ECGPRED: Prediction of Gene Expression from its Nuculeotides Composition

ECGPred
Prediction of Gene Expression from its Nucleotide Composition

This server allows user to analsis the expresion data (Microarray Data) where it calculate correlation coefficient between level of gene expression and nucleotides composition of genes. This will facilitate users in understanding which nucleotides are prefered and vice verse in a organism in given condition. This server also allows to learn from known microarray gene expression data and to predict expression level of other genes of same organism in that condition from their DNA sequence. The method uses SVM for learning and prediction.

Data Sets

In this study we used following datasets i) Yeast data (Nucleotide sequence & Expression data) ; ii) Mouse data (Nucleotide sequence & Expression data); iii) Arabidopsis (Nucleotide sequence & Expression data)


Please read related articles

Raghava, G. P. S., Hwang, D. J. and Han, J. H. (2004) Correlation between Expression Level of Gene and Codon Usage. Proceedings of the 3rd Annual Conference of the Korean Society for Bioinformatics(KSBI2004), November 4-5, 2004, Seoul Korea. pp. 138-149. Reprint (PDF)

Raghava, G. P. S. and Han, J. H. (2005) Correlation and prediction of gene expression level from amino acid and dipeptide composition of its protein. BMC Bioinformatics 6:59.
Reprint (PDF)