IJPR  articles are Indexed in SCOPUSClick Here     Impact Factor for Five Years is 0.13 (2013 - 2018).    

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INTERNATIONAL JOURNAL OF PHARMACEUTICAL RESEARCH

A Step Towards Excellence

IJPR included in UGC-Approved List of Journals - Ref. No. is SL. No. 4812 & J. No. 63703

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0975-2366
5 - Years Impact Factor

Year 2012 - 2016

Impact Factor: 1.55

Total Publications: 317

Total Citation: 491

Year 2011 - 2015

Impact Factor: 1.46

Total Publications: 326

Total Citation: 477

Year 2010 - 2014

Impact Factor: 1.3

Total Publications: 313

Total Citation: 407

Year 2009 - 2013

Impact Factor: 0.973

Total Publications: 293

Total Citation: 285

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Predication and Classification of Cancer Using Sequence Alignment and Back Propagation Algorithms in Brca1 and Brca2 Genes

Author: ALI ABDUL, BAN NADEEM DHANNOON
Abstract: 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..
Keyword: Classification; Bioinformatics; Sequence Alignment; Back Propagation Neural Network; Brca1 and Brca2 genes; Breast Cancer.
DOI: https://doi.org/10.31838/ijpr/2019.11.01.062
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Impact Factor for five years is 1.55 (2012 - 2016)

Year 2011 - 2015 Impact Factor - 1.46 Total Publications - 326 Total Citations - 477