一种基于统计生物网络模体发现算法

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1、AbstractIn2003,theHumanGenomeProjecthasbeencompleted,andwehaveenteredthepost-genomicera.Interactionnetworksareofcentralimportanceinpost-genomicmolecularbiology,withincreasingamountofdatabecomingavailablebyhigh-throughputmethods.Examplesaregeneregulatorynetworksorproteininte

2、ractionmaps.Themainchallengeintheanalysisofthesedataistoreadoffbiologicalfunctionsfromthetopologyofthenetwork.Topologicalmotifs,i.e,patternsoccurringrepeatedlyatdifferentpositionsinthenetworkhaverecentlybeenidentifiedasbasicmodulesofmolecularinformationprocessing.Inthispape

3、r,wediscussmotifsderivedfromfamiliesofmutuallysimilarbutnotnecessarilyidenticalpatterns.Weestablishastatisticalmodelfortheoccurrenceofsuchmotifs,fromwhichwederiveascoringfuctionfortheirstatisticalsignificance.Thealgorithmistostartwithamethodthatefficientlyenumeratesallsize-

4、knontreelikegraphs.Thenbasedonthescoringfunction,wederivethetopologicalmotifs.Experimentalevaluationonrealbiologicalnetworksdatafromvariousdomainsshowsthatouralgorithmachievesgoodperformance.Keyword:BiologicalNetworksNetworkMotifSubgraphMining目录第一章绪论........................

5、.............................................................................................31.1研究背景...........................................................................................................31.2生物网络模体发现的研究现状与动态..............................................

6、.............51.3本文的研究工作和论文结构............................................................................6第二章图论与生物网络简介.........................................................................................72.1图的相关定义.........................................................

7、...........................................72.1.1网络的图表示.........................................................................................72.1.2图的同构与重叠.....................................................................................72.1.3度与度分布.....................

8、........................................................................82.1.4几种随机