简介：Algorithmsusedindataminingandbioinformaticshavetodealwithhugeamountofdataefficiently.Inmanyapplications,thedataaresupposedtohaveexplicitorimplicitstructures.Todevelopefficientalgorithmsforsuchdata,wehavetoproposepossiblestructuremodelsandtestifthemodelsarefeasible.Hence,itisimportanttomakeacompactmodelforstructureddata,andenumerateallinstancesefficiently.Therearefewgraphclassesbesidestreesthatcanbeusedforamodel.Inthispaper,weinvestigatedistance-hereditarygraphs.Thisclassofgraphsconsistsofisometricgraphsandhencecontainstreesandcographs.First,acanonicalandcompacttreerepresentationoftheclassisproposed.Thetreerepresentationcanbeconstructedinlineartimebyusingprefixtrees.Usually,prefixtreesareusedtomaintainasetofstrings.Inouralgorithm,theprefixtreesareusedtomaintaintheneighborhoodofvertices,whichisanewapproachunlikethelexicographicallybreadth-firstsearchusedinotherstudies.Basedonthecanonicaltreerepresentation,efficientalgorithmsforthedistance-hereditarygraphsareproposed,includinglineartimealgorithmsforgraphrecognitionandgraphisomorphismandanefficientenumerationalgorithm.Anefficientcodingforthetreerepresentationisalsopresented;itrequires[3.59n]bitsforadistance-hereditarygraphofnverticesand3nbitsforacograph.Theresultsofcodingimprovepreviouslyknownupperbounds(bothare2~(O(nlogn)))ofthenumberofdistance-hereditarygraphsandcographsto2~([3.59n])and2~(3n),respectively.

简介：蛋白质合拢问题是生物信息学的最突出的问题之一。在这篇论文，我们与单体的二种学习一个三维的关闭,关,断开,截止格子蛋白质AB模型，恐水病；吸水，；介绍一个启发式的伪物理的算法。由精心地在物理世界上模仿光滑的有弹性的球的运动，算法为给定的单体链发现低精力的配置。一个随后的“关闭,关,断开,截止陷井”策略被建议被触发一为一种粘住的状况的jump以便从本地最小出来。方法在关闭,关,断开,截止格子AB模型被测试了。计算结果显示出有希望的性能。为有13～55单体的所有序列，算法比以前建议的通常认为的接地状态与更低的精力发现状态。而且为有21的序列，34；55单体，新通常认为的接地状态被发现，它与在现在的文学给的那些不同。