Predicting the targets of IRF8 and NFATc1 during osteoclast differentiation using the machine learning method framework cTAP.

ABSTRACT:

Background

Interferon regulatory factor-8 (IRF8) and nuclear factor-activated T cells c1 (NFATc1) are two transcription factors that have an important role in osteoclast differentiation. Thanks to ChIP-seq technology, scientists can now estimate potential genome-wide target genes of IRF8 and NFATc1. However, finding target genes that are consistently up-regulated or down-regulated across different studies is hard because it requires analysis of a large number of high-throughput expression studies from a comparable context.

Method

We have developed a machine learning based method, called, Cohort-based TF target prediction system (cTAP) to overcome this problem. This method assumes that the pathway involving the transcription factors of interest is featured with multiple "func

SUBMITTER: Wang H 

PROVIDER: S-EPMC8740472 | biostudies-literature | 2022 Jan

REPOSITORIES: biostudies-literature