Assessing the model transferability for prediction of transcription factor binding sites based on chromatin accessibility

Assessing the model transferability for prediction of transcription factor binding sites based on chromatin accessibility

Abstract Background Computational prediction of transcription factor (TF) binding sites in different cell types is challenging. Recent technology development allows us to determine the genome-wide chromatin accessibility in various cellular and developmental contexts. The chromatin accessibility pro...

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Bibliographic Details
Main Authors: Sheng Liu, Cristina Zibetti, Jun Wan, Guohua Wang, Seth Blackshaw, Jiang Qian
Format: Article
Language:English
Published: BMC 2017-07-01
Series:BMC Bioinformatics
Subjects:
Transcription factor binding prediction
Chromatin accessibility
Machine learning
Feature selection
Online Access:http://link.springer.com/article/10.1186/s12859-017-1769-7

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http://link.springer.com/article/10.1186/s12859-017-1769-7

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