Abstract
Sequence-to-expression relationship is one of the major research topics in the field of regulatory genomics. Prediction of epigenomic states such as DNA accessibility or transcription factor(TF)-DNA binding has been studied extensively, but predicting a gene's expression in different cell types based on its regulatory enhancer sequences remains largely unsolved. Here, we present a thermodynamics-based sequence-to-expression model that combines DNA accessibility, TF concentrations and enhancer sequence information to classify enhancers into their spatio-temporal activity classes in Drosophila mesoderm.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
