Predicting dynamic cellular protein-RNA interactions by PrismNet

RNA Binding Protein:

Show eCLIP coverage (K562 and HepG2)

Show icSHAPE data

Show eCLIP Peaks (K562 and HepG2)

Click the "Select tracks" button () to select and display multiple cell lines and RBPs.

Reference

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#
Cell Research

Code

Download data

PrismNet_Predictions.tar.gz (318MB) MD5: 53048877b212e3a7cb3b746ed9d94be1
PrismNet_Predictions_OnlySeq.tar.gz (316MB) MD5: 752cc4cfe5130d3107c8982df5bfab89
icSHAPE.tar (557M) MD5: d22796148b49437b32e912d022a90016
Structural_Variable_Sites_Table.zip (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