Computer aided classification of marker proteins for cell survival /cell death

The signaling system underlying cell death allows the cell to
process input signals capturing information coming from the
environment of the cell to lead to one of two possible outputs:
cell survival or cell death. This work examines signaling networks
that control the survival decision treated with combinations
of the pro-death cytokine, tumor necrosis factor-α (TNF),
and the pro-survival growth factors, epidermal growth factor
(EGF) and insulin. There are ten different combinations of
TNF, EGF and insulin whose values are in ng/ml. We have
considered the heat map image which is showing 11 different
proteins : MK2, JNK, FKHR, MEK, ERK, IRS, AkT, IKK,
pAkT, ptAkT and EGFR for the HT carcinoma cells which
helps in cell survival/ death. The averages of all outputs were
taken which were normalized to maximum. Data mining methods
have the potential to identify groups at high risk. There
are different steps for processing the data so as to extract their
results: data collection, data pre-processing, feature extraction,
feature selection, data partitioning, and data classification.
There are different types of regression analysis. Out of which
simple regression and multiple regressions was considered. For
calculation purpose we have used PLS analysis which calculates
squared r values. We have validated our results by calculating
adjusted regression coefficient, predicted regression coefficient
regression coefficient cross validation, rm2 , F-test values, Coefficient
of determination, ANOVA, t-value, Durban Watson statistics
for the different proteins. Later multiple regressions were
used as we have different independent variables (proteins). To
validate the results we have calculated the coefficient, standard
error, standard coefficient, tolerance, t value and p value, variation
explanation of predictors and estimators which gives cumulative
percentage. After analysis we get 7 proteins (AkT, Epidermal
growth factor receptor (EGFR), Extracellular-regulated
kinase (ERK), c-jun N-terminal kinases(JNK), Mitogen-activated
protein kinase-activated protein kinase 2 (MK2), Insulin
receptor substrate (IRS) , and Forkhead transcription factor
(FKHR))as the marker (best) proteins which were used for classification.

Author(s): Shruti Jain

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