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Cancer is one of the most feared diseases in the world it has increaseddisturbingly and breast cancer occurs in one out of eight women, the predictionof malignancies plays essential roles not only in revealing human genome, butalso in discovering effective prevention and treatment of cancers. Generallycancer disease driven by somatic mutations in an individual DNA sequence, orgenome that accumulates during the lifetime of person. This paper is proposed anovel method can predict the disease by mutations despite The presence in genesequence is not necessary it are malignant, so will be compare the protein ofpatient with the gene's protein of disease if there is difference between thesetwo proteins then can say there is malignant mutations. This method will usebioinformatics techniques like FASTA, CLUSTALW, etc which shows whethermalignant mutations or not, then training the backpropagation algorithm usingall expected malignant mutations for a certain genes (e.g. BRCA1 and BRCA2) ofdisease, and using it to test whether patient is holder the disease or not.Implementing this novel method as the first way to predict the disease based onmutations in the sequence of the gene that causes the disease shows twodecisions are achieved successfully, the first diagnose whether the patient hasmutations of cancer or not using bioinformatics techniques the secondclassifying these mutations are related to breast cancer (e.g. BRCA1 and BRCA2)using backpropagation with mean square rate 0.1. Keywords-Gene sequence;Protein; Deoxyribonucleic Acid DNA; Malignant mutation; Bioinformatics;Back-propagation algorithm.

Novel Method for Mutational Disease Prediction using Bioinformatics Techniques and Backpropagation Algorithm