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Paper Details


Title
Mining and predicting protein-drug interaction network of breast cancer risk genes
Author
Muhammad Nahidul Islam, Bikash Kumar Paul, Shams Shah Shaolin, Touhid Bhuiyan,
Email
bikash.swe@diu.edu.bd
Abstract

Background and objective

The increasing number of patients of Breast Cancer (BC) is a matter of concern all around the world. There isn't any specific reason behind this disease to be occurred in the human body. But there are such diseases which are counted as a risk factor of BC. Atypical Hyperplasia (AH) and Lobular Carcinoma in SITU (LCIS) are two of them. In this research we have collected the gene list of BC, AH and LCIS from the NCBI gene database and then our target was to find out the common genes among them by implementing an intersecting program.

Method

Then we used those intersected data to construct and analyze the Protein-Protein Interaction Network (PPIN), Protein-drug interaction network and so on. After the end of this we have got the most common fundamental genes associated with these diseases, the interrelated interaction networks of this 3 disease that will help us to better understand the common gene structure of them.

Results

We have got a drug signature suggestion for the hub proteins in the PDI network. From PPIN, 9 most responsible hub genes are obtained. Finally, following the PDI network, 4 of those hub genes were selected where several drug molecules from DRUGBANK were suggested for each hub gene.

Conclusions

In future by implementing further studies and analyzing those gene structures, it may be able to notify us to take precautionary steps to reduce the risk of BC.

Keywords
Breast cancer Atypical hyperplasia Lobular carcinoma in SITU Bioinformatics Data mining methods Drug-protein interaction network
Journal or Conference Name
Gene Reports
Publication Year
2020
Indexing
scopus