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Predication and Classification of Cancer Using Sequence Alignment and Back Propagation Algorithms in Brca1 and Brca2 Genes
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| Author:
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ALI ABDUL, BAN NADEEM DHANNOON
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| Abstract:
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Cancer is one of the most common and widespread diseases around the world. It is also one of the most dangerous
diseases because millions of people die every year because of the disease. Breast cancer is one of the most common
and hazardous types of cancer around the world. One in eight women is susceptible to breast cancer at some point in
their lives, and it is also the second cancer causing death that comes after lung cancer. Genetic mutation increases the
risk of cancer. The two main genes related to breast cancer are known as Breast Cancer1 and Breast Cancer2
(BRCA1 and BRCA2). One of the major problems is to classify the normal genes and the invalid genes which are
infected by some kind of diseases. So, it is important to identify those genes and classify them. This paper for
prediction and classification cancer genes mutations use two stages; first whether the affected person (patient) has
mutations or not by used sequence alignment for two DNA sequences in BRCA1 and BRCA2 genes (mutant and nonmutant
sequences), the second stage classify these mutations that causes the disease by used BPNN algorithm to
training and testing with 5-fold cross validation. The performance of the proposed system for classification mutations
in BRCA1 and BRCA2 genes using back-propagation neural network show that the average rate of Accuracy,
Sensitivity and Specificity for BRCA1 and BRCA2 are 99.81 - 100 - 99.85 and 98.15 - 100 - 98.68 respectively..
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| Keyword:
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Classification; Bioinformatics; Sequence Alignment; Back Propagation Neural Network; Brca1 and Brca2 genes; Breast Cancer.
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| EOI:
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| DOI:
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https://doi.org/10.31838/ijpr/2019.11.01.062
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| Download:
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Request For Article
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