  Tumor protein P53 is believed to be involved in over half of human cancers
cases, the prediction of malignancies plays essential roles not only in advance
detection for cancer, but also in discovering effective prevention and
treatment of cancer, till now there isn't approach be able in prediction the
mutated in tumor protein P53 which is caused high ratio of human cancers like
breast, Blood, skin, liver, lung, bladder etc. This research proposed a new
approach for prediction pre-cancer via detection malignant mutations in tumor
protein P53 using bioinformatics tools like FASTA, BLAST, CLUSTALW and TP53
databases worldwide. Implement and apply this new approach of prediction
pre-cancer through mutations at tumor protein P53 shows an effective result
when used more specific parameters/features to extract the prediction result
that means when the user increase the number of filters of the results which
obtained from the database gives more specific diagnosis and classify, addition
that the detecting pre-cancer via prediction mutated tumor protein P53 will
reduces a person's cancers in the future by avoiding exposure to toxins,
radiation or monitoring themselves at older ages by change their food,
environment, even the pace of living. Also that new approach of prediction
pre-cancer will help if there is any treatment can give for that person to
therapy the mutated tumor protein P53. Index Terms (Normal Homology TP53 gene,
Tumor Protein P53, Oncogene Labs, GC and AT content, FASTA, BLAST, ClustalW)
