RNAsnap2: Single-sequence and Profile-based Prediction of RNA Solvent Accessibility Using Dilated Convolution Neural Network.

Posted on by Jaswinder Singh

Our resources are limited. If you wish to run several batches per day please make use of the downloadable package or contact the administrator directly.

Submit

E-mail address (optional):
Target (optional):
Input your RNA Sequences: Maximum: 1,000 nts for RNAsnap2 and 50,000 for RNAsnap2_SingleSeq, Only one RNA sequence at a time
Solvent accessibility prediction method:

Note:

To run RNAsnap2 for long sequences, please use standalone version of RNAsnap2 mentioned below.

Standalone Program to Run Locally:

RNAsnap2-local

Datasets:

Training TR95, validation VL24, and test (TS45, TS31) sets Dropbox or Nihao Cloud

Reference:

Anil Kumar Hanumanthappa, Jaswinder Singh, Kuldip Paliwal, Jaspreet Singh, Yaoqi Zhou, Single-sequence and profile-based prediction of RNA solvent accessibility using dilated convolutional neural network, Bioinformatics, Volume 36, Issue 21, 1 November 2020, Pages 5169–5176. https://doi.org/10.1093/bioinformatics/btaa652