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The NRpred is a SVM based tool for the classification of nuclear receptors on the basis of amino acid composition or dipeptide composition. The overall prediction accuracy of amino acid composition and dipeptide composition based methods is 82.6% and 97.2% respectively.The method can classify the nuclear receptors to these four familities.
  • Thyroid hormone like (TR,RAR,ROR,PPAR,VDR).
  • HNF4-like (HNF4,RXR,TLL,COUP,USP).
  • Estrogen like (ER,ERR,GR,MR,PR,AR).
  • Fushi tarazu-F1 like (SF1,FTF,FTZ-F1).

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Choose Prediction Approach
 Composition Based
 Dipeptide composition Based