Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.11851/1180
Title: Employing social network analysis for disease biomarker detection
Authors: Özyer, Tansel
Üçer, Serkan
İyidoğan, Taylan
143116
Keywords: Social Networks
Sna
Social Network Analysis
Cancer Biomarkers
Genomic Data
Feature Elimination
Issue Date: 2015
Publisher: Inderscience Enterprises Ltd.
Source: Á-zyer, T., Ucer, S., & Iyidogan, T. (2015). Employing social network analysis for disease biomarker detection. International journal of data mining and bioinformatics, 12(3), 343-362.
Abstract: Detection of disease biomarkers in general and cancer biomarkers in particular is an important task which has received considerable attention in the area of in silico genomic experiments. We describe a new approach for detecting cancer biomarkers based on genomic microarray data; it is characterised by employing Social Network Analysis (SNA) techniques. Through social interaction perspective, we can have genes as actors in a social network, where similarities between genes can be described as connections between these actors. The correct determination of biomarkers out of huge genomic data dramatically decreases the number of features. It is also possible to achieve the same or better classification performance compared to using the whole data. The minimum number of biomarkers can be researched further biologically to reduce the numerous time-consuming in vitro experiments. Results of the conducted experiments with selected biomarkers are promising and efficient.
URI: http://www.inderscience.com/offer.php?id=69661
https://hdl.handle.net/20.500.11851/1180
ISSN: 1748-5673
Appears in Collections:Bilgisayar Mühendisliği Bölümü / Department of Computer Engineering
PubMed İndeksli Yayınlar Koleksiyonu / PubMed Indexed Publications Collection
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection

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