The inference of gene co-expression networks of breast and colon cancer using miRNA-target gene interactions data

Determination of disease related biological processes and the estimation of molecular interactions related to these processes are important to understand the underlying mechanism of diseases. In our study we infer gene co-expression networks of breast and colon cancer using miRNA-target gene interac...

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Bibliographic Details
Published in:	2017 25th Signal Processing and Communications Applications Conference (SIU) pp. 1 - 4
Main Authors:	Cingiz, Mustafa Ozgur, Diri, Banu
Format:	Conference Proceeding
Language:	English
Published:	IEEE 01.05.2017
Subjects:	Algorithm design and analysis Bioinformatics Breast Cancer gene co-expression networks gene network inference algorithms Inference algorithms miRNA-target gene interactions Proteins
Online Access:	Get full text
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Summary:	Determination of disease related biological processes and the estimation of molecular interactions related to these processes are important to understand the underlying mechanism of diseases. In our study we infer gene co-expression networks of breast and colon cancer using miRNA-target gene interactions. Popular information theory based gene network inference algorithms are utilized to infer gene co-expression networks. Literature data, which is used as validation data in overlap analysis, is used to measure the performances of gene network inference algorithms. According to the results, the precision values of gene co-expression networks of two cancers are close to each other. Our study also states that the relevance calculation methods of gene-gene interactions at the first step of gene network inference algorithms don't change the performance results of gene co-expression networks.
DOI:	10.1109/SIU.2017.7960684