ECGpred: Correlation and prediction of gene expression level from amino acid and dipeptide composition of its protein

This study explores the relationship between the amino acid and dipeptide composition of a protein and its corresponding gene expression levels. By analyzing high-throughput microarray data, the study demonstrates that the primary sequence of a protein contains significant information that correlates with how much of that protein is expressed in a cell. Citation Raghava, G. P. S., & Han, J. H. (2005). Correlation and prediction of gene expression level from amino acid and dipeptide composition of its protein. BMC Bioinformatics, 6:59. https://doi.org/10.1186/1471-2105-6-59 About the Research In the post-genomic era, understanding the regulation of gene expression is a major challenge. While many studies focus on regulatory elements in DNA or mRNA stability, this study investigates the "protein-side" of the equation. It suggests that the amino acid composition—essentially the building blocks of the protein—is non-randomly associated with the abundance of that protein. Dataset: The study utilized protein sequence data and gene expression levels for Saccharomyces cerevisiae(yeast). Methodology: Systematic correlation analysis was performed between expression levels and the frequency of 20 amino acids and 400 possible dipeptides.