/home/leansigm/public_html/components/com_easyblog/services<title>Social Network Analysis Identifies Cancer Biomarkers</title>
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	<h1>Social Network Analysis Identifies Cancer Biomarkers</h1>
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			<span class="post-date">Jun 19</span>

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				Posted by <a href="/forum/user/431-nitin-sinha">Nitin Sinha</a>				in <a href="/resources/sigmaway-blog/analytics">Analytics</a>			</span>
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	<p><span style="font-family: Calibri, sans-serif; font-size: 13.3333330154419px;">Growing social networks have caused rapid development of tools for understanding the interactions between members of the network. The Department of Computer Engineering, at TOBB University, in Ankara, Turkey used Social Network Analysis (SNA) tools to identify the biomarkers present in patient genomic data. Genomic databases comprise of about 20000 genes. Such an approach dramatically decreased the features that need to be analyzed to find useful biomarkers. The team demonstrated their proof of principle with three types of cancer: lymphoma, colon cancer and leukemia. They combined clustering and classification to help in detecting the links between the various genes to validate the outcome. Now they shall extend it with a view to improve diagnostics and tailoring therapy for individual patients based on their personal Biological Network Analysis. Read more at:&nbsp;</span><a href="http://medicalxpress.com/news/2015-06-social-networking-analysis-cancer-biomarkers.html" target="_blank" style="color: purple; font-size: 14.6666669845581px; font-family: Calibri, sans-serif;">http://medicalxpress.com/news/2015-06-social-networking-analysis-cancer-biomarkers.html</a></p></div>

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		<a href="/blog/tags/data-analytics-1">
		<span itemprop="keywords">Data analytics</span>
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		<a href="/blog/tags/social-network-analysis">
		<span itemprop="keywords">social network analysis</span>
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		<a href="/blog/tags/cancer">
		<span itemprop="keywords">cancer</span>
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		<a href="/blog/tags/biomarkers">
		<span itemprop="keywords">Biomarkers</span>
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		<a href="/blog/tags/healthcare">
		<span itemprop="keywords">healthcare</span>
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