acm bcb 2016 7th acm conference on...

ACM-BCB 2016

The 7th ACM Conference on Bioinformatics , Computational Biology , and Health Informatics

October 2-5, 2016

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OrganizingCommitteeGeneralChairs:ÜmitV.Çatalyürek,GeorgiaInstituteofTechnologyGenevieveMelton-Meaux,UniversityofMinnesotaProgramChairs:JohnKececioglu,UniversityofArizonaAdamWilcox,UniversityofWashingtonWorkshopChair:AnanthKalyanaraman,WashingtonStateUniversityTutorialChair:MehmetKoyuturk,CaseWesternReserveUniversityDemoandExhibitChair:Robert(Bob)Cottingham,OakRidgeNationalLaboratoryPosterChairs:LinYang,UniversityofFloridaDongxiaoZhu,WayneStateUniversityRegistrationChair:PreetamGhosh,VirginiaCommonwealthUniversityPublicityChairsDanielCapurro,PontificiaUniv.CatólicadeChileA.ErcumentCicek,BilkentUniversityPierangeloVeltri,U.MagnaGraeciaofCatanzaroStudentTravelAwardChairsMayD.Wang,GeorgiaInstituteofTechnologyandEmoryUniversityJaroslawZola,UniversityatBuffalo,TheStateUniversityofNewYorkStudentActivityChairMarziehAyati,CaseWesternReserveUniversityDanDeBlasio,CarnegieMellonUniversityProceedingsChairs:XinghuaMindyShi,UofNorthCarolinaatCharlotteYangShen,TexasA&MUniversityWebAdmins:AnasAbu-Doleh,TheOhioStateUniversityHyunAnderson,TheOhioStateUniversityJonathanKho,GeorgiaInstituteofTechnology

SteeringCommittee:AidongZhang,StateUniversityofNewYorkatBuffalo,Co-ChairMayD.Wang,GeorgiaInstituteofTechnologyandEmoryUniversity,Co-ChairSrinivasAluru,GeorgiaInstituteofTechnologyTamerKahveci,UniversityofFloridaChristopherC.Yang,DrexelUniversity

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ACM-BCB2016ProgramREGISTRATIONSunday7:30–16:00/Monday-Tuesday8:00–16:00/Wednesday8:00–11:00

Sunday,October2,2016

8am ContinentalBreakfastLocation:FourthFloorBreakstation

Seattle1 Seattle2 Seattle3 Belltown Pioneer FirstHill EmeraldII8:25am

BigLS(8:25am–12pm)

(1:30pm–5pm)

MAHA(8:25am–11:40am)(1:30pm–

5pm)

pSALSA(8:25am–12pm)

(1:30pm–5:30pm)

Tutorial1(T1)

CNB-MAC(8:50am–12pm)

(1:20pm–6pm)

TDA-Bio(8:50am–12:05pm)(1:30pm–5:15pm)

10am ParBio(10am–12pm)

Tutorial2(T2)

12pm 1pm BrainKDD

(1pm–5pm)

Tutorial3(T3)

4pm Tutorial4(T4)

6pm StudentNetworkingandSocialEventattheSeattleGreatWheelMeetatthepre-eventspaceonthe4thfloor

WORKSHOPS*CNB-MAC 3rdInternationalWorkshoponComputationalNetworkBiology:Modeling,Analysis,andControl

Organizers:Byung-JunYoon,XiaoningQianandTamerKahveci

BigLS 4thACMInternationalWorkshoponBigDatainLifeSciencesOrganizers:JaroslawZolaandAnanthKalyanaraman

MAHA 1stInternationalWorkshoponMethodsandApplicationsinHealthcareAnalyticsOrganizers:FeiWang,JyotishmanPathakandNigamShah

pSALSA 3rdWorkshoponParallelSoftwareLibrariesforSequenceAnalysisOrganizers:SrinivasAluru

TDA-Bio 1stInternationalWorkshoponTopologicalDataAnalysisinBiomedicineOrganizers:BalaKrishnamoorthyandBeiWangPhillips

ParBio 5thInternationalWorkshoponParallelandCloud-basedBioinformaticsandBiomedicineOrganizers:MarioCannataroandJohnA.Springer

BrainKDD The3rdInternationalWorkshoponDataMiningandVisualizationforBrainScienceOrganizers:ShuiwangJi,LeiShi,HanghangTong,ShuaiHuangandPaulThompson

*Seepage12fordetailedworkshopprograms.

TUTORIALS*Sunday,October28:30-9:30 T1:Combinatorialmethodsfornucleicacidsequenceanalysis

Presenters:SreeramKannanandMarkChaisson,UniversityofWashington10:00-12:00 T2:NetworkSciencemeetsTissue-specificBiology

Presenters:ShahinMohammadiandAnanthGrama,PurdueUniversity1:30-3:30pm T3:BigDataforDiscoveryScience

Presenters:BenHeavner(InstituteforSystemsBiology),RaviMadduri(ArgonneNationalLab),JackVanHorn(UniversityofSouthernCalifornia),andNaveenAshish(FredHutchinsonCancerResearchCenter)

4:00-6:00pm T4:DeepLearningforBioinformaticsandHealthInformatics Presenter:SungrohYoon,SeoulNationalUniversity

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Monday,October3(SeattleII)11:00-12:00pm T5:Data-DrivenAnalysisofUntargetedMetabolomicsDatasets

Presenter:SohaHassoun,TuftsUniversity 1:30-3:30pm T6:EvolutionaryAlgorithmsforProteinStructureModeling

Presenters:EmmanualSapin,AmardaShehu,andKennethDeJong,GeorgeMasonUniversity

Tuesday,October4(SeattleII)10:00-12:00pm T7:TheISBCancerGenomicsCloud

Presenter:SheilaReynolds,InstituteforSystemsBiology 1:30-3:30pm T8:LivingtheDREAM:Crowdsourcingbiomedicalresearchthroughchallengesandensembles

Presenters:GauravPandey,LaraMangravite,SolveigSieberts,RobertVogel,andGustavoStolovitzky,IcahnSchoolofMedicineatMountSinai,SAGEBionetworks

*Seepage19formoreinformationonindividualtutorials.

StudentNetworkingandSocialEventAllstudentsandpostdocsareinvitedtothestudent-networkingevent,whichwillbeheldSundayat6pm.ThisyeartheeventwillincludeanexcursiontoTheSeattleGreatWheel(thelargestobservationwheelonthewestcoast).Thestudentactivityisfocusedondevelopingprogramsforstudentgrowththrougheducationalandnetworkingopportunities.Thisisthesecondyearofarecognizedstudentactivityandlastyearimprovedthestudentrelationshipsduringtheconference.Theeventwillbeginat6:00PMonSunday,October2,2016withscientificspeednetworkinginthepre-eventspaceonthe4thfloorbeforetheshortwalktoElliotBay.(ThenetworkingeventisfreebutpleasebringcashforadiscountedadmissiontotheGreatWheel.)

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Monday,October3,20168:00–10:00

ContinentalBreakfastLocation:FourthFloorBreakstation

8:15–8:30

OpeningRemarks (Location:SeattleI&II)GeneralChairs:ÜmitV.Çatalyürek,GeorgiaInstituteofTechnology&

GenevieveMelton-Meaux,UniversityofMinnesotaProgramChairs:JohnKececioglu,UniversityofArizona&AdamWilcox,UniversityofWashington

8:30–9:30

KeynoteTalk1 (Location:SeattleI&II)Don’tforgetthenotes:WhyNLPiskeytohealthcaretransformation

WendyW.Chapman,UniversityofUtahSessionChair:GenevieveMelton-Meaux,UniversityofMinnesota

9:30–10:00 MorningBreak

Session1ALocation:SeattleISystemsBiology

SessionChair:AnnaRitz,ReedCollege

Session1BLocation:SeattleII

DemoPresentations&TutorialsSessionChair:RobertW.Cottingham,

OakRidgeNationalLaboratory

Session1CLocation:SeattleIII

AutomatedDiagnosisandPrediction

SessionChair:JaroslawZola,UniversityatBuffalo

10:00–12:00

10:00TinNguyen,DianaDiaz,SorinDraghici.“TOMAS:AnovelTOpology-awareMeta-AnalysisapproachappliedtoSystembiology”

10:30HueyEngChua,SouravS.Bhowmick,JieZheng,LisaTucker-Kellogg.“TAPESTRY:Network-centricTargetPrioritizationinDisease-relatedSignalingNetworks”

11:00 AisharjyaSarkar,YuanfangRen,RashaElhesha,TamerKahveci.“Countingindependentmotifsinprobabilisticnetworks”

11:30PaolaPesantez-Cabrera,AnanthKalyanaraman.“DetectingCommunitiesinBiologicalBipartiteNetworks”

DemoPresentations10:00“Softwaretoolsforsequencecomparison,sequencemapping,andpatient-specifichealthcareoutcomeprediction”.Presenter:AnkitAgrawal,NorthwesternUniversity

10:20“TheCMHVariantWarehouse–ACatalogofGeneticVariationinPatientsofaChildren’sHospital".Presenter:ByunggilYoo,Children’sMercyHospital

10:40“KBase:DevelopingcollaborativeanalysesofbiologicalfunctionusingNarrativesandAppCatalog”.Presenter:RobertW.Cottingham,OakRidgeNationalLaboratory

10:00Shou-HsuanStephenHuang,Ming-ChihShih,YouliZu.“AMulti-ObjectiveFlowCytometryProfilingforB-CellLymphomaDiagnosis”

10:30YingSha,JananiVenugopalan,MayD.Wang.“ANovelTemporalSimilarityMeasureforPatientsBasedonIrregularlyMeasuredDatainElectronicHealthRecords”

11:00AydinSaribudak,AdarshaA.Subick,JoshuaA.Rutta,M.ÜmitUyar,“TheAlzheimer'sDiseaseNeuroimagingInitiative.GeneExpressionBasedComputationMethodsforAlzheimer'sDiseaseProgressionusingHippocampalVolumeLossandMMSEScores”

11:30QiulingSuo,HongfeiXue,JingGao,AidongZhang.“Riskfactoranalysisbasedondeeplearningmodels”

Tutorial

11:00T5:Data-DrivenAnalysisofUntargetedMetabolomicsDatasetsPresenter:SohaHassoun,TuftsUniversity

12:30–13:30

Lunch(Onyourown)

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Session2ALocation:SeattleIBiologicalModeling

SessionChair:TamerKahveci,UniversityofFlorida


Tutorials


ApplicationstoHealthcareProcessesSessionChair:BethBritt,UniversityofWashington

13:30–15:30

13:30HanyuJiang,MorisaManzella,LukaDjapic,NarayanGanesan.“ComputationalFrameworkforin-SilicoStudyofVirtualCellBiologyviaProcessSimulationandMultiscaleModeling”

14:00MuhiburRasheed,NathanClement,AbhishekBhowmick,ChandrajitBajaj.“StatisticalFrameworkforUncertaintyQuantificationinComputationalMolecularModeling”

14:30JeetBanerjee,TanviRanjan,RitwikKumarLayek.“StabilityAnalysisofPopulationDynamicsModelinMicrobialBiofilmswithNon-participatingStrains”

15:00ShuoWang,MansoorehAhmadian,MinghanChen,JohnTyson,YoungCao.“AHybridStochasticModeloftheBuddingYeastCellCycleControlMechanism”

T6:EvolutionaryAlgorithmsforProteinStructureModelingPresenters:EmmanualSapin,AmardaShehu,andKennethDeJong,GeorgeMasonUniversity

13:30ShitalKumarMishra,SouravS.Bhowmick,HueyEngChua,JieZheng.Predictive“ModelingofDrugEffectsonSignalingPathwaysinDiverseCancerCellLines”

14:00QianCheng,JingboShang,JoshuaJuen,JiaweiHan,BruceSchatz.“MiningDiscriminativePatternstoPredictHealthStatusforCardiopulmonaryPatients”

14:30PaulD.Martin,MichaelRushanan,ThomasTantillo,ChristophLehmann,AvielD.Rubin.“ApplicationsofSecureLocationSensinginHealthcare”

15:00SaiNiveditaChandrasekaran,AlexiosKoutsoukas,JunHuan.“InvestigatingMultiviewandMultitaskLearningFrameworksforPredictingDrug-DiseaseAssociations”

15:30–16:00 AfternoonBreak–RefreshmentsProvided

16:00–18:00

ACMSIGBioGeneralMeetingLocation:SeattleI&II

18:00–20:00

PosterReception–Lighthorsd'oeuvres&Cashbar(seepage21forlistofposters)

DEMOS(Belltown)“Softwaretoolsforsequencecomparison,sequencemapping,andpatient-specifichealthcareoutcomeprediction”.Presenter:AnkitAgrawal,NorthwesternUniversity

“TheCMHVariantWarehouse–ACatalogofGeneticVariationinPatientsofaChildren’sHospital".Presenter:ByunggilYoo,Children’sMercyHospital

“KBase:DevelopingcollaborativeanalysesofbiologicalfunctionusingNarrativesandAppCatalog”.Presenter:RobertW.Cottingham,OakRidgeNationalLaboratory

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Tuesday,October4,20168:00–10:00


8:30–9:30

KeynoteTalk2 (Location:SeattleI&II)Anevolutionarybiologist'sskepticalsearchforcomputationalbiology

JosephFelsenstein,UniversityofWashingtonSessionChair:SrinivasAluru,GeorgiaInstituteofTechnology

9:30–10:00

MorningBreak

Session3ALocation:SeattleI

InferringPhylogeniesandHaplotypes

SessionChair:AnanthKalyanaraman,

WashingtonStateUniversity


Tutorials


TextMiningandClassificationSessionChair:XinghuaMindyShi,UniversityofNorthCarolinaat

Charlotte

10:00–12:00

10:00JucheolMoon,OliverEulenstein.“Robinson-FouldsMedianTrees:AClique-basedHeuristic”

10:30AlexeyMarkin,OliverEulenstein.“ManhattanPath-DifferenceMedianTrees”

11:00

MisaghKordi,MukulS.Bansal.“ExactAlgorithmsforDuplication-Transfer-LossReconciliationwithNon-BinaryGeneTrees”

11:30OliviaChoudhury,AnkushChakrabarty,ScottEmrich.“HAPI-Gen:HighlyAccuratePhasingandImputationofGenotypeData”

T7:TheISBCancerGenomicsCloudPresenter:SheilaReynolds,InstituteforSystemsBiology

10:00MajidRastegar-Mojarad,RavikumarKomandurElayavilli,LiweiWang,RashmiPrasad,HongfangLiu.“PrioritizingAdverseDrugReactionandDrugRepositioningCandidatesgeneratedbyLiterature-BasedDiscovery”

10:30KishlayJha,WeiJin.“MiningNovelKnowledgefromBiomedicalLiteratureusingStatisticalMeasuresandDomainKnowledge”

11:00RamakanthKavuluru,MariaRamos-Morales,TaraHoladay,AmandaG.Williams,LauraHaye,JulieCerel.“ClassificationofHelpfulCommentsonOnlineSuicideWatchForums”

11:30HaotianXu,MingDong,DongxiaoZhu,AlexanderKotov,AprilIdalskiCarcone,SylvieNaar-King.“TextClassificationwithTopic-basedWordEmbeddingandConvolutionalNeuralNetworks”

12:00–13:30

WomeninBioinformaticsPanelChair:MayD.Wang,

GeorgiaInstituteofTechnology&EmoryUniversity

Lunch (Onyourown)

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SequenceAnalysisandGenomeAssembly

SessionChair:OliverEulenstein,IowaStateUniversity


Tutorials


KnowledgeRepresentationApplications

SessionChair:NaveenaYanamala,CentersforDiseaseControland

Prevention

13:30–15:30

13:30RahulNihalani,SrinivasAluru.“EffectiveUtilizationofPairedReadstoImproveLengthandAccuracyofContigsinGenomeAssembly”

14:00PriyankaGhosh,AnanthKalyanaraman.“AFastSketch-basedAssemblerforGenomes”

14:30SubrataSaha,SanguthevarRajasekaran.“POMP:apowerfulsplicemapperforRNA-seqreads”

15:00TonyPan,PatrickFlick,ChiragJain,YongchaoLiu,SrinivasAluru.“Kmerind:AFlexibleParallelLibraryforK-merIndexingofBiologicalSequencesonDistributedMemorySystems”

T8:LivingtheDREAM:CrowdsourcingbiomedicalresearchthroughchallengesandensemblesPresenters:GauravPandey,LaraMangravite,SolveigSieberts,RobertVogel,andGustavoStolovitzky,IcahnSchoolofMedicineatMountSinai,SAGEBionetworks

13:30NaveenAshish,ArihantPatawari,SimratSinghChhabra,ArthurW.Toga.“NameSimilarityforCompositeElementNameMatching”

14:00EdwardWHuang,ShengWang,RunshunZhang,BaoyanLiu,XuezhongZhou,ChengXiangZhai.“PaReCat:PatientRecordSubcategorizationforPrecisionTraditionalChineseMedicine”

14:30MichaelR.WyattII,TravisJohnston,MiaPapas,MichelaTaufer.“DevelopmentofaScalableMethodforCreatingFoodGroupsUsingtheNHANESDatasetandMapReduce”

15:00ShahinMohammadi,AnanthGrama.“Denovoidentificationofcelltypehierarchywithapplicationtocompoundmarkerdetection”

15:30–16:00 AfternoonBreak–RefreshmentsProvided

16:00–17:30

NSFSponsoredStudentResearchForumLocation:SeattleI&II

17:30–19:00

Break(forbanquetsetup)CashBarat18:30

19:00–21:30

BanquetLocation:SeattleI,II&III

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Wednesday,October5,20168:00–10:00


8:30–9:30

KeynoteTalk3 (Location:SeattleI&II)Data,Predictions,andDecisionsEricHorvitz,MicrosoftResearch

SessionChair:ÜmitV.Çatalyürek,GeorgiaInstituteofTechnology9:30–10:00

MorningBreak


ProteinStructureandDynamicsSessionChair:SreeramKannan,Univ.ofWashington


ApplicationstoMicrobesandImagingGeneticsSessionChair:MarkClement,BrighamYoungUniv.

10:00–12:00

10:00DongSi.“AutomaticDetectionofBeta-barrelfromMediumResolutionCryo-EMDensityMaps”10:30TatianaMaximova,DanielCarr,ErionPlaku,AmardaShehu.“Sample-basedModelsofProteinStructuralTransitions”11:00DarioGhersi,RobertoSanchez.“RecoveringBoundFormsofProteinStructuresUsingtheElasticNetworkModelandMolecularInteractionFields”11:30RamuAnandakrishnan,MayankDaga,AlexeyOnufriev,Wu-ChunFeng.“MultiscaleApproximationwithGraphicalProcessingUnitsforMultiplicativeSpeedupinMolecularDynamics”

10:00JeffreyD.McGovern,EricJohnson,AlexDekhtyar,MichaelBlack,ChristopherKitts,JenniferVanderkelen.“Library-BasedMicrobialSourceTrackingviaStrainIdentification”10:30SergheiMangul,DavidKoslicki.“Reference-freecomparisonofmicrobialcommunitiesviadeBruijngraphs”11:00MdAshadAlam,OsamuKomori,VinceCalhoun,Yu-PingWang.“RobustKernelCanonicalCorrelationAnalysistoDetectGene-GeneInteractionforImagingGeneticsData”11:30MdAshadAlam,VinceCalhoun,Yu-PingWang.“InfluenceFunctionofMultipleKernelCanonicalAnalysistoIdentifyOutliersinImagingGeneticsData”

12:00–13:30

NoonBreak–RefreshmentsProvided


ProteinandRNAAnalysisSessionChair:JohnKececioglu,UniversityofArizona


AdvancingAlgorithmsandMethodsSessionChair:AdamWilcox,UniversityofWashington

13:30–15:30

13:30DeeptakVerma,GevorgGrigoryan,ChrisBailey-Kellogg.“OCoM-SOCoM:CombinatorialMutagenesisLibraryDesignOptimallyCombiningSequenceandStructureInformation”14:00ByunghanLee,JunghwanBaek,SeunghyunPark,SungrohYoon.“deepTarget:End-to-endLearningFrameworkformicroRNATargetPredictionusingDeepRecurrentNeuralNetworks”14:30NaozumiHiranuma,ScottLundberg,Su-InLee.“CloudControl:LeveragingmanypublicChIP-seqcontrolexperimentstobetterremovebackgroundnoise”15:00WenruoBai,JeffreyBilmes,WilliamS.Noble.“Bipartitematchinggeneralizationsforpeptideidentificationintandemmassspectrometry”

13:30SoumiRay,AdamWright.“DetectingAnomaliesinAlertFiringwithinClinicalDecisionSupportSystemsusingAnomaly/OutlierDetectionTechniques”14:00Chih-WenCheng,YingSha,MayD.Wang.“InterVisAR:AnInteractiveVisualizationforAssociationRuleSearch”

14:30LaxmiParida,NiinaHaiminen.“ScalableAlgorithmsatGenomicResolutiontofitLDDistributions”

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KeynotesMonday,October3|WendyW.Chapman,UniversityofUtah

Title:Don’tforgetthenotes:WhyNLPiskeytohealthcaretransformationAbstract:Themajorityofclinicalinformationusefulforpatientcareandresearchislockedinclinicalnotesandonlyaccessiblewithgreatpainandeffort.NaturalLanguageProcessinghasthepotentialtounlocktheinformationinthenotestosupportphenotypingforprecisionmedicine,qualityimprovement,andhealthservicesresearch.ThistalkwillillustratethepotentialofNLPthroughexistingapplications,willdescribethechallengesofmakingNLParealandscalablesolution,andwillprovideconcretesuggestionsforhowtheaudiencecanhelpNLPreachitspotentialinhealthcareanddiscovery.Biography: Dr. Chapman earned her Bachelor’s degree in Linguistics and her PhD inMedicalInformaticsfromtheUniversityofUtahin2000.From2000-2010shewasaNationalLibraryofMedicine postdoctoral fellow and then a facultymember at theUniversity of Pittsburgh. ShejoinedtheDivisionofBiomedicalInformaticsattheUniversityofCalifornia,SanDiegoin2010.In 2013,Dr. Chapmanbecame the chair of theUniversity ofUtah,Department of BiomedicalInformaticswhereshecontinuesherresearchonnaturallanguageprocessinginthecontextofinformaticssolutionstoproblemsthatvexhealthcare.

TuesdayOctober4|JosephFelsenstein,UniversityofWashington

Title:Anevolutionarybiologist'sskepticalsearchforcomputationalbiologyAbstract:Thistalkwillexplainhow,startingwithaninterestinbiology,andalsoincomputers,Igraduallylearnedhowtousecomputerstoilluminateproblemsinevolutionarybiology.AlongthewayIlearnedabouttheoreticalpopulationgenetics,learnedwhyitisnotalwaysbesttowriteyourtheoremsdown,andhowfascinationwithaproblemmayindicatethatsomethingmoreimportantisatstake.Imovedfromtheoreticalpopulationgeneticstoalgorithmsforinferringevolutionarytrees(phylogenies).Thestatisticalviewpointthatwasstandardintheoreticalpopulationgeneticsturnedouttobehighlycontroversialamongtaxonomistsstudyingevolution,andwasalsoconsideredunnecessarybycomputerscientists.Bothofthesegroupsofpeoplewerewrong.Iwillarguethatcomputerscientistsandbiologistsshouldindeedcommunicate,butthatthisisbestdoneviaastatistician.Iwillarguethataparametricmodelbasedonevolutionarytheoryiscrucial,butthatoneshouldbewareofbelievinginittoomuch.Computationisessentialinbiology,butIwonderwhethertherereallyisafieldcalledComputationalBiology.Oroughttobe..IntheeraofComplexSystemsandBigData,aSimpleSystemsperspectivebasedonSmallDatahasdistinctadvantages.Aswereachlimitsinwhatgenomedatacantellus,aconcernforefficientuseofthosedatawillbecomeimportant,andanunderstandingoftheeffectsofstatisticalnoisewillproveimportant,anditshouldencouragealittlemorehumility.Biography:JoeFelsensteingrewupinPhiladelphia,andattendedtheUniversityofWisconsin,wherehegotinvolvedwiththeoreticalpopulationgeneticsinthelabofJamesF.Crow.HewentontodohisPh.D.withRichardLewontinattheUniversityofChicago,andapostdoctoralfellowshipwithAlanRobertsonattheInstituteofAnimalGeneticsattheUniversityofEdinburgh.HehassincethenbeenafacultymemberoftheDepartmentofGeneticsattheUniversityofWashington,Seattle,anditssuccessortheDepartmentofGenomeSciences,andheisalsojointlyappointedintheDepartmentofBiology.Althoughhistrainingwasthusintheoreticalpopulationgenetics,sincehisgraduateworkhehasalsobeenfascinatedbythereconstructionofevolutionarytrees(phylogenies).Thisledhimtopromoteanddeveloplikelihoodmethodsforinferenceofphylogenies,toapplythebootstrapmethodtoinvestigatingwhichpartsofthemarewell-supported,andtoreleasethefirstgeneralprogrampackageforinferringphylogenies,PHYLIP,in1980.Hewishesthatcomputationalbiologytextbookswouldpaymoreattentiontophylogenies,whicharethebasicstructuresformakingsenseofmultispeciesdata.Hisworkinthisareahasalsoledhimintotheextremeandbyzantineconflictsinsystematics--someofhisclosestfriendshipsincomputationalphylogeneticswerecementedbysharedvictimization.Joehasreceivedanumberofverynicehonors,whicharelistedathisonlineCV,butwhichfalsemodestydictatesthathenotmentionhere.

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WednesdayOctober5|EricHorvitz,MicrosoftResearch

Title:Data,Predictions,andDecisionsAbstract:Iwilldescribeseveralprojectsthathighlightdirectionswiththeuseofmachinelearningtoenhancepatientcareandtobuildinsightsabouthealthandwellbeing.Iwillfirstpresentresearchonleveraginglargeamountsofdatadrawnfromelectronichealthrecordstopredictoutcomesandtoguidedecisions.Iwillfocusonopportunitieswithreducingreadmissionsandidentifyingpatientsatriskforhospital-associatedinfection,emphasizingthepromiseofcouplingpredictivemodelswithdecisionanalysis.Iwillreflectonchallengingdirectionswiththeseefforts,includingcausalinferenceandtransferlearning.Then,Iwillmovetostudiesofhealthandwell-beingfromnon-traditionalsourcesofdata,includingtheuseofanonymizedlogsofonlineactivities.Iwillpresentresultsonpharmacovigilance,detectingtheonsetofillness,andbuildingdeeperunderstandingsofepisodicinformationneedsofpatientsoverphasesofillness.I’llwrapupbydiscussingseveralaspirationaldirectionswithdata,predictions,anddecisions.Biography: Eric Horvitz is technical fellow at Microsoft, where he serves as director of theMicrosoftResearchlabatRedmond.Hisinterestsspantheoreticalandpracticalchallengeswithcomputingsystemsthat learnfromdataandthatcanperceive,reason,anddecide.Hiseffortsand collaborations have led to fielded systems in the areas of transportation, healthcare,ecommerce,andoperatingsystems.EricreceivedMDandPhDdegreesatStanfordUniversity.Hehasbeenelected fellowof theNationalAcademyofEngineering (NAE),AAAI,ACM,AAAS,and the American Academy of Arts and Sciences. He received the Feigenbaum Prize and theACM-AAAIAllenNewellAwardforhisresearchcontributions.HecurrentlyservesontheBoardofRegentsoftheNationalLibraryofMedicine,theComputerScienceandTelecommunicationsBoard (CSTB), and theadvisoryboard for theCenter forCausalDiscoveryat theUniversityofPittsburgh.Moreinformationcanbefoundathttp://research.microsoft.com/~horvitz.

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Workshops3rdInternationalWorkshoponComputationalNetworkBiology:Modeling,Analysis,andControl(CNB-MAC)8:45am-6pm,October2,2016Organizers:Byung-JunYoon,TexasA&MUniversityXiaoningQian,TexasA&MUniversityTamerKahveci,UniversityofFloridahttps://cnbmac.org/Next-generationhigh-throughputprofilingtechnologieshaveenabledmoresystematicandcomprehensivestudiesoflivingsystems.Networkmodelsplaycrucialrolesinunderstandingthecomplexinteractionsthatgovernbiologicalsystems,andtheirinteractionswithexternalenvironment.Theinferenceandanalysisofsuchcomplexnetworksandnetwork-basedanalysisoflarge-scalemeasurementdatahavealreadyshownstrongpotentialsforunveilingthekeymechanismsofcomplexdiseasesaswellasfordesigningimprovedtherapeuticstrategies.Atthesametime,theinferenceandanalysisofcomplexbiologicalnetworksposenewexcitingchallengesforcomputerscience,signalprocessing,control,andstatistics.TheCNB-MACworkshopaimstoprovideaninternationalscientificforumforpresentingrecentadvancesincomputationalnetworkbiologythatinvolvemodeling,analysis,andcontrolofbiologicalsystemsunderdifferentconditions,andsystem-orientedanalysisoflarge-scaleOMICSdata.08:50-9:00OpeningRemarks09:00-10:00KeynoteTalkbyDr.Su-InLee(Universityof

Washington),TalkTitle:MiningBigDataforMolecularMarkerIdentification

10:00-10:20 CoffeeBreak

10:20-12:00Session1“SparseFeatureSelectionforClassificationandPredictionofMetastasisinEndometrialCancer”,MehmetErenAhsen,ToddBoren,NitinSingh,BurookMisganaw,DavidMutch,KathleenMoore,FloorBackes,CarolynMcCourt,JayanthiLea,DavidMiller,MichaelWhiteandMathukumalliVidyasagar“DataRequirementsforModel-BasedCancerPrognosisPrediction”,LoriDaltonandMohammadmahdiRezaeiYousefi“Comparisonoftissue/diseasespecificintegratednetworksusingdirectedgraphletsignatures”,ArzuBurcakSonmezandTolgaCan“OptimalROC-basedClassificationandPerformanceAnalysisunderBayesianUncertaintyModels”,LoriDalton“SNPbySNPbyEnvironmentInteractionNetworkofAlcoholism”,AminZollanvariandGilAlterovitz12:00-13:20LunchBreak13:20-15:00Session2“Towardstargetedcombinatorialtherapydesignforthetreatmentofcastration-resistantprostatecancer”,OsamaArshadandAniruddhaDatta“Combinationtherapydesignformaximizingsensitivityandminimizingtoxicity”,KevinMatlock,NoahBerlow,CharlesKellerandRanadipPal“DIGNiFI:Discoveringcausativegenesfororphandiseasesusingprotein-proteininteractionnetworks”,XiaoxiaLiu,ZhihaoYang,HongfeiLin,MichaelSimmonsandZhiyongLu“SEQUOIA:Significanceenhancednetworkqueryingthroughcontext-sensitiverandomwalkandminimizationofnetworkconductance”,HyundooJeongandByung-JunYoon“FindingLow-ConductancesetswithDenseinteractions(FLCD)forbetterproteincomplexprediction”,YijieWangandXiaoningQian15:00-15:20CoffeeBreak15:20-16:40Session3“InferringMicrobialInteractionNetworksfromMetagenomicDataUsingSgLV-EKFAlgorithm”,MustafaAlshawaqfeh,AhmadBaniYounesandErchinSerpedin“StochasticModelingandSimulationofReaction-DiffusionSystemwithHillFunctionDynamics”,MinghanChen,FeiLi,ShuoWangandYangCao“InterpretiveTime-FrequencyAnalysisofGenomicSequences”,HamedHassaniSaadi,RezaSameniandAminZollanvari“ComprehensiveEvaluationofRNA-seqQuantificationMethodsforLinearity”,HaijingJin,Ying-WooiWanandZhandongLiu16:40-17:05Five-MinuteLightningTalksforPosters17:05-17:50PosterSession17:50-18:00ClosingRemarks

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4thACMInternationalWorkshoponBigDatainLifeSciences(BigLS)8:25am-5:30pm,October2,2016Organizers:JaroslawZola,SUNYBuffaloAnanthKalyanaraman,WashingtonStateUniversityhttp://www.bigls.orgTheever-growingvolumeanddiversityofbiologicalandbiomedicaldatacollectionscontinuestoposenewchallengesandincreasingdemandsoncomputinganddatamanagement.TheinherentcomplexityofthisBigDataforcesustorethinkhowwecollect,store,combineandanalyzeit.BigLSisaworkshopseriesdedicatedtothebroadthemeofBigDatainlifesciences.ThegoaloftheworkshopistobringtogetherleadingresearchersandpractitionersworkingonadiverserangeofBigDataproblemsrelatingtobiologyandmedicine,andengagetheminadiscussionaboutcurrentBigDataproblems,thestateofcomputationaltoolsandanalytics,thechallengesandthefuturetrendswithinlifesciences.

8:25am-8:30am:OpeningRemarks8:30am-10:00RegularPapers“Explorationofregressionmodelsforcancernoncodingmutationrecurrence”,TanjinXu,StephenA.Ramsey.“OptimizationofI/OIntensiveGenomeAssembliesontheCoriSupercomputerwithBurstBuffer”,JoshuaPritchett,BillAndreopoulos.“ExplorationsinVeryEarlyPrognosisoftheHumanImmuneResponsetoInfluenza”,ManuChaturvedi,TomtitGhosh,MichaelKirby,XiaoyuLiu,XiaofengMa,ShannonStiverson.10:00am-10:30amCoffeeBreak(withstudentposters

ondisplay)10:30am-12:00pmKeynoteTalkbyDr.NathanPrice

(InstituteofSystemsBiology,Arivale,Inc.)Title:Actionablebigdataforproactivehealthcare

12pm-1:30pm LunchBreak1:30pm-3:10pmInvitedTalks–Session1InvitedtalkbyDr.WilliamStaffordNoble(UniversityofWashington),Talktitle:“JointImputationofEpigenomicsDatabyThreeDimensionalTensorFactorization”InvitedtalkbyDr.AdamMargolin(OregonHealth&ScienceUniversity),Talktitle:“Inferringgenomicpredictorsofcancerphenotypes:machinelearning,crowd-sourcing,andbigdata”Q&Asession3:10pm-3:30pmCoffeeBreak3:30pm-4:10pmInvitedTalks–Session2InvitedtalkbyDr.DavidHeckerman(MicrosoftResearch),Talktitle:“Embracingbigdataingenomics”4:15pm-5:30pmPostersessionandinteraction

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1stInternationalWorkshoponMethodsandApplicationsinHealthcareAnalytics(MAHA)8:30am-5:30pm,October2,2016Organizers:FeiWang,UniversityofConnecticutJyotishmanPathak,CornellUniversityNigamShah,StanfordUniversityhttps://sites.google.com/site/feiwang03/acm-bcb-workshop-on-healthcare-analyticsHealthcareisundergoingamassivetransition,duetochangesinpaymentincentives,growthofclinicaldatawarehouses,advancesingenomesequencingtechnologyanddigitalimaging,aswellastheincreasedroleofthepatientinmanagingtheirownhealthinformationandrapidaccumulationofbiomedicalknowledge.Asaresult,dataanalyticstechniques,forknowledgediscoveryandderivingdatadriveninsightsfromvariousdatasources,areincreasinglyimportantinmodernhealthcare.Although,effectiveanalyticalapproacheshavebeenappliedinmanyhealthcareproblems,severalchallengesremainincluding:dataheterogeneity,sparsity,irregularsamplingandthedifficultyofdrawinginferencesfromsuchdata.Thisworkshopfocusesonnovelmethodologiesandtheirapplicationsinaddressingtheseemerginghealthcareanalyticsproblemsfrombothacademiaandindustry.

8:30am-8:35amOpeningRemarks8:35am-9:10amSession1“UsingaSemi-AutomatedModelingEnvironmenttoConstructaBayesian,SepsisDiagnosticSystem,”PeterHaugandJeffreyFerraroInvitedtalkbyDr.WanprachaArtChaovalitwongse,Talktitle:“OptimizationinMedicalAnalytics:FromDatatoKnowledgetoDecisions”10:10am-10:30amCoffeeBreak10:30am-11:05amSession2“AutomaticclassificationofCo-occurringpatientevents,”AlexanderTitus,RebeccaFaillandAmarDas“OnInterestingnessMeasuresforMiningStatisticallySignificantandNovelClinicalAssociationsfromEMRs,”OrhanAbar,RichardJ.Charnigo,AbnerRayapatiandRamakanthKavuluru11:40am-1:30pmLunchBreak1:30pm-3:05pmSession3InvitedTalkbyDr.DanielaWitten,Talktitle:“Learningfromtime”“AutomatedVerificationofPhenotypesusingPubMed,”RyanBridges,JetteHenderson,JoyceHo,ByronWallaceandJoydeepGhosh3:05pm-3:30pmCoffeeBreak3:30pm-5:20pmSession4“PredictingFutureFrequentUsersofEmergencyDepartmentsinCaliforniaState,”MayanaPereira,VikhyatiSingh,ChunPanHon,T.GregMcKelvey,ShanuSushmitaandMartineDeCock“Predictinghuman-immunodeficiencyvirusreboundaftertherapyinitiation/switchusinggenetic,laboratory,andclinicaldata,”MattiaProsperi,AlejandroPironti,FrancescaIncardona,GiuseppeTradigoandMaurizioZazzi“FeatureSelectionModelforDiagnosis,ElectronicMedicalRecordsandGeographicalDataCorrelation,”GiovanniCanino,QiulingsSuo,PietroH.Guzzi,GiuseppeTradigo,AidongZhangandPierangeloVeltri5:20pm-5:30pmClosingRemarks

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3rdWorkshoponParallelSoftwareLibrariesforSequenceAnalysis(pSALSA)8:25am-5:30pm,October2,2016Organizers:SrinivasAluru,GeorgiaTech.http://psalsa.gatech.edu/High-throughputDNAsequencinginstrumentsarecapableofgeneratingterabytesofsequencingdatainasingleexperimentatacostthatisaffordableonaroutinebasis.Analyzingsuchdataisfundamentaltomanyapplicationsincludinggenomeresequencing,denovogenomesequencing,transcriptomesampling,metagenomics,andpopulationdiversitystudies.Therateandvolumeofdatagenerationisexposingthelimitationsofserialbioinformaticssoftware.Effectiveexploitationofhighperformancecomputingtechnologiesincludingmulticores,accelerators,clusterandcloudcomputingplatformscanbridgethiscriticalgap.Thegoalofthisworkshopistobringtogetheracommunityofbioinformaticsresearchersinterestedindevelopmentofparallelalgorithmsandhighperformancecomputingsoftwareforhigh-throughputDNAsequenceanalysisanditsmyriadapplications.Inparticular,thisworkshopfocusesoncommunity-drivendevelopmentofparallelsoftwarelibrariestoenablethebioinformaticscommunitytomoreeasilyexploithighperformancecomputingtechnologies.Developmentofsuchlibrariesisfeasiblebecausebioinformaticsapplicationsoftenrelyonacommoncoreofindexanddatastructures–fore.g.,lookuptables,suffixtrees/arrays,deBruijngraphsetc.Suchlibrarieshaveprovedenormouslyusefulinotherapplicationdomains(e.g.BLASlibrariesforscientificcomputing),andsimilareffortsarecurrentlyunderwayinotherapplicationdomains(e.g.parallelgraphlibraries).ThisworkshopissupportedinpartbyanNSF/NIHBigDataawardtodevelopparallelsoftwarelibrariesforhighthroughputsequencing.

8:25am-8:30amOpeningRemarks

8:30am-9:15amNCBIPathogendetectionpipelineforfoodsafety:SNPsandMLSTschemesRichaAgarwala,NCBI,NIH

9:15am-10:00amSketchingBiologicalSequencesforStorageandComputationJaroslawZola,SUNYBuffalo

10:00am-10:30amCoffeeBreak

10:30am-11:15amHigh-ThroughputSequencingAnalysisontheAWScloudMiaChampion,Amazon,Inc.

11:15am-12:00pmAnalyzingGenomicDataatScalewithADAMFrankAustinNothaft,UCBerkeley

12pm-1:30pm LunchBreak

1:30pm-2:30pmKeynoteTalk:AtourofcontemporarygenomeassemblyalgorithmsandsoftwareAydınBuluç,LawrenceBerkeleyNationalLab

2:30pm-3:15pmSKESA:FastandaccuratehaploidgenomeassemblerwithapplicationinPathogendetectionAlexandreSouvorov,NCBI,NIH

3:15pm-3:35pmCoffeeBreak

3:45pm-4:30pmFastEtch:FastandEfficientGenomeAssemblyUsingSketchingPriyankaGhosh,WashingtonStateUniversity

4:30pm-5:15pmParBLiSS:AparallelbioinformaticslibraryforshortsequencesSrinivasAluru,GeorgiaTech

5:15pm-5:30pmDiscussionandWrapUp

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1stInternationalWorkshoponTopologicalDataAnalysisinBiomedicine(TDA-Bio)8:50am-5pm,October2,2016Organizers:BalaKrishnamoorthy,WashingtonStateUniversityBeiWangPhillips,UniversityofUtahhttp://www.sci.utah.edu/~beiwang/acmbcbworkshop2016/Datasetsofdifferentformsinbiomedicalscienceshaveseenahugeincreaseinsizeandcomplexityinthepasttwodecades.Wehavemadesubstantialprogressinvariousaspectsofgenomics,e.g.,mappingofwholegenomesofhumansaswellasothersmallandlargespecies.Similarly,alothasbeenexploredinthescopeofthesequence-to-structure-to-functionparadigmforproteins.Atthesametime,currentdatachallengesinbiomedicinearemuchmorediverse,aswellasvariedinscope.Thesheerscaleanddiversityofdatasourcesandtypesencounteredintoday'sbiomedicaldatasetsoftenrendertheroutinecomputationaltechniquesineffective.Recently,asuiteofnewtechniquestermedtopologicaldataanalysis(TDA)hasshownalotofpromiseindiscoveringstructureinlarge,high-dimensional,anddiversedatasetsthatothertraditionaltechniquescouldnotfind.Therangeofapplicationsincludesgeneexpressionanalysis,voting,andbasketballplayers'performances,tonameafew.Thisworkshopwillpresentaconciseyetself-containedoverviewofthekeyaspectsofTDA,withaneyetowardmotivatingtheapplicationofthesetechniquestoproblemsinbioinformaticsandcomputationalbiology(BCB).WhiletopologicaltechniqueshavebeenappliedpreviouslyincertainsubfieldsofBCB(e.g.,tomodelproteinandDNA/RNA3Dstructure),theyhaveprovedtobemuchmoreversatileandpowerfulthantheseapplicationsmightsuggest.Weaimtoshowcasetheversatilityandstrengthofthissuiteoftechniquesinthisworkshop.Thisworkshopwillexposetheaudiencetothekeyfundamentalaswellascomputationalaspectsoftopology.Thespeakerswillintroduce(withintheirtalks)basicTDAconceptsandtechniques,suchassimplicialcomplexes,homology,persistenthomology,Reebgraphsandmapper.Theywillalsopresenthowtheseconceptsandtechniqueshavebeen,orpotentiallycouldbe,employedtotackleinterestingproblemsinseveralareasofBCB.

8:50am-9:00amOpeningRemarks9:00am-10:00amKeynoteTalkbyDr.YusuWang(TheOhioStateUniversity)Title:TwoExamplesofApplicationofTopologicalMethodsinNeuronDataAnalysis10:00am-10:35amInvitedtalkbyDr.ChaoChen(CityUniversityofNewYork)Title:ExtractingandUsingTopologicalStructuresintheAnalysisofBiomedicalImages10:35am-10:50amCoffeeBreak10:50am-11:30amInvitedtalkbyDr.ElizabethMuch(UniversityofAlbany)Title:UtilizingTopologicalDataAnalysistoDetectPeriodicity11:30am-12:05pmInvitedtalkbyDr.BrittanyFasy(MontanaStateUniversity)Title:UsingTopologicalDataAnalysistoStudyGlandularArchitecture12:05pm-1:30pmLunchBreak1:30pm-2:30pmKeynoteTalkbyDr.GunnarCarlsson(StanfordUniversity,Ayasdi)Title:TheShapeofBiomedicalData2:30pm-3:20pmDemobyDr.SvetlanaLockwood(WashingtonStateUniversity)Title:OpenSourceSoftwareforTDA3:20pm-3:25pmCoffeeBreak3:25pm-4:00pmInvitedtalkbyDr.BeiWangPhillips(UniversityofUtah)Title:TopologicalDataAnalysisforBrainNetworks4:00pm-4:35pmInvitedtalkbyDr.MichaelRobinsonTitle:FindingCross-SpeciesOrthologswithLocalTopology4:40pm-5:10pmPanelDiscussion5:10pm-5:15pmClosingRemarks

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5thInternationalWorkshoponParallelandCloud-basedBioinformaticsandBiomedicine(ParBio)10am-12pm,October2,2016Organizers:MarioCannataro,University"MagnaGræcia"ofCatanzaroJohnSpringer,PurdueUniversityhttp://staff.icar.cnr.it/cannataro/parbio2016/Duetotheavailabilityofhigh-throughputplatforms(e.g.nextgenerationsequencing,microarrayandmassspectrometry)andclinicaldiagnostictools(e.g.medicalimaging),arecenttrendinBioinformaticsandBiomedicineistheincreasingproductionofexperimentalandclinicaldata.Consideringthecomplexanalysispipelineofthebiomedicalresearch,thebottleneckismoreandmoremovingtowardthestorage,integration,andanalysisofexperimentaldata,aswellastheircorrelationandintegrationwithpubliclyavailabledatabanks.ThegoaloftheParBioworkshopistobringtogetherscientistsinthefieldsofhighperformanceandcloudcomputing,computationalbiologyandmedicine,todiscuss,amongtheothers,theorganizationoflargescalebiologicalandbiomedicaldatabases,theparallel/service-basedimplementationofbioinformaticsandbiomedicalapplications,andproblemsandopportunitiesofmovingbiomedicalandhealthapplicationsonthecloud.

9:55am-10:00amOpeningRemarks10:00am-12:00pmPaperSession“High-performancedatastructuresfordenovoassemblyofgenomes:cacheobliviousgenericprogramming,”FrancoMilicchio,GiuseppeTradigo,PierangeloVeltri,MattiaProsperi

“G-quadruplexStructurePredictionandIntegrationintheGenData2020DataModel,”GiuseppeTradigo,FrancescaCristiano,StefanoAlcaro,SergioGreco,GianlucaPollastri,PierangeloVeltri,MattiaProsperi

“AMulti-threadedAlgorithmforMiningMaximalCohesiveDenseModulesfromInteractionNetworkswithGeneProfiles,”SaeedSalem,AdityaGoparaju

“ASurveyofSemanticIntegrationApproachesinBioinformatics,”ChaimaaMessaoudi,RachidaFissoune,HassanBadir

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The3rdInternationalWorkshoponDataMiningandVisualizationforBrainScience(BrainKDD)1pm-5pm,October2,2016Organizers:ShuiwangJi,WashingtonStateUniversityLeiShi,ChineseAcademyofSciencesHanghangTong,ArizonaStateUniversityShuaiHuang,UniversityofWashingtonPaulThompson,UniversityofSouthernCaliforniahttps://sites.google.com/site/brainkdd2016/Understandingbrainfunctionisoneofthegreatestchallengesfacingscience.Today,brainscienceisexperiencingrapidchangesandisexpectedtoachievemajoradvancesinthenearfuture.InApril2013,U.S.PresidentBarackObamaformallyannouncedtheBrainResearchthroughAdvancingInnovativeNeurotechnologiesInitiative,theBRAINInitiative.InEurope,theEuropeanCommissionhasrecentlylaunchedtheEuropeanHumanBrainProject(HBP).Intheprivatesector,theAllenInstituteforBrainScienceisembarkingonanew10-yearplantogeneratecomprehensive,large-scaledatainthemammaliancerebralcortexundertheMindScopeproject.Theseongoingandemergingprojectsareexpectedtogenerateadelugeofdatathatcapturethebrainactivitiesatdifferentlevelsoforganization.Thereisthusacompellingneedtodevelopthenextgenerationofdatamining,visualizationandknowledgediscoverytoolsthatallowonetomakesenseofthisrawdataandtounderstandhowneurologicalactivityencodesinformation.Thisworkshopwillfocusonexploringtheforefrontbetweencomputerscienceandbrainscienceandinspiringfundamentallynewwaysofmining,visualizationandknowledgediscoveryfromavarietyofbraindata.

1:00pm-1:10pmOpeningRemarks1:10pm-2:10pmKeynoteTalkbyDr.HanchuanPeng(AllenInstituteofBrainScience),Talktitle:“MassiveBrainScaleInformatics”2:10pm-2:50pmPaperSession1“ENIGMA-Viewer:InteractiveVisualizationStrategiesforConveyingEffectSizesinMeta-Analysis,”GuohaoZhang,PeterKochunov,ElliotHong,NedaJahanshad,PaulThompsonandJianChen

“HierarchicalSpatio-temporalVisualAnalysisofClusterEvolutioninElectrocorticographyData,”SugeerthMurugesan,KristoferBouchard,EdwardChang,MaxDougherty,BerndHamannandGuntherH.Weber

2:50pm-3:20pmCoffeeBreak3:20pm-4:20pmKeynoteTalkbyDr.BingniWenBrunton(UniversityofWashington),Talktitle:Data-intensiveapproachestounderstandingneurialcomputationsunderlyingnaturalisticbehaviors4:20pm-5:00pmPaperSession2“Sub-networkbasedKernelsforBrainNetworkClassification,”BiaoJie,MinxiaLiu,XiJiangandDaoqiangZhang

“UsingNetworkAlignmentforAnalysisofConnectomes:ExperiencesfromaClinicalDataset,”PietroHiramGuzzi,MariannaMilano,OlgaTymofiyeva,DuanXu,ChristopherHessandMarioCannataro

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TutorialsT1:CombinatorialmethodsfornucleicacidsequenceanalysisSreeramKannanandMarkChaisson,UniversityofWashingtonAbstract: By deciphering the sequences of genomes, we are able to determine the ‘blueprint’ of how our cells function.Unfortunatelywhileourgenomesarepolymersofbillionsofnucleotides,methodsforreadingsequencesarelimitedtohundredstothousands of nucleotides. To determine the sequence of a genome,many small fragments ofDNA are read, and the genome isinferredthrough‘denovo’fragmentassembly,wheretheseshortfragmentsarestitchedtogethertoreconstructtheentiregenome.In this tutorial, we will discuss information-theoretic barriers and algorithmic methods for reconstructing DNA, and the alliedcombinatorialproblemsinvolvedforsolvinggenomestructure.Inparticular,wewilldiscussthefollowingaspectsindetail.

1. Thearchitectureofhumangenomesandhowthiscreateschallengesforfragmentassembly.2. Thecharacteristicsofhigh-throughputsequencingdata.3. Informationtheoreticbarriersforfragmentassembly4. Combinatorial methods for de novo fragment assembly, including novel challenges for assembling reads from third-

generationlong-readsequencers.5. ChallengesinRNAsequenceassembly

T2:NetworkSciencemeetsTissue-specificBiologyShahinMohammadiandAnanthGrama,PurdueUniversityAbstract:Networksareubiquitousacrossdisciplinestomodelsystems-levelcharacteristics.Inbiology,thesenetworkscanrepresentinteractionsamongadiversesetofbiomolecules,rangingfromgenes,proteins,non-codingRNAs,andmetabolites.Concurrentwithadvancesinhigh-throughputtechnologies,alargebodyofresearchhasbeendevotedtomethodsandmodelsaimedatextractinginformation from the ever-increasing interaction datasets. However, unlike its counterpart in sequence analysis, a majority offundamentalproblemsinnetworkanalysisare“hard”tosolve. Inthistutorial,wereviewandexperimentwiththelatestnetworkanalysis tools, including alignment, community detection, and information flow analysis.Wewill illustrate how to utilize publiclyavailabletissuecelltype-specificprofilestoconstruct“tissue-specific interactomes”andhowtousethesespecializednetworkstogainnovelbiologicalinsights.T3:BigDataforDiscoveryScienceBenHeavner,InstituteforSystemsBiologyRaviMadduri,ArgonneNationalLabJackVanHorn,UniversityofSouthernCaliforniaNaveenAshish,FredHutchinsonCancerResearchCenterAbstract:This2hourtutorialwillpresentthe“BigData”biomedicaldiscoverytechnologies,end-to-endsolutions,andapplicationsdevelopedat theBigData forDiscoveryScience (BDDS)CenterofExcellenceforBigDataComputing inBiomedicalResearch.TheBDDScenteritselfisuniquelyfocusedonhandlingbigdatainbiomedicalresearch.Thecenterintroducessolutionstokeybiomedicalinformatics challenges such as big data organization, storage, processing, distribution, and sharing data across collaborativenetworks. All BDDS developments aim for interaction of basic science, biological and engineering researchers using vast datacollections and distant computers and storage systems to explore, interact and understand what the data mean and to deriveknowledgefromthem.

This tutorialwill describe and demonstrate the technologies thatwe are developing for addressing the complexity, scalability ofanalysis,andeaseofinteractionwithbigdataandassociatedanalyticmethods.ParticipantswilllearnhowBDDSresearchersapplythesetoolstoprocessgenomic,imaging,andotherdatafromtensofthousandsofpatients,andwillgaintheknowledgerequiredtotakethesetoolsbacktotheirinstitutionsandapplythemtotheirownbigdataproblems.Inthistutorial,attendeeswillbeabletodiscover datasets of interest from public data repositories such as ENCODE, SRA, generate easily exchangeable BDBags of rawdatasets,generateuniquepermanentidentifierswithmetadata,transferthedatasetsbyleveraginghighperformancedatatransferservices to cloud-basedBDDSGlobusGalaxy service.UsingBDDSGalaxy, attendees can interactively analyzedataor runexistinglarge-scaleoptimizedworkflowsforgeneexpressionandtranscriptomicregulatorynetworks.

LearningObjective1:Attendeeswillunderstandwhatspecificbigdataanalysistechnologiescanbeapplied,inanintegratedway,toaddresstheirparticularclinical,imagingandgeneticsdataanalysisneedsandthatcouldnotbeachievedbeforewiththepriorstateoftheart.

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LearningObjective2:Attendeeswill learnhow touseand furtherexplore robustdataanalysis tools in theareasof clinicaldataanalysis,proteinfunctionanalysis,andgeneticanalysis.

TutorialContent:InBDDS,wearedevelopingtechnologiesthatenablesrapiddiscoveryinthefieldofbiomedicine.Specifically,weare developing tools and services that enables discovery, exchange, identification, large-scale analysis and publication of bigbiomedicaldata.

Thistutorialwillbehandsonandattendeesareexpectedtobringalaptop.T4:DeepLearningforBioinformaticsandHealthInformaticsSungrohYoon,SeoulNationalUniversityAbstract:Inthiseraofbigdata,transformationofbiomedicalbigdataintovaluableknowledgehasbeenoneofthemostimportantproblemsinbioinformatics.Meanwhile,deeplearninghasadvancedrapidlysincetheearly2000s,andnowdemonstratesstate-of-the-art performance in various fields. Accordingly, the application of deep learning in bioinformatics to gain insight fromdata isemphasizedboth inacademiaand industry.Thistutorialwill reviewdeep learning inthebioinformaticsandpresentsexamplesofcurrent research. To provide a useful and comprehensive perspective, the presenter will categorize related research both bybioinformatics domain (i.e., omics, biomedical imaging, biomedical signal processing) and deep learning architecture (i.e., deepneuralnetworks,convolutionalneuralnetworks,recurrentneuralnetworks,emergentarchitectures)andpresentbriefdescriptionsof each study. Additionally, there will be discussion on theoretical and practical issues of deep learning in bioinformatics andsuggestionsforfutureresearchdirections.Thistutorialwillprovidevaluableinsightandserveasastartingpointforresearcherstoapplydeeplearningapproachesintheirbioinformaticsstudies.T5:Data-DrivenAnalysisofUntargetedMetabolomicsDatasetsSohaHassoun,TuftsUniversityAbstract:Metabolomicsisanexpandingfieldof‘omics’researchconcernedwiththecharacterizationofsmallmoleculemetabolitesinbiologicalsystems.Owingtorecenttechnologicaladvancesinmassspectrometry,itisnowpossibletosimultaneouslydetectinanuntargeted fashiona very largenumberofmetabolites coveringa substantial fractionofmetabolites in abiological sample. Thispresentsanexcitingopportunity todeveloppotentially transformativedata-drivenapproaches to studyandmanipulatecellsandorganisms.Amajorchallengeinrealizingmetabolomics’richpotentialisinanalyzingcollecteddata.Inthistutorial,wereviewrecentcomputational techniques forautomatedassignmentof chemical identities to spectraldatacollected throughmetabolomics.Thetutorialwillbeginwithanoverviewoftandemmassspectrometryplatformsandavailabledatabasesthatcataloguespectraldata.The tutorial will then cover recent metabolite identification techniques including those based on biochemical transformationanalysis, metabolite fragmentation, and statistical methods including overrepresentation, pathway enrichment analysis, andinference.Thetutorialconcludesbyoutliningchallengesandresearchopportunitiesinmetabolomics.Thistutorialwillbebeneficialfor researchers in systems biology, and those interested in integrating metabolomics with other ‘omics’ data and in tacklingchallengesenabledbynovelmassspectrometrycollectionplatforms.T6:EvolutionaryAlgorithmsforProteinStructureModelingEmmanuelSapin,AmardaShehu,andKennethDeJong,GeorgeMasonUniversityAbstract: In the last two decades, great progress has been made in molecular modeling through computational treatments ofbiological molecules grounded in evolutionary search techniques. Evolutionary algorithms (EAs) are gaining popularity beyondexploringtherelationshipbetweensequenceandfunctioninbiomolecules.Inparticular,recentworkisshowingthepromiseofEAsinexploringstructurespacesofproteins,suchasdenovostructurepredictionandotherstructuremodelingproblems.Theobjectiveof this tutorial is to introduce the Bioinformatics and Computational Biology, and Health Informatics community to the rapiddevelopments on EA-based frameworks for protein structure modeling through a concise but comprehensive review ofdevelopmentsinthisdirectionoverthelastdecade.Thereviewwillbeaccompaniedwithspecificdetailedhighlightsandinteractivesoftware demonstrations of representative methods. The tutorial will introduce BCB researchers to solving open problems incomputationalstructuralbiologyusingpowerfulevolutionarysearchtechniques.T7:TheISBCancerGenomicsCloudSheilaM.Reynolds,InstituteforSystemsBiologyAbstract:TheISBCancerGenomicsCloud(ISB-CGC)isoneofthreepilotprojectsfundedbytheNationalCancerInstitutewiththegoal of democratizing access to The Cancer Genome Atlas (TCGA) data by substantially lowering the barriers to accessing and

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computingoverthisrichdataset.TheISB-CGCisacloud-basedplatformthatservesasalarge-scaledatarepositoryforTCGAdata,while also providing the computational infrastructure and interactive exploratory tools necessary to carry out cancer genomicsresearchatunprecedentedscales.TheISB-CGCfacilitatescollaborativeresearchbyallowingscientiststosharedata,analyses,andinsights in a cloud environment. Tools, data, and resources that make up the ISB-CGC platform include an interactive webapplication,dataleveragingvariousGoogleCloudtechnologiessuchasCloudStorage,BigQueryandGoogleGenomics,andopen-sourcecodeexamples.TheISB-CGCteamincludesscientistsandengineersfromtheInstituteforSystemsBiology(ISB),Google,andCSRA.T8:LivingtheDREAM:CrowdsourcingbiomedicalresearchthroughchallengesandensemblesGauravPandeyandRobertVogel,IcahnSchoolofMedicineatMountSinaiLaraMangraviteandSolveigSieberts,SageBionetworksGustavoStolovitzky,IBMResearchAbstract:Theexplosion in thescale,varietyandcomplexityofbiomedicaldatasetshasnecessitatedanalmostparallelgrowthofadvanced computational methods that can produce actionable knowledge from these datasets. This growth has led to a newapproach for addressing complex biomedical problems, namely the organization of unbiased crowdsourcing-based sciencecompetitions/challenges. DREAM Challenges, the most prominent and comprehensive effort in this direction, engagediversecommunitiesofexpertstoleveragethe“wisdomofcrowds”tosolvespecificbiomedicalproblemswithinfixedtimeperiods.DREAMorganizershavelaunchedover35successfulchallenges,whichhaveattractedover8,000participantsandresultedinover100publicationsusingDREAMdata.Thefirstpartofourtutorialwilldescribethemotivation,designandscientificimpactofDREAMchallenges. The participation of a large diverse community of experts in DREAM challenges offers a promising opportunity todevelop/learn challenge “ensembles” that automatically and effectively assimilate the rich knowledge embedded in the diversesubmissions made to the challenges. This diversity among the submissions calls for the development of novel heterogeneousensemblelearningmethods,whichwillbethefocusofthesecondpartofthetutorial.

Posters1. NoaRappaport,MichalTwik,RonNudel,InbarPlaschkes,TsippiInyStein,DanitOz-Levi,SimonFishilevich,MarilynSafran,

DoronLancet.IntegratedIdentificationofDisease-GeneLinksandtheirUtilityinNext-GenerationSequencingInterpretation

2. OmidGhiasvand,MaryShimoyama.IntroducingaTextAnnotationTool(OntoMate),AssistingCurationatRatGenomeDatabase

3. Yoo-AhKim,SannaMadan,TeresaPrzytycka.WeSME:uncoveringmutualexclusivityofcancermutations

4. IlyaZhbannikov,KonstantinArbeev,AnatoliyYashin.MultidimensionalStochasticProcessModelanditsApplicationstoAnalysisofLongitudinalDatawithGeneticInformation

5. ThomasHahn,HidayatRahman,RichardSegall.AdvancedFeature-DrivenDiseaseNamedEntityRecognitionUsingConditionalRandomFields

6. EunjiKim,IvanIvanov,JianpingHua,RobertS.Chapkin,EdwardR.Dougherty.Model-basedstudyoftheEffectivenessofReportingListsofSmallFeatureSetsusingRNA-SeqData

7. HasiniYatawatte,ChristianPoellabauer,SusanLatham.AutomatedCaptureofNaturalisticChildVocalizationsforHealthResearch

8. ManalAlshehri,ImanRezaeian,AbedAlkhateeb,LuisRueda.AMachineLearningModelforDiscoveryofProteinIsoformsasBiomarkers.

9. SomyungOh,JeonghyeonHa,KyungwonLee,SejongOh.IntegratedVisualizationToolforDifferentiallyExpressedGenesandGeneOntologyAnalysis

10. JaniquePeyper,NaomiWalker,RobertWilkinson,GraemeMeintjes,JonathanBlackburn.TheTB-IRISneutrophilproteome:bioinformaticchallenges

11. RichardTillquist,ManuelLladser.Metric-spacePositioningSystems(MPS)forMachineLearning

12. ByunggilYoo,NeilMiller,GreysonTwist,ShaneCorder.TheCMHWarehouse-ACatalogofGeneticVariationinPatientsofaChildren'sHospital

13. SalvadorEugenioCaoili.KineticandAffinityConstraintsonReactionsBetweenAntihaptenAntibodiesandNonpeptidicB-CellEpitopes:ImplicationsforPredictingAntibody-MediatedModulationofPharmacokineticsandPharmacodynamics

14. TaeinKwon,EunjeongPark,HyukjaeChang.SmartRefrigeratorforHealthcareUsingFoodImageClassification

22

15. MethunKamruzzaman,AnanthKalyanaraman,BalaKrishnamoorthy.CharacterizingtheRoleofEnvironmentonPhenotypicTraitsusingTopologicalDataAnalysis

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17. ChunPanHon,MayanaPereira,ShanuSushmita,AnkurTeredesai,MartineDeCock.RiskStratificationforHospitalReadmissionofHeartFailurePatients:AMachineLearningApproach

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ProgramCommitteeNancyAmato,TexasA&MUniversityRolfBackofen,UniversityofFreiburgChrisBailey-Kellogg,DartmouthCollegeAsaBen-Hur,ColoradoStateUniversityCatherineBlake,Univ.ofIllinois,Urbana-ChampaignChristinaBoucher,ColoradoStateUniversityBethBritt,UniversityofWashingtonDanielBrown,UniversityofWaterlooYangCao,VirginiaTechJohnChelico,NewYorkUniversityBrianY.Chen,LehighUniversityJakeChen,IndianaUniv.-PurdueUniv.IndianapolisYiChen,NewJerseyInstituteofTechnologyJianlinJackCheng,UniversityofMissouriChih-LinChi,UniversityofMinnesotaA.ErcumentCicek,BilkentUniversityMarkClement,BrighamYoungUniversityTrevorCohen,UniversityofTexas,HoustonCarloCombi,UniversityofVeronaHectorCorradoBravo,Univ.ofMaryland,CollegeParkLenoreCowen,TuftsUniversityBhaskarDasgupda,UniversityofIllinoisatChicagoPeterElkin,UniversityatBuffaloEmreErtin,TheOhioStateUniversityOliverEulenstein,IowaStateUniversityJeffFerraro,TheUniversityofUtahTerryGaasterland,UniversityofCalifornia,SanDiegoAndrewGentles,StanfordUniversityAnanthGrama,PurdueUniversityEricHall,CincinnatiChildren'sHospitalNuritHaspel,UniversityofMassachusetts,BostonLenwoodHeath,VirginiaTechVasantHonavar,PennsylvaniaStateUniversityFereydounHormozdiari,UniversityofCalifornia,DavisFilipJagodzinski,WesternWashingtonUniversityXiaoqianJiang,UniversityofCalifornia,SanDiegoTamerKahveci,UniversityofFloridaAnanthKalyanaraman,WashingtonStateUniversitySreeramKannan,UniversityofWashingtonJohnKececioglu,Co-Chair,UniversityofArizonaZiaKhan,UniversityofMaryland,CollegeParkMehmetKoyuturk,CaseWesternReserveUniversityAlbertLai,TheOhioStateUniversitySu-InLee,UniversityofWashingtonHans-PeterLenhof,SaarlandUniversityJingLi,CaseWesternReserveUniversityHongfangLiu,MayoClinicStefanoLonardi,UniversityofCalifornia,Riverside

ZhiyongLu,NationalInstitutesofHealthHuiLu,UniversityofIllinoisatChicagoShaunMahony,PennStateUniversityBradMalin,VanderbiltUniversityRamgopalMettu,TulaneUniversityTijanaMilenkovic,UniversityofNotreDameT.M.Murali,VirginiaTechChadMyers,UniversityofMinnesotaLuayNakhleh,RiceUniversityScottNarus,TheUniversityofUtahWilliamStaffordNoble,UniversityofWashingtonLaxmiParida,IBMTJWatsonResearchCenterMihaiPop,UniversityofMarylandGiuseppePozzi,PolitecnicodiMilanoTeresaPrzytycka,NationalInstitutesofHealthPredragRadivojac,IndianaUniversitySusanRea,IntermountainHealthcareAnnaRitz,ReedCollegeLarryRuzzo,UniversityofWashingtonFarrantSakaguchi,TheUniversityofUtahHarmScherpbier,JeffersonCollegeRussellSchwartz,CarnegieMellonUniversitySoumitraSengupta,ColumbiaUniversityAmardaShehu,GeorgeMasonUniversityXinghuaShi,UniversityofNorthCarolinaatCharlotteMonaSingh,PrincetonUniversityKristerSwenson,CNRS,UniversitédeMontpellierJijunTang,UniversityofSouthCarolinaHaixuTang,IndianaUniversityNurcanTuncbag,MassachusettsInstituteofTechnologyJasonWang,NewJerseyInstituteofTechnologyNicoleWeiskopf,OregonHealth&ScienceUniversityChunhuaWeng,ColumbiaUniversityTravisWheeler,UniversityofMontanaAdamWilcox,Co-Chair,UniversityofWashingtonAdamWright,BrighamandWomen'sHospitalJinboXu,ToyotaTechnologicalInstituteatChicagoNaveenaYanamala,CentersforDiseaseControlandPreventionRuiZhang,UniversityofMinnesotaAidongZhang,Univ.atBuffalo,StateUniv.ofNewYorkMiZhang,MichiganStateUniversityLiqingZhang,VirginiaTechJieZhang,TheOhioStateUniversityLiZhou,PartnersHealthcareBinhaiZhu,MontanaStateUniversityJaroslawZola,Univ.atBuffalo,StateUniv.ofNewYork

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