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		<title>Hidden Math Toolkit Could Reshape How We Model Evolution</title>
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				<category><![CDATA[Biology]]></category>
		<category><![CDATA[computational probability]]></category>
		<category><![CDATA[evolutionary biology]]></category>
		<category><![CDATA[gene family evolution]]></category>
		<category><![CDATA[likelihood]]></category>
		<category><![CDATA[Markov]]></category>
		<category><![CDATA[Markov modulated models]]></category>
		<category><![CDATA[matrix-analytic]]></category>
		<category><![CDATA[matrix-analytic methods]]></category>
		<category><![CDATA[phase-type distributions]]></category>
		<category><![CDATA[phylogenetic inference]]></category>
		<category><![CDATA[quasi-birth-and-death processes]]></category>
		<category><![CDATA[stochastic fluid models]]></category>
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					<description><![CDATA[A new perspective argues that a rich class of probability models known as Markov modulated models could transform how evolutionary biologists model gene families, species trees, and traits, but only through close collaboration between probabilists and biologists.]]></description>
		
		
		
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