BTNET : boosted tree based gene regulatory network inference algorithm using time-course measurement data.

ABSTRACT:

Background

Identifying gene regulatory networks is an important task for understanding biological systems. Time-course measurement data became a valuable resource for inferring gene regulatory networks. Various methods have been presented for reconstructing the networks from time-course measurement data. However, existing methods have been validated on only a limited number of benchmark datasets, and rarely verified on real biological systems.

Results

We first integrated benchmark time-course gene expression datasets from previous studies and reassessed the baseline methods. We observed that GENIE3-time, a tree-based ensemble method, achieved the best performance among the baselines. In this study, we introduce BTNET, a boosted tree based gene regulatory network inference al

SUBMITTER: Park S 

PROVIDER: S-EPMC5861501 | biostudies-literature | 2018 Mar

REPOSITORIES: biostudies-literature