Machine learning based prediction of essential genes of Saccharomyces cerevisiae utilising protein abundance as a feature

Protein abundance is a measure of expression of mRNA in a cell. The code of DNA is not expressed constitutively in all conditions; hence it is important to determine the population and abundance of proteins in a cell to determine cellular functions. Essential protein products are mandatory for functioning of a live cell. Thus patterns of abundance of essential and non-essential proteins may vary. A machine learning based framework has been applied here using neural net algorithm which could predict essential genes of S. cerevisiae using protein abundance as a feature using 77.65 percent accuracy.