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									<identifier>oai:www.peertechzpublications.org:10.17352/ojbb.000003</identifier>
									<datestamp>2017-06-27</datestamp>
									<setSpec>PTZ.OJBB:VOL1</setSpec>
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										<dc:title>
										Causality in Genomics Studies: Time is ripe for a new Paradigm
										</dc:title><dc:creator>Ahmed Rebai</dc:creator><dc:description>&lt;p class="bodyText"&gt;&lt;span lang="EN-US"&gt;Biological sciences have been for so long
dominated by observational approaches&lt;/span&gt;&lt;span dir="RTL"&gt;&lt;/span&gt;&lt;span dir="RTL"&gt;&lt;/span&gt;&lt;span dir="RTL" style="font-family:&amp;quot;Gautami&amp;quot;,sans-serif;mso-ascii-font-family:
Georgia;mso-hansi-font-family:Georgia;mso-bidi-font-family:Gautami;mso-bidi-theme-font:
minor-bidi" lang="EN-US"&gt;&lt;span dir="RTL"&gt;&lt;/span&gt;&lt;span dir="RTL"&gt;&lt;/span&gt; &lt;/span&gt;&lt;span lang="EN-US"&gt;as
shown by the scarcity of studies trying to infer causality from association,
starting from the historical and very instructive studies of Pierre Louis
(1835) on the efficacy of the standard treatments for pneumonia and John Snow
(1855) on the causal relationship between cholera and water contamination &lt;/span&gt;&lt;span style="color:#C00000" lang="EN-US"&gt;[1]&lt;/span&gt;&lt;span lang="EN-US"&gt;.&lt;/span&gt;&lt;/p&gt;</dc:description>
										<dc:publisher>Open Journal of Bioinformatics and Biostatistics - Peertechz Publications</dc:publisher>
										<dc:date>2017-06-27</dc:date>
										<dc:type>Review Article</dc:type>
										<dc:identifier>https://doi.org/10.17352/ojbb.000003</dc:identifier>
										<dc:language>en</dc:language>
										<dc:rights>Copyright © Ahmed Rebai et al.</dc:rights>
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