RNArank

Introduction

RNArank is a novel deep learning-based approach to both local (nucleotide-specific) and global quality assessment of predicted RNA 3D structure models. This network is trained to predict intermediate two 2D maps, including inter-nucleotide contact maps and distance deviation maps. These maps are then used to estimate the local and global accuracy (i.e., lDDT). Extensive benchmark tests indicate that RNArank consistently outperforms traditional methods and other deep learning-based methods. Read more about the RNArank algorithm...

The supported input format is:

The output results include:

Submit Your Job
  • Provide a single RNA structure
    •
    Please input a RNA structure file (structure in PDB format or mmCIF format). Click for an example of PDB input, mmCIF input
    Or upload the structure file:


  • Other information (optional)
    • Email: (Optional, where the results will be sent to)

    Target name: (Optional, your given name to this target)


    Keep my results private (check this box if you want to keep your job private. A key will be assigned for you to access the results)


    Reference

  • Liu et al, Quality assessment of RNA 3D structure models using deep learning and intermediate 2D maps.