pair-wise gene functional similarity from multiplex gene expression maps that provide information about the location of gene expression. The features are extracted from expr

SUBMITTER: An L 

PROVIDER: S-EPMC3375633 | biostudies-literature | 2012 Mar

REPOSITORIES: biostudies-literature