Open AccessStandard Multiple Regression Analysis Model for Cell Survival/ Death Decision of JNK Protein Using HT-29 Carcinoma Cells
Author(s) -
Shruti Jain,
D.S. Chauhan
Publication year - 2019
Publication title -
international journal of innovative technology and exploring engineering
Language(s) - English
Resource type - Journals
ISSN - 2278-3075
DOI - 10.35940/ijitee.h7163.0881019
Subject(s) - statistics , regression analysis , linear regression , standard deviation , correlation coefficient , mathematics , regression , outlier , analysis of covariance , covariance matrix , analysis of variance , standard error
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