The applications listed here are available for use in the Discovery Environment and are documented in: Discovery Environment Manual.

Discovery Environment Applications List

The box below searches only this space.
To search the entire iPlant wiki, enter your query in the box at the upper right.

 

 

 

Skip to end of metadata
Go to start of metadata

Rationale:


LncTar is software for predicting lncRNA-RNA interactions by means of free energy minimization. LncTar utilized a variation on the standard "sliding" algorithm approach to calculate the normalized binding free energy (ndG) and found the minimum free energy joint structure. The ndG was regarded as a cutoff which determining the paired RNAs as either interacting or not. Of course, LncTar is not specific for lncRNAs but also can be used for predicting putative interactions among various types of RNA molecules, such as mRNA, noncoding RNAs including lncRNAs, pre-miRNAs, and other types of noncoding RNAs.

  1. Sub program
    1. Kind
  2. Type 1
    1. Query LncRNA (Fasta) file
    2. Target mRNA (Fasta) file
  3. Type 2
    1. Input paired RNA sequence file
  4. Settings
    1. Normalized deltaG (nDG): cutoff of the normalized deltaG (ndG). Set the value of the ndG: ndG is regarded as a cutoff which can be used for predicting putative interactions among various types of RNA molecules. The default value is -0.1.
    2. Output the paired sequences
  5. Outputs
    1. Output file

Test run:

Please run Infernal app with the test data located at Community Data > iplantcollaborative > example_data > lnctar  (/iplant/home/shared/iplantcollaborative/example_data/lnctar)

  1. Sub program
    1. Kind
  2. Type 1
    1. Query LncRNA (Fasta) file
    2. Target mRNA (Fasta) file
  3. Type 2
    1. Input paired RNA sequence file
  4. Settings
    1. Normalized deltaG (nDG)
    2. Output the paired sequences
  5. Outputs
    1. Output file

Please work through the documentation and add your comments on the bottom of this page, or click the intercom button on this page. 

  • No labels