Predicting dynamic cellular protein-RNA interactions using deep learning and in vivo RNA structure
Lei Sun* and Kui Xu* and Wenze Huang* and Yucheng T. Yang* and Lei Tang and Tuanlin Xiong and Qiangfeng Cliff Zhang#

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PrismNet_Predictions.tar.gz (318MB) MD5: 53048877b212e3a7cb3b746ed9d94be1
PrismNet_Predictions_OnlySeq.tar.gz (316MB) MD5: 752cc4cfe5130d3107c8982df5bfab89
icSHAPE.tar (557M) MD5: d22796148b49437b32e912d022a90016 (48MB) MD5: dcc6cf1c2425b54f9e4385e09658df60
eCLIP_Peaks_K562_HepG2.tar.gz (114MB) MD5: 8eecc6265fe0bc8eae1ba01165e3db51
Integrative motif from PrismNet (191 motifs of 168 RBPs) (4.7MB) MD5: 0a5eb668954190c4032167532dfb2e31