Standard multiple regression analysis model for cell survival/ death decision of JNK protein using HT-29 carcinoma cells

Abstract

Signaling by the JNK protein has been studied for more than decades with various previous reviews covering more specific aspects. For estimating the relationship among variables a statistical technique called Regression analysis (RA) is used. RA is used to determine the correlation among two or more variables. In this paper, a multiple regression analysis is used to assess the most significant contribution of JNK protein using ten different concentrations of TNF, EGF, and Insulin that control the survival/ apoptosis response of HT-29 human colon carcinoma cells. The data is analyzed using Statistica software. Data normality and the outliers were checked by visual method (histograms, box plot and Q-Q plot). Descriptive statistics (mean and standard deviation) and correlation matrix (correlation and covariance between variables) are used to get the best concentration. Standard regression analysis is used to make a model through which analysis of variance, regression coefficient & correlation coefficients were analysed and based on the p-value we come to know that 100-0-500 yields the best concentration level which helps in the analysis the cell survival/ apoptosis of JNK protein that was validated by variable importance plot.