biostudies-literatureWang HNICHD NIH HHSNIH/NICHD14https://www.ebi.ac.uk/biostudies/studies/S-EPMC8740472biostudies-literatureUnknown23(1)<h4>Background</h4>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.<h4>Method</h4>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 "funcBMC genomicsPredicting the targets of IRF8 and NFATc1 during osteoclast differentiation using the machine learning method framework cTAP.PMC8740472R01 HD0986361R01HD098636-0Joshi PWang HMaye PFRowe DWHong SHShin DGfalsePredicting the targets of IRF8 and NFATc1 during osteoclast differentiation using the machine learning method framework cTAP.<h4>Background</h4>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.<h4>Method</h4>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 "func2022-01-01T00:00:00Z2022 Jan2025-04-21T17:38:42.58Z2022-02-11T15:09:04.606ZS-EPMC87404723499146710.1186/s12864-021-08159-z