Inthepost-genomicera,identificationofspecificregulatorymotifsortranscrip-tionfactorbindingsites(TFBSs)innon-codingDNAsequences,whichisessentialtoelucidatetranscriptionalregulatorynetworks,hasemergedasanobstaclethatfrustratesmanyresearchers.Consequently,numerousmotifdiscoverytoolsandcorrelateddatabaseshavebeenappliedtosolvingthisproblem.However,theseexistingmethods,basedondifferentcomputationalalgorithms,showpersemotifpredictionefficiencyinnon-codingDNAsequences.Therefore,understandingthesimilaritiesanddifferencesofcomputationalalgorithmsandenrichingthemotifdiscoveryliteraturesareimportantforuserstochoosethemostappropriateoneamongtheonlineavailabletools.Moreover,therestilllackscrediblecriteriontoassessmotifdiscoverytoolsandinstructionsforresearcherstochoosethebestaccordingtotheirownprojects.Thusintegrationoftherelatedresourcesmightbeagoodapproachtoimproveaccuracyoftheapplication.Recentstudiesintegrateregulatorymotifdiscoverytoolswithexperimentalmethodstoofferacomplemen-taryapproachforresearchers,andalsoprovideamuch-neededmodelforcurrentresearchesontranscriptionalregulatorynetworks.HerewepresentacomparativeanalysisofregulatorymotifdiscoverytoolsforTFBSs.