What is being modeled?
Genome-wide binding profiles of transcription factors
Description & purpose of resource
scFAN is a deep learning model that predicts the probability of a TF binding at a given genomic region, with inputs of ATAC-seq, DNA sequence, and DNA mapability data from that region.
1 - 103 s
This resource is currently
mature and useful in ongoing research
Has this resource been validated?
Link to Resource Credibility Assessment
Key publications (e.g. describing or using resource)
Fu, Laiyi, Lihua Zhang, Emmanuel Dollinger, Qinke Peng, Qing Nie, and Xiaohui Xie. "Predicting transcription factor binding in single cells through deep learning." Science Advances 6, no. 51 (2020): eaba9031.
DOI link to publication describing this resource
Link to resource
Xiaohui Xie (PI)
Qing Nie (PI)
PI contact information
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