Regression based predictor for p53 transactivation.

ABSTRACT:

Background

The p53 protein is a master regulator that controls the transcription of many genes in various pathways in response to a variety of stress signals. The extent of this regulation depends in part on the binding affinity of p53 to its response elements (REs). Traditional profile scores for p53 based on position weight matrices (PWM) are only a weak indicator of binding affinity because the level of binding also depends on various other factors such as interaction between the nucleotides and, in case of p53-REs, the extent of the spacer between the dimers.

Results

In the current study we introduce a novel in-silico predictor for p53-RE transactivation capability based on a combination of multidimensional scaling and multinomial logistic regression. Experimentally vali

SUBMITTER: Gowrisankar S 

PROVIDER: S-EPMC2719629 | biostudies-literature | 2009 Jul

REPOSITORIES: biostudies-literature