SPOT-RNA-2D: Predicting RNA distance-based contact maps by integrated deep learning on physics-inferred base-pairing and evolutionary-derived coupling.

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 (required):
Target (optional):
Input your RNA Sequences: Maximum: 500 nts for SPOT-RNA-2D and 10,000 for SPOT-RNA-2D-Single, Only one RNA sequence at a time
Predictor:

Example outputs:

Example-1: 3NPN (Chain-A)      Example-2: 6P2H (Chain-A)

Standalone Program to Run Locally:

SPOT-RNA-2D-local

Datasets:

Sequences      Secondary structure labels      Distance-based contact-labels      Predictions

Reference:

Jaswinder Singh, Kuldip Paliwal, Thomas Litfin, Jaspreet Singh, and Yaoqi Zhou. “Predicting RNA distance-based contact maps by integrated deep learning on physics-inferred secondary structure and evolutionary-derived mutational coupling.” under-review (2022).