MTTFsite: cross-cell type TF binding site prediction by using multi-task learning.

ABSTRACT:

Motivation

The prediction of transcription factor binding sites (TFBSs) is crucial for gene expression analysis. Supervised learning approaches for TFBS predictions require large amounts of labeled data. However, many TFs of certain cell types either do not have sufficient labeled data or do not have any labeled data.

Results

In this paper, a multi-task learning framework (called MTTFsite) is proposed to address the lack of labeled data problem by leveraging on labeled data available in cross-cell types. The proposed MTTFsite contains a shared CNN to learn common features for all cell types and a private CNN for each cell type to learn private features. The common features are aimed to help predicting TFBSs for all cell types especially those cell types that lack labeled dat

SUBMITTER: Zhou J 

PROVIDER: S-EPMC6954652 | biostudies-literature | 2019 Dec

REPOSITORIES: biostudies-literature