<?xml version="1.0" encoding="UTF-8"?>
<XML><RECORDS>
<RECORD>
	<REFERENCE_TYPE>31</REFERENCE_TYPE>
	<AUTHORS>
		<AUTHOR>C. Ryan*</AUTHOR>
		<AUTHOR>G. Cagney*</AUTHOR>
		<AUTHOR>N. Krogan*</AUTHOR>
		<AUTHOR>P. Cunningham</AUTHOR>
		<AUTHOR>D. Greene</AUTHOR>
	</AUTHORS>
	<YEAR>9998</YEAR>
	<TITLE>Imputing and predicting quantitative genetic interactions in epistatic MAPs</TITLE>
	<SECONDARY_TITLE>Network Biology: Methods and Protocols</SECONDARY_TITLE>
	<KEYWORDS>
		<KEYWORD>bioinformatics,emaps,imputation,krogan</KEYWORD>
	</KEYWORDS>
	<ABSTRACT>&lt;p&gt;Epistatic miniarray profiles (E-MAPs) are a high-throughput approach capable of quantifying aggravating or alleviating genetic interactions between gene pairs. The datasets resulting from E-MAP experiments typically take the form of a symmetric pairwise matrix of interaction scores. These datasets have a significant number of missing values - up to 35% - that can reduce the effectiveness of some data analysis techniques and prevent the use of others.&lt;/p&gt;</ABSTRACT>
</RECORD>
</RECORDS></XML>