Prediction of Prostate Cancer Cells based on Principal Component Analysis Technique

Abstract

Amino acids, the essential building blocks of life are important to study the genetic diseases, modelling of protein structure and also in drug designing. A PCA model along with signal processing technique is used here for differentiating the prostate cancer cells from normal prostate cells. The amino acid sequence of cells is taken as input sample for the PCA technique. The model is successfully tested on 8 normal and 8 cancerous Homo sapiens prostate cells.