Skip to main content
padlock icon - secure page this page is secure

Prediction of Cancer Rescue p53 Mutants In Silico Using Naive Bayes Learning Methodology

Buy Article:

$68.00 + tax (Refund Policy)

This research is focussed on predicting through Naive Bayes learning, the possible p53 rescue mutants from amino-acid substitutions at the second, third and fourth site recombination that could reinstate normal p53 activity. The Naive Bayes probability values of the amino-acid substitutions at the respective site-wise recombination were utilized to formulate the proposed Genetic Mutant Marker Extraction (GMME) technique that could unearth the hot spot cancer, strong rescue and weak rescue mutants. The p53 mutation records depicting the amino-acid substitutions obtained by yeast assays comprising of nearly 16,700 records, available at the University of California, Machine Learning Repository, were utilized as the training dataset for the GMME technique. The proposed GMME technique revealed the hot spot cancer mutants, strong rescue and weak rescue mutants leading to the detection of probable genetic markers for Cancer prediction from the surface regions 96-289 constituting the second, third and fourth site recombinations. Thus far, computational approaches have been able to predict rescue markers at region-specific mutations (96-105, 114-123, 130-156 and 223- 232) with respect to the second site recombination for three hot spot cancer mutants only viz, P152L, R158L and G245S. The GMME technique aimed at predicting possible rescue markers for p53 mutants at the second, third and fourth site recombinations revealing novel rescue markers for fourteen hot spot cancer mutants. Moreover, the GMME technique can be extended effectively to increasing number of recombinant sites that can be efficiently utilized to predict novel rescue markers.
No References
No Citations
No Supplementary Data
No Article Media
No Metrics

Keywords: Classification; cancer; data mining; genetic marker prediction; mutations; p53

Document Type: Research Article

Publication date: November 1, 2013

More about this publication?
  • Protein & Peptide Letters publishes short papers in all important aspects of protein and peptide research, including structural studies, recombinant expression, function, synthesis, enzymology, immunology, molecular modeling, drug design etc. Manuscripts must have a significant element of novelty, timeliness and urgency that merit rapid publication. Reports of crystallisation, and preliminary structure determinations of biologically important proteins are acceptable. Purely theoretical papers are also acceptable provided they provide new insight into the principles of protein/peptide structure and function.
  • Editorial Board
  • Information for Authors
  • Subscribe to this Title
  • Ingenta Connect is not responsible for the content or availability of external websites
  • Access Key
  • Free content
  • Partial Free content
  • New content
  • Open access content
  • Partial Open access content
  • Subscribed content
  • Partial Subscribed content
  • Free trial content
Cookie Policy
Cookie Policy
Ingenta Connect website makes use of cookies so as to keep track of data that you have filled in. I am Happy with this Find out more