Transcription factor binding site detection using convolutional neural networks with a functional group-based data representation
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László Tóth | Gergely Pap | Györgypál Zoltán | Krisztián Ádám | Zoltán Hegedűs | L. Tóth | Z. Hegedus | Gergely Pap | Györgypál Zoltán | Krisztian Adam
[1] Hong-Bin Shen,et al. RNA-protein binding motifs mining with a new hybrid deep learning based cross-domain knowledge integration approach , 2016, BMC Bioinformatics.
[2] B. Frey,et al. Predicting the sequence specificities of DNA- and RNA-binding proteins by deep learning , 2015, Nature Biotechnology.
[3] Daniel Quang,et al. FactorNet: a deep learning framework for predicting cell type specific transcription factor binding from nucleotide-resolution sequential data , 2017, bioRxiv.
[4] Xiaohui S. Xie,et al. Predicting transcription factor binding in single cells through deep learning , 2020, bioRxiv.
[5] Krisztian Adam,et al. DNA Readout Viewer (DRV): visualization of specificity determining patterns of protein-binding DNA segments , 2020, Bioinform..
[6] William Stafford Noble,et al. DNA sequence+shape kernel enables alignment-free modeling of transcription factor binding , 2016, bioRxiv.
[7] David K. Gifford,et al. Convolutional neural network architectures for predicting DNA–protein binding , 2016, Bioinform..
[8] Xiaohui Xie,et al. FactorNet: a deep learning framework for predicting cell type specific transcription factor binding from nucleotide-resolution sequential data , 2017, bioRxiv.
[9] May D. Wang,et al. DeeperBind: Enhancing Prediction of Sequence Specificities of DNA Binding Proteins , 2016, bioRxiv.