CLIP-Seq, Portal, Visualize, Analyze, Discover.
    


Please Cite our starBase Paper:
Li et al. Nucleic Acids Res. 2014;42:D92-D97. & Yang et al. Nucleic Acids Res. 2011;39:D202-D209.

  1. clade:       genome:    assembly:

  2. microRNA:   

  3. Number of supporting Experiments>=

  4. Number of Cancer Types(Pan-Cancer)>=

  5. Program Number>=

  6. Intersections by selecting two or more programs

    targetScan   picTar   RNA22   PITA   miRanda/mirSVR   

  7. Gene Symbol: (e.g. "E2F1")


You can search for intersections among targets predicted by five predicted softwares(TargetScan, PicTar, PITA, miRanda/mirSVR and RNA22) by entering the gene name or selecting a microRNA name and selecting one/multiple target prediction softwares. Here, we list the predicted intersections supported with CLIP-Seq data.

Examples:

  1. When you selected targetScan and picTar, the output will include target sites predicted by both targetScan and picTar programs.

  2. When you selected all predicted softwares, the output will include target sites predicted by all predicted programs.

Note:
  1. Number of supporting Experiments can be used to reduce false positives for predicted target sites. For example, medium stringency(>=2) means that >=2 CLIP-Seq experiments supported the predicted miRNA target site.
  2. Number of Cancer Types(Pan-Cancer) can be used to explore anti-correlation (pearson correlation: r<0, p-value<0.05) between miRNA and target genes across diverse cancer types. For example, cancer type >=1 means that expression of miRNA and target gene is anti-correlation (pearson correlation: r<0, p-value<0.05) at least one cancer type.