python外文文献.docx
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python外文文献.docx
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python外文文献
apythonEnvironmentforTreeExploration
ReviewedbyJaimeHuerta-Cepas,correspondingauthor1JoaquínDopazo,2andToniGabaldóncorrespondingauthor1
Abstract
Manybioinformaticsanalyses,rangingfromgeneclusteringtophylogenetics,producehierarchicaltreesastheirmainresult.Theseareusedtorepresenttherelationshipsamongdifferentbiologicalentities,thusfacilitatingtheiranalysisandinterpretation.Anumberofstandaloneprogramsareavailablethatfocusontreevisualizationorthatperformspecificanalysesonthem.However,suchapplicationsarerarelysuitableforlarge-scalesurveys,inwhichahigherlevelofautomationisrequired.Currently,manygenome-wideanalysesrelyontree-likedatarepresentationandhencethereisagrowingneedforscalabletoolstohandletreestructuresatlargescale.
Keywords:
Python,spikingneurons,simulation,integrateandfire,teaching,neuralnetworks,computationalneuroscience,software
Background
HerewepresenttheEnvironmentforTreeExploration(ETE),apythonprogrammingtoolkitthatassistsintheautomatedmanipulation,analysisandvisualizationofhierarchicaltrees.ETElibrariesprovideabroadsetoftreehandlingoptionsaswellasspecificmethodstoanalyzephylogeneticandclusteringtrees.Amongotherfeatures,ETEallowsfortheindependentanalysisoftreepartitions,hassupportfortheextendednewickformat,providesanintegratednodeannotationsystemandpermitstolinktreestoexternaldatasuchasmultiplesequencealignmentsornumericalarrays.Inaddition,ETEimplementsanumberofbuilt-inanalyticaltools,includingphylogeny-basedorthologypredictionandclustervalidationtechniques.Finally,ETE'sprogrammabletreedrawingenginecanbeusedtoautomatethegraphicalrenderingoftreeswithcustomizednode-specificvisualizations.
Conclusions
ETEprovidesacompletesetofmethodstomanipulatetreedatastructuresthatextendscurrentfunctionalityinotherbioinformatictoolkitsofamoregeneralpurpose.ETEisfreesoftwareandcanbedownloadedfromarecommonlyusedtorepresenttheresultsofmanybioinformaticsanalyses.Inparticular,suchtypeofbinarygraphsareidealtodescribethehierarchicalrelationshipsamongavarietyofbiologicalentities.Somecommonexamplesaretheevolutionaryanalysisofmolecularsequencesortheclusterizationofgenesandproteinsaccordingtotheirproperties.Besidestheinformationencodedinthetopologyoftrees,branchlengthscanalsobescaledtoprovideinformationonthedistancesbetweenthedifferentpartitions.Inphylogenetics,forinstance,treesareusedtoillustratetheevolutionaryrelationshipsamongspeciesormolecularsequences,consideringterminalnodesasextantOperationalTaxonomicUnits(OTU)andinternalnodesastheircorrespondingancestors.Insuchphylogenetictrees,branchlengthsareusuallyproportionaltotheevolutionarydistanceamongsequences.Otherapplications,suchastheanalysisofgeneexpression,usehierarchicalclusteringanalysistogroupgenesorexperimentalconditionsaccordingtothesimilarityoftheirexpressionpatterns.Likewise,treesareusedbymanyproteinclassificationmethodsandfortheanalysisofphylogeneticprofiles.Thus,theanalysisoftreedatastructuresisacommontaskinmanyareasofbioinformaticsandthereisaneedforanalyticalandvisualizationtools.Inthisrespect,anumberofbioinformaticprogramsdoexistthatassistintheexplorationofhierarchicaltrees.Mostofthem,however,consistofstandaloneapplicationsthatarefocusedonvisualizationand,occasionally,onperformingspecifictests.SomewellknownexamplesareTreeView[1],awidelyusedprogramforinspectingphylogenetictrees;ClusterTreeview[2],anapplicationforvisualizingmicroarrayclusteringresults;ATV[3],ajavaprogramusedtoexplorephylogenieswhichprovidesalsosomeeditingoptions;MEGA[4],anevolutionarygeneticsanalysissuitethatincludesabuilt-intreeviewer;andmanyotherrecentapplications[5-8].Whilealltheseprogramsareveryusefultomanagesingletrees,theycanhardlybeautomatizedoradaptedtospecificneeds.Thus,whentheanalysisofhundredsorthousandsoftreesisrequired,theuseofstandaloneprogramsbecomesrestrictive,becauseamuchhigherlevelofautomationisrequired.Insuchcases,programmingtoolkitsrepresentamoreadequateframework,sincetheyprovidetoolsandmethodstohandledataatalowerlevel.Usingtoolkits,bioinformaticianscaneasilycreatetheirownanalysispipelinesandprogramcustomtasksoverlargecollectionsofdata[9].Severalgenericbioinformatictoolkitsdoexistthatcoverawiderangeofprogramminglanguagesandscopes,withBioPerl[10]andBioPython[11]beingthemostextensivelydeveloped.Togetherwithabroadrangeofotherfeatures,thesetoolkitsallowcertainlevelofintera
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