Download ACM-BCB 2016 The 7th ACM Conference on Bioinformatics

ACM-BCB 2016
The 7th ACM Conference on Bioinformatics,
Computational Biology, and Health Informatics
October 2-5, 2016
OrganizingCommittee
GeneralChairs:
ÜmitV.Çatalyürek,GeorgiaInstituteofTechnology
GenevieveMelton-Meaux,UniversityofMinnesota
ProgramChairs:
JohnKececioglu,UniversityofArizona
AdamWilcox,UniversityofWashington
WorkshopChair:
AnanthKalyanaraman,WashingtonStateUniversity
TutorialChair:
MehmetKoyuturk,CaseWesternReserveUniversity
DemoandExhibitChair:
Robert(Bob)Cottingham,OakRidgeNational
Laboratory
PosterChairs:
LinYang,UniversityofFlorida
DongxiaoZhu,WayneStateUniversity
RegistrationChair:
PreetamGhosh,VirginiaCommonwealthUniversity
PublicityChairs
DanielCapurro,PontificiaUniv.CatólicadeChile
A.ErcumentCicek,BilkentUniversity
PierangeloVeltri,U.MagnaGraeciaofCatanzaro
StudentTravelAwardChairs
MayD.Wang,GeorgiaInstituteofTechnologyand
EmoryUniversity
JaroslawZola,UniversityatBuffalo,TheStateUniversity
ofNewYork
StudentActivityChair
MarziehAyati,CaseWesternReserveUniversity
DanDeBlasio,CarnegieMellonUniversity
ProceedingsChairs:
XinghuaMindyShi,UofNorthCarolinaatCharlotte
YangShen,TexasA&MUniversity
WebAdmins:
AnasAbu-Doleh,TheOhioStateUniversity
HyunAnderson,TheOhioStateUniversity
JonathanKho,GeorgiaInstituteofTechnology
SteeringCommittee:
AidongZhang,StateUniversityofNewYorkatBuffalo,
Co-Chair
MayD.Wang,GeorgiaInstituteofTechnologyand
EmoryUniversity,Co-Chair
SrinivasAluru,GeorgiaInstituteofTechnology
TamerKahveci,UniversityofFlorida
ChristopherC.Yang,DrexelUniversity
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ACM-BCB2016Program
REGISTRATION
Sunday7:30–16:00/Monday-Tuesday8:00–16:00/Wednesday8:00–11:00
8am
Seattle1
8:25am
10am
12pm
1pm
Seattle2
Sunday,October2,2016
ContinentalBreakfast
Location:FourthFloorBreakstation
Seattle3
Belltown
Pioneer
CNB-MAC
(8:50am–
12pm)
(1:20pm–
6pm)
BigLS
(8:25am–
12pm)
(1:30pm–
5pm)
MAHA
(8:25am–
11:40am)
(1:30pm–
5pm)
pSALSA
(8:25am–
12pm)
(1:30pm–
5:30pm)
TDA-Bio
(8:50am–
12:05pm)
(1:30pm–
5:15pm)
4pm
6pm
FirstHill
ParBio
(10am–
12pm)
BrainKDD
(1pm–
5pm)
StudentNetworkingandSocialEventattheSeattleGreatWheel
Meetatthepre-eventspaceonthe4thfloor
EmeraldII
Tutorial1
(T1)
Tutorial2
(T2)
Tutorial3
(T3)
Tutorial4
(T4)
WORKSHOPS*
CNB-MAC
3rdInternationalWorkshoponComputationalNetworkBiology:Modeling,Analysis,andControl
Organizers:Byung-JunYoon,XiaoningQianandTamerKahveci
BigLS
4thACMInternationalWorkshoponBigDatainLifeSciences
Organizers:JaroslawZolaandAnanthKalyanaraman
MAHA
1stInternationalWorkshoponMethodsandApplicationsinHealthcareAnalytics
Organizers:FeiWang,JyotishmanPathakandNigamShah
pSALSA
3rdWorkshoponParallelSoftwareLibrariesforSequenceAnalysis
Organizers:SrinivasAluru
TDA-Bio
1stInternationalWorkshoponTopologicalDataAnalysisinBiomedicine
Organizers:BalaKrishnamoorthyandBeiWangPhillips
ParBio
5thInternationalWorkshoponParallelandCloud-basedBioinformaticsandBiomedicine
Organizers:MarioCannataroandJohnA.Springer
BrainKDD
The3rdInternationalWorkshoponDataMiningandVisualizationforBrainScience
Organizers:ShuiwangJi,LeiShi,HanghangTong,ShuaiHuangandPaulThompson
*Seepage12fordetailedworkshopprograms.
TUTORIALS*
Sunday,October2
8:30-9:30
T1:Combinatorialmethodsfornucleicacidsequenceanalysis
Presenters:SreeramKannanandMarkChaisson,UniversityofWashington
10:00-12:00
T2:NetworkSciencemeetsTissue-specificBiology
Presenters:ShahinMohammadiandAnanthGrama,PurdueUniversity
1:30-3:30pm
T3:BigDataforDiscoveryScience
Presenters:BenHeavner(InstituteforSystemsBiology),RaviMadduri(ArgonneNationalLab),JackVanHorn
(UniversityofSouthernCalifornia),andNaveenAshish(FredHutchinsonCancerResearchCenter)
4:00-6:00pm
T4:DeepLearningforBioinformaticsandHealthInformatics
Presenter:SungrohYoon,SeoulNationalUniversity
3
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,IcahnSchool
ofMedicineatMountSinai,SAGEBionetworks
*Seepage19formoreinformationonindividualtutorials.
StudentNetworkingandSocialEvent
Allstudentsandpostdocsareinvitedtothestudent-networkingevent,whichwillbeheldSundayat6pm.Thisyeartheevent
willincludeanexcursiontoTheSeattleGreatWheel(thelargestobservationwheelonthewestcoast).Thestudentactivityis
focusedondevelopingprogramsforstudentgrowththrougheducationalandnetworkingopportunities.Thisisthesecondyearofa
recognizedstudentactivityandlastyearimprovedthestudentrelationshipsduringtheconference.Theeventwillbeginat6:00PM
onSunday,October2,2016withscientificspeednetworkinginthepre-eventspaceonthe4thfloorbeforetheshortwalktoElliot
Bay.(ThenetworkingeventisfreebutpleasebringcashforadiscountedadmissiontotheGreatWheel.)
4
Monday,October3,2016
8:00–
10:00
8:15–
8:30
8:30–
9:30
ContinentalBreakfast
Location:FourthFloorBreakstation
OpeningRemarks
(Location:SeattleI&II)
GeneralChairs:ÜmitV.Çatalyürek,GeorgiaInstituteofTechnology&
GenevieveMelton-Meaux,UniversityofMinnesota
ProgramChairs:JohnKececioglu,UniversityofArizona&AdamWilcox,UniversityofWashington
KeynoteTalk1
(Location:SeattleI&II)
Don’tforgetthenotes:WhyNLPiskeytohealthcaretransformation
WendyW.Chapman,UniversityofUtah
SessionChair:GenevieveMelton-Meaux,UniversityofMinnesota
9:30–
10:00
MorningBreak
Session1A
Location:SeattleI
SystemsBiology
SessionChair:AnnaRitz,
ReedCollege
Session1B
Location:SeattleII
DemoPresentations&Tutorials
SessionChair:RobertW.Cottingham,
OakRidgeNationalLaboratory
10:00
TinNguyen,DianaDiaz,Sorin
Draghici.“TOMAS:Anovel
TOpology-awareMeta-Analysis
approachappliedtoSystembiology”
DemoPresentations
10:00
“Softwaretoolsforsequence
comparison,sequencemapping,and
patient-specifichealthcareoutcome
10:30
prediction”.Presenter:AnkitAgrawal,
HueyEngChua,SouravS.Bhowmick, NorthwesternUniversity
JieZheng,LisaTucker-Kellogg.
“TAPESTRY:Network-centricTarget
PrioritizationinDisease-related
SignalingNetworks”
10:00–
12:00
11:00
AisharjyaSarkar,YuanfangRen,
RashaElhesha,TamerKahveci.
“Countingindependentmotifsin
probabilisticnetworks”
11:30
PaolaPesantez-Cabrera,Ananth
Kalyanaraman.“Detecting
CommunitiesinBiologicalBipartite
Networks”
12:30–
13:30
10:20
“TheCMHVariantWarehouse–A
CatalogofGeneticVariationinPatients
ofaChildren’sHospital".Presenter:
ByunggilYoo,Children’sMercyHospital
10:40
“KBase:Developingcollaborative
analysesofbiologicalfunctionusing
NarrativesandAppCatalog”.Presenter:
RobertW.Cottingham,OakRidge
NationalLaboratory
Tutorial
11:00
T5:Data-DrivenAnalysisofUntargeted
MetabolomicsDatasets
Presenter:SohaHassoun,TuftsUniversity
Session1C
Location:SeattleIII
AutomatedDiagnosisand
Prediction
SessionChair:JaroslawZola,
UniversityatBuffalo
10:00
Shou-HsuanStephenHuang,MingChihShih,YouliZu.“AMultiObjectiveFlowCytometryProfiling
forB-CellLymphomaDiagnosis”
10:30
YingSha,JananiVenugopalan,May
D.Wang.“ANovelTemporal
SimilarityMeasureforPatients
BasedonIrregularlyMeasuredData
inElectronicHealthRecords”
11:00
AydinSaribudak,AdarshaA.Subick,
JoshuaA.Rutta,M.ÜmitUyar,“The
Alzheimer'sDiseaseNeuroimaging
Initiative.GeneExpressionBased
ComputationMethodsfor
Alzheimer'sDiseaseProgression
usingHippocampalVolumeLoss
andMMSEScores”
11:30
QiulingSuo,HongfeiXue,JingGao,
AidongZhang.“Riskfactoranalysis
basedondeeplearningmodels”
Lunch
(Onyourown)
5
Session2A
Location:SeattleI
BiologicalModeling
SessionChair:TamerKahveci,
UniversityofFlorida
Session2B
Location:SeattleII
Tutorials
13:30
HanyuJiang,MorisaManzella,Luka
Djapic,NarayanGanesan.
“ComputationalFrameworkforin-Silico
StudyofVirtualCellBiologyviaProcess
SimulationandMultiscaleModeling”
13:30–
15:30
14:00
MuhiburRasheed,NathanClement,
AbhishekBhowmick,ChandrajitBajaj.
“StatisticalFrameworkforUncertainty
QuantificationinComputational
MolecularModeling”
14:30
JeetBanerjee,TanviRanjan,Ritwik
KumarLayek.“StabilityAnalysisof
PopulationDynamicsModelinMicrobial
BiofilmswithNon-participatingStrains”
15:00
ShuoWang,MansoorehAhmadian,
MinghanChen,JohnTyson,YoungCao.
“AHybridStochasticModelofthe
BuddingYeastCellCycleControl
Mechanism”
15:30–
16:00
16:00–
18:00
18:00–
20:00
Session2C
Location:SeattleIII
ApplicationstoHealthcareProcesses
SessionChair:BethBritt,
UniversityofWashington
13:30
ShitalKumarMishra,SouravS.Bhowmick,
HueyEngChua,JieZheng.Predictive
“ModelingofDrugEffectsonSignaling
PathwaysinDiverseCancerCellLines”
T6:EvolutionaryAlgorithmsfor
ProteinStructureModeling
Presenters:EmmanualSapin,
AmardaShehu,andKennethDe
Jong,GeorgeMasonUniversity
14:00
QianCheng,JingboShang,JoshuaJuen,
JiaweiHan,BruceSchatz.“Mining
DiscriminativePatternstoPredictHealth
StatusforCardiopulmonaryPatients”
14:30
PaulD.Martin,MichaelRushanan,
ThomasTantillo,ChristophLehmann,Aviel
D.Rubin.“ApplicationsofSecureLocation
SensinginHealthcare”
15:00
SaiNiveditaChandrasekaran,Alexios
Koutsoukas,JunHuan.“Investigating
MultiviewandMultitaskLearning
FrameworksforPredictingDrug-Disease
Associations”
AfternoonBreak–RefreshmentsProvided
ACMSIGBioGeneralMeeting
Location:SeattleI&II
PosterReception–Lighthorsd'oeuvres&Cashbar
(seepage21forlistofposters)
DEMOS(Belltown)
“Softwaretoolsforsequencecomparison,sequencemapping,andpatient-specifichealthcareoutcomeprediction”.Presenter:Ankit
Agrawal,NorthwesternUniversity
“TheCMHVariantWarehouse–ACatalogofGeneticVariationinPatientsofaChildren’sHospital".Presenter:ByunggilYoo,
Children’sMercyHospital
“KBase:DevelopingcollaborativeanalysesofbiologicalfunctionusingNarrativesandAppCatalog”.Presenter:RobertW.
Cottingham,OakRidgeNationalLaboratory
6
Tuesday,October4,2016
ContinentalBreakfast
Location:FourthFloorBreakstation
KeynoteTalk2
(Location:SeattleI&II)
Anevolutionarybiologist'sskepticalsearchforcomputationalbiology
JosephFelsenstein,UniversityofWashington
SessionChair:SrinivasAluru,GeorgiaInstituteofTechnology
8:00–
10:00
8:30–
9:30
9:30–
10:00
MorningBreak
Session3A
Location:SeattleI
InferringPhylogeniesand
Haplotypes
SessionChair:Ananth
Kalyanaraman,
WashingtonStateUniversity
10:00
JucheolMoon,OliverEulenstein.
“Robinson-FouldsMedianTrees:A
Clique-basedHeuristic”
10:30
AlexeyMarkin,OliverEulenstein.
“ManhattanPath-DifferenceMedian
Trees”
11:00
10:00–
12:00
MisaghKordi,MukulS.Bansal.“Exact
AlgorithmsforDuplication-TransferLossReconciliationwithNon-Binary
GeneTrees”
11:30
OliviaChoudhury,Ankush
Chakrabarty,ScottEmrich.“HAPIGen:HighlyAccuratePhasingand
ImputationofGenotypeData”
Session3B
Location:SeattleII
Tutorials
Session3C
Location:SeattleIII
TextMiningandClassification
SessionChair:XinghuaMindyShi,
UniversityofNorthCarolinaat
Charlotte
T7:TheISBCancerGenomicsCloud
Presenter:SheilaReynolds,Institutefor
SystemsBiology 10:00
MajidRastegar-Mojarad,Ravikumar
KomandurElayavilli,LiweiWang,
RashmiPrasad,HongfangLiu.
“PrioritizingAdverseDrugReaction
andDrugRepositioningCandidates
generatedbyLiterature-Based
Discovery”
10:30
KishlayJha,WeiJin.“MiningNovel
KnowledgefromBiomedicalLiterature
usingStatisticalMeasuresand
DomainKnowledge”
11:00
RamakanthKavuluru,MariaRamosMorales,TaraHoladay,AmandaG.
Williams,LauraHaye,JulieCerel.
“ClassificationofHelpfulComments
onOnlineSuicideWatchForums”
11:30
HaotianXu,MingDong,Dongxiao
Zhu,AlexanderKotov,AprilIdalski
Carcone,SylvieNaar-King.“Text
ClassificationwithTopic-basedWord
EmbeddingandConvolutionalNeural
Networks”
12:00–
13:30
WomeninBioinformaticsPanel
Chair:MayD.Wang,
GeorgiaInstituteofTechnology&
EmoryUniversity
Lunch
(Onyourown)
7
Session4A
Location:SeattleI
SequenceAnalysisandGenome
Assembly
SessionChair:OliverEulenstein,
IowaStateUniversity
13:30
RahulNihalani,SrinivasAluru.
“EffectiveUtilizationofPairedReads
toImproveLengthandAccuracyof
ContigsinGenomeAssembly”
14:00
PriyankaGhosh,Ananth
Kalyanaraman.“AFastSketch-based
AssemblerforGenomes”
13:30–
15:30
14:30
SubrataSaha,Sanguthevar
Rajasekaran.“POMP:apowerful
splicemapperforRNA-seqreads”
15:00
TonyPan,PatrickFlick,ChiragJain,
YongchaoLiu,SrinivasAluru.
“Kmerind:AFlexibleParallelLibrary
forK-merIndexingofBiological
SequencesonDistributedMemory
Systems”
15:30–
16:00
16:00–
17:30
17:30–
19:00
19:00–
21:30
Session4B
Location:SeattleII
Tutorials
Session4C
Location:SeattleIII
KnowledgeRepresentation
Applications
SessionChair:NaveenaYanamala,
CentersforDiseaseControland
Prevention
T8:LivingtheDREAM:Crowdsourcing
biomedicalresearchthroughchallenges
andensembles
Presenters:GauravPandey,Lara
Mangravite,SolveigSieberts,Robert
Vogel,andGustavoStolovitzky,Icahn
SchoolofMedicineatMountSinai,SAGE
Bionetworks
13:30
NaveenAshish,ArihantPatawari,
SimratSinghChhabra,ArthurW.
Toga.“NameSimilarityforComposite
ElementNameMatching”
14:00
EdwardWHuang,ShengWang,
RunshunZhang,BaoyanLiu,
XuezhongZhou,ChengXiangZhai.
“PaReCat:PatientRecord
SubcategorizationforPrecision
TraditionalChineseMedicine”
14:30
MichaelR.WyattII,TravisJohnston,
MiaPapas,MichelaTaufer.
“DevelopmentofaScalableMethod
forCreatingFoodGroupsUsingthe
NHANESDatasetandMapReduce”
15:00
ShahinMohammadi,AnanthGrama.
“Denovoidentificationofcelltype
hierarchywithapplicationto
compoundmarkerdetection”
AfternoonBreak–RefreshmentsProvided
NSFSponsoredStudentResearchForum
Location:SeattleI&II
Break(forbanquetsetup)
CashBarat18:30
Banquet
Location:SeattleI,II&III
8
Wednesday,October5,2016
8:00–
10:00
8:30–
9:30
9:30–
10:00
ContinentalBreakfast
Location:FourthFloorBreakstation
KeynoteTalk3
(Location:SeattleI&II)
Data,Predictions,andDecisions
EricHorvitz,MicrosoftResearch
SessionChair:ÜmitV.Çatalyürek,GeorgiaInstituteofTechnology
MorningBreak
Session5A
Location:SeattleI
ProteinStructureandDynamics
SessionChair:SreeramKannan,Univ.ofWashington
Session5B
Location:SeattleII
ApplicationstoMicrobesandImagingGenetics
SessionChair:MarkClement,BrighamYoungUniv.
10:00–
12:00
10:00
DongSi.“AutomaticDetectionofBeta-barrelfromMedium
ResolutionCryo-EMDensityMaps”
10:30
TatianaMaximova,DanielCarr,ErionPlaku,AmardaShehu.
“Sample-basedModelsofProteinStructuralTransitions”
11:00
DarioGhersi,RobertoSanchez.“RecoveringBoundFormsof
ProteinStructuresUsingtheElasticNetworkModeland
MolecularInteractionFields”
11:30
RamuAnandakrishnan,MayankDaga,AlexeyOnufriev,WuChunFeng.“MultiscaleApproximationwithGraphical
ProcessingUnitsforMultiplicativeSpeedupinMolecular
Dynamics”
10:00
JeffreyD.McGovern,EricJohnson,AlexDekhtyar,Michael
Black,ChristopherKitts,JenniferVanderkelen.“Library-Based
MicrobialSourceTrackingviaStrainIdentification”
10:30
SergheiMangul,DavidKoslicki.“Reference-freecomparisonof
microbialcommunitiesviadeBruijngraphs”
11:00
MdAshadAlam,OsamuKomori,VinceCalhoun,Yu-PingWang.
“RobustKernelCanonicalCorrelationAnalysistoDetectGeneGeneInteractionforImagingGeneticsData”
11:30
MdAshadAlam,VinceCalhoun,Yu-PingWang.“Influence
FunctionofMultipleKernelCanonicalAnalysistoIdentify
OutliersinImagingGeneticsData”
12:00–
13:30
13:30–
15:30
NoonBreak–RefreshmentsProvided
Session6A
Location:SeattleI
ProteinandRNAAnalysis
SessionChair:JohnKececioglu,UniversityofArizona
13:30
DeeptakVerma,GevorgGrigoryan,ChrisBailey-Kellogg.
“OCoM-SOCoM:CombinatorialMutagenesisLibraryDesign
OptimallyCombiningSequenceandStructureInformation”
14:00
ByunghanLee,JunghwanBaek,SeunghyunPark,Sungroh
Yoon.“deepTarget:End-to-endLearningFrameworkfor
microRNATargetPredictionusingDeepRecurrentNeural
Networks”
14:30
NaozumiHiranuma,ScottLundberg,Su-InLee.
“CloudControl:LeveragingmanypublicChIP-seqcontrol
experimentstobetterremovebackgroundnoise”
15:00
WenruoBai,JeffreyBilmes,WilliamS.Noble.“Bipartite
matchinggeneralizationsforpeptideidentificationin
tandemmassspectrometry”
Session6B
Location:SeattleII
AdvancingAlgorithmsandMethods
SessionChair:AdamWilcox,UniversityofWashington
13:30
SoumiRay,AdamWright.“DetectingAnomaliesinAlertFiring
withinClinicalDecisionSupportSystemsusingAnomaly/Outlier
DetectionTechniques”
14:00
Chih-WenCheng,YingSha,MayD.Wang.“InterVisAR:An
InteractiveVisualizationforAssociationRuleSearch”
14:30
LaxmiParida,NiinaHaiminen.“ScalableAlgorithmsatGenomic
ResolutiontofitLDDistributions”
9
Keynotes
Monday,October3|WendyW.Chapman,UniversityofUtah
Title:Don’tforgetthenotes:WhyNLPiskeytohealthcaretransformation
Abstract:Themajorityofclinicalinformationusefulforpatientcareandresearchislockedin
clinicalnotesandonlyaccessiblewithgreatpainandeffort.NaturalLanguageProcessinghas
thepotentialtounlocktheinformationinthenotestosupportphenotypingforprecision
medicine,qualityimprovement,andhealthservicesresearch.Thistalkwillillustratethe
potentialofNLPthroughexistingapplications,willdescribethechallengesofmakingNLPareal
andscalablesolution,andwillprovideconcretesuggestionsforhowtheaudiencecanhelpNLP
reachitspotentialinhealthcareanddiscovery.
Biography: Dr. Chapman earned her Bachelor’s degree in Linguistics and her PhD in Medical
InformaticsfromtheUniversityofUtahin2000.From2000-2010shewasaNationalLibraryof
Medicine postdoctoral fellow and then a faculty member at the University of Pittsburgh. She
joinedtheDivisionofBiomedicalInformaticsattheUniversityofCalifornia,SanDiegoin2010.
In 2013, Dr. Chapman became the chair of the University of Utah, Department of Biomedical
Informaticswhereshecontinuesherresearchonnaturallanguageprocessinginthecontextof
informaticssolutionstoproblemsthatvexhealthcare.
TuesdayOctober4|JosephFelsenstein,UniversityofWashington
Title:Anevolutionarybiologist'sskepticalsearchforcomputationalbiology
Abstract:Thistalkwillexplainhow,startingwithaninterestinbiology,andalsoincomputers,I
graduallylearnedhowtousecomputerstoilluminateproblemsinevolutionarybiology.Along
thewayIlearnedabouttheoreticalpopulationgenetics,learnedwhyitisnotalwaysbestto
writeyourtheoremsdown,andhowfascinationwithaproblemmayindicatethatsomething
moreimportantisatstake.Imovedfromtheoreticalpopulationgeneticstoalgorithmsfor
inferringevolutionarytrees(phylogenies).Thestatisticalviewpointthatwasstandardin
theoreticalpopulationgeneticsturnedouttobehighlycontroversialamongtaxonomists
studyingevolution,andwasalsoconsideredunnecessarybycomputerscientists.Bothofthese
groupsofpeoplewerewrong.Iwillarguethatcomputerscientistsandbiologistsshouldindeed
communicate,butthatthisisbestdoneviaastatistician.Iwillarguethataparametricmodel
basedonevolutionarytheoryiscrucial,butthatoneshouldbewareofbelievinginittoomuch.
Computationisessentialinbiology,butIwonderwhethertherereallyisafieldcalled
ComputationalBiology.Oroughttobe..IntheeraofComplexSystemsandBigData,aSimple
SystemsperspectivebasedonSmallDatahasdistinctadvantages.Aswereachlimitsinwhat
genomedatacantellus,aconcernforefficientuseofthosedatawillbecomeimportant,andan
understandingoftheeffectsofstatisticalnoisewillproveimportant,anditshouldencouragea
littlemorehumility.
Biography:JoeFelsensteingrewupinPhiladelphia,andattendedtheUniversityofWisconsin,
wherehegotinvolvedwiththeoreticalpopulationgeneticsinthelabofJamesF.Crow.Hewent
ontodohisPh.D.withRichardLewontinattheUniversityofChicago,andapostdoctoral
fellowshipwithAlanRobertsonattheInstituteofAnimalGeneticsattheUniversityof
Edinburgh.HehassincethenbeenafacultymemberoftheDepartmentofGeneticsatthe
UniversityofWashington,Seattle,anditssuccessortheDepartmentofGenomeSciences,and
heisalsojointlyappointedintheDepartmentofBiology.Althoughhistrainingwasthusin
theoreticalpopulationgenetics,sincehisgraduateworkhehasalsobeenfascinatedbythe
reconstructionofevolutionarytrees(phylogenies).Thisledhimtopromoteanddevelop
likelihoodmethodsforinferenceofphylogenies,toapplythebootstrapmethodtoinvestigating
whichpartsofthemarewell-supported,andtoreleasethefirstgeneralprogrampackagefor
inferringphylogenies,PHYLIP,in1980.Hewishesthatcomputationalbiologytextbookswould
paymoreattentiontophylogenies,whicharethebasicstructuresformakingsenseof
multispeciesdata.Hisworkinthisareahasalsoledhimintotheextremeandbyzantineconflicts
insystematics--someofhisclosestfriendshipsincomputationalphylogeneticswerecemented
bysharedvictimization.Joehasreceivedanumberofverynicehonors,whicharelistedathis
onlineCV,butwhichfalsemodestydictatesthathenotmentionhere.
10
WednesdayOctober5|EricHorvitz,MicrosoftResearch
Title:Data,Predictions,andDecisions
Abstract:Iwilldescribeseveralprojectsthathighlightdirectionswiththeuseofmachine
learningtoenhancepatientcareandtobuildinsightsabouthealthandwellbeing.Iwillfirst
presentresearchonleveraginglargeamountsofdatadrawnfromelectronichealthrecordsto
predictoutcomesandtoguidedecisions.Iwillfocusonopportunitieswithreducing
readmissionsandidentifyingpatientsatriskforhospital-associatedinfection,emphasizingthe
promiseofcouplingpredictivemodelswithdecisionanalysis.Iwillreflectonchallenging
directionswiththeseefforts,includingcausalinferenceandtransferlearning.Then,Iwillmove
tostudiesofhealthandwell-beingfromnon-traditionalsourcesofdata,includingtheuseof
anonymizedlogsofonlineactivities.Iwillpresentresultsonpharmacovigilance,detectingthe
onsetofillness,andbuildingdeeperunderstandingsofepisodicinformationneedsofpatients
overphasesofillness.I’llwrapupbydiscussingseveralaspirationaldirectionswithdata,
predictions,anddecisions.
Biography: Eric Horvitz is technical fellow at Microsoft, where he serves as director of the
MicrosoftResearchlabatRedmond.Hisinterestsspantheoreticalandpracticalchallengeswith
computingsystemsthatlearnfromdataandthatcanperceive,reason,anddecide.Hisefforts
and collaborations have led to fielded systems in the areas of transportation, healthcare,
ecommerce,andoperatingsystems.EricreceivedMDandPhDdegreesatStanfordUniversity.
He has been elected fellow of the National Academy of Engineering (NAE), AAAI, ACM, AAAS,
and the American Academy of Arts and Sciences. He received the Feigenbaum Prize and the
ACM-AAAIAllenNewellAwardforhisresearchcontributions.HecurrentlyservesontheBoard
ofRegentsoftheNationalLibraryofMedicine,theComputerScienceandTelecommunications
Board (CSTB), and the advisory board for the Center for Causal Discovery at the University of
Pittsburgh.Moreinformationcanbefoundathttp://research.microsoft.com/~horvitz.
11
rd
Workshops
3 InternationalWorkshoponComputationalNetwork
Biology:Modeling,Analysis,andControl(CNB-MAC)
8:45am-6pm,October2,2016
Organizers:
Byung-JunYoon,TexasA&MUniversity
XiaoningQian,TexasA&MUniversity
TamerKahveci,UniversityofFlorida
https://cnbmac.org/
Next-generationhigh-throughputprofilingtechnologieshave
enabledmoresystematicandcomprehensivestudiesofliving
systems.Networkmodelsplaycrucialrolesinunderstanding
thecomplexinteractionsthatgovernbiologicalsystems,and
theirinteractionswithexternalenvironment.Theinference
andanalysisofsuchcomplexnetworksandnetwork-based
analysisoflarge-scalemeasurementdatahavealreadyshown
strongpotentialsforunveilingthekeymechanismsof
complexdiseasesaswellasfordesigningimproved
therapeuticstrategies.Atthesametime,theinferenceand
analysisofcomplexbiologicalnetworksposenewexciting
challengesforcomputerscience,signalprocessing,control,
andstatistics.TheCNB-MACworkshopaimstoprovidean
internationalscientificforumforpresentingrecentadvances
incomputationalnetworkbiologythatinvolvemodeling,
analysis,andcontrolofbiologicalsystemsunderdifferent
conditions,andsystem-orientedanalysisoflarge-scaleOMICS
data.
08:50-9:00OpeningRemarks
09:00-10:00KeynoteTalkbyDr.Su-InLee(Universityof
Washington),
TalkTitle:MiningBigDataforMolecularMarker
Identification
10:00-10:20 CoffeeBreak
10:20-12:00Session1
“SparseFeatureSelectionforClassificationandPredictionof
MetastasisinEndometrialCancer”,MehmetErenAhsen,
ToddBoren,NitinSingh,BurookMisganaw,DavidMutch,
KathleenMoore,FloorBackes,CarolynMcCourt,Jayanthi
Lea,DavidMiller,MichaelWhiteandMathukumalli
Vidyasagar
“DataRequirementsforModel-BasedCancerPrognosis
Prediction”,LoriDaltonandMohammadmahdiRezaeiYousefi
“Comparisonoftissue/diseasespecificintegratednetworks
usingdirectedgraphletsignatures”,ArzuBurcakSonmezand
TolgaCan
“OptimalROC-basedClassificationandPerformanceAnalysis
underBayesianUncertaintyModels”,LoriDalton
“SNPbySNPbyEnvironmentInteractionNetworkof
Alcoholism”,AminZollanvariandGilAlterovitz
12:00-13:20LunchBreak
13:20-15:00Session2
“Towardstargetedcombinatorialtherapydesignforthe
treatmentofcastration-resistantprostatecancer”,Osama
ArshadandAniruddhaDatta
“Combinationtherapydesignformaximizingsensitivityand
minimizingtoxicity”,KevinMatlock,NoahBerlow,Charles
KellerandRanadipPal
“DIGNiFI:Discoveringcausativegenesfororphandiseases
usingprotein-proteininteractionnetworks”,XiaoxiaLiu,
ZhihaoYang,HongfeiLin,MichaelSimmonsandZhiyongLu
“SEQUOIA:Significanceenhancednetworkqueryingthrough
context-sensitiverandomwalkandminimizationofnetwork
conductance”,HyundooJeongandByung-JunYoon
“FindingLow-ConductancesetswithDenseinteractions
(FLCD)forbetterproteincomplexprediction”,YijieWangand
XiaoningQian
15:00-15:20CoffeeBreak
15:20-16:40Session3
“InferringMicrobialInteractionNetworksfromMetagenomic
DataUsingSgLV-EKFAlgorithm”,MustafaAlshawaqfeh,
AhmadBaniYounesandErchinSerpedin
“StochasticModelingandSimulationofReaction-Diffusion
SystemwithHillFunctionDynamics”,MinghanChen,FeiLi,
ShuoWangandYangCao
“InterpretiveTime-FrequencyAnalysisofGenomic
Sequences”,HamedHassaniSaadi,RezaSameniandAmin
Zollanvari
“ComprehensiveEvaluationofRNA-seqQuantification
MethodsforLinearity”,HaijingJin,Ying-WooiWanand
ZhandongLiu
16:40-17:05Five-MinuteLightningTalksforPosters
17:05-17:50PosterSession
17:50-18:00ClosingRemarks
12
4thACMInternationalWorkshoponBigDatainLife
Sciences(BigLS)
8:25am-5:30pm,October2,2016
Organizers:
JaroslawZola,SUNYBuffalo
AnanthKalyanaraman,WashingtonStateUniversity
http://www.bigls.org
Theever-growingvolumeanddiversityofbiologicaland
biomedicaldatacollectionscontinuestoposenew
challengesandincreasingdemandsoncomputingand
datamanagement.TheinherentcomplexityofthisBig
Dataforcesustorethinkhowwecollect,store,combine
andanalyzeit.BigLSisaworkshopseriesdedicatedto
thebroadthemeofBigDatainlifesciences.Thegoalof
theworkshopistobringtogetherleadingresearchers
andpractitionersworkingonadiverserangeofBigData
problemsrelatingtobiologyandmedicine,andengage
theminadiscussionaboutcurrentBigDataproblems,
thestateofcomputationaltoolsandanalytics,the
challengesandthefuturetrendswithinlifesciences.
8:25am-8:30am:OpeningRemarks
8:30am-10:00RegularPapers
“Explorationofregressionmodelsforcancernoncoding
mutationrecurrence”,TanjinXu,StephenA.Ramsey.
“OptimizationofI/OIntensiveGenomeAssemblieson
theCoriSupercomputerwithBurstBuffer”,Joshua
Pritchett,BillAndreopoulos.
“ExplorationsinVeryEarlyPrognosisoftheHuman
ImmuneResponsetoInfluenza”,ManuChaturvedi,
TomtitGhosh,MichaelKirby,XiaoyuLiu,XiaofengMa,
ShannonStiverson.
10:00am-10:30amCoffeeBreak(withstudentposters
ondisplay)
10:30am-12:00pmKeynoteTalkbyDr.NathanPrice
(InstituteofSystemsBiology,Arivale,Inc.)
Title:Actionablebigdataforproactive
healthcare
12pm-1:30pm LunchBreak
1:30pm-3:10pmInvitedTalks–Session1
InvitedtalkbyDr.WilliamStaffordNoble(Universityof
Washington),Talktitle:“JointImputationof
EpigenomicsDatabyThreeDimensionalTensor
Factorization”
InvitedtalkbyDr.AdamMargolin(OregonHealth&
ScienceUniversity),Talktitle:“Inferringgenomic
predictorsofcancerphenotypes:machinelearning,
crowd-sourcing,andbigdata”
Q&Asession
3:10pm-3:30pmCoffeeBreak
3:30pm-4:10pmInvitedTalks–Session2
InvitedtalkbyDr.DavidHeckerman(Microsoft
Research),Talktitle:“Embracingbigdataingenomics”
4:15pm-5:30pmPostersessionandinteraction
13
1stInternationalWorkshoponMethodsand
ApplicationsinHealthcareAnalytics(MAHA)
8:30am-5:30pm,October2,2016
Organizers:
FeiWang,UniversityofConnecticut
JyotishmanPathak,CornellUniversity
NigamShah,StanfordUniversity
https://sites.google.com/site/feiwang03/acm-bcbworkshop-on-healthcare-analytics
Healthcareisundergoingamassivetransition,dueto
changesinpaymentincentives,growthofclinicaldata
warehouses,advancesingenomesequencing
technologyanddigitalimaging,aswellastheincreased
roleofthepatientinmanagingtheirownhealth
informationandrapidaccumulationofbiomedical
knowledge.Asaresult,dataanalyticstechniques,for
knowledgediscoveryandderivingdatadriveninsights
fromvariousdatasources,areincreasinglyimportantin
modernhealthcare.Although,effectiveanalytical
approacheshavebeenappliedinmanyhealthcare
problems,severalchallengesremainincluding:data
heterogeneity,sparsity,irregularsamplingandthe
difficultyofdrawinginferencesfromsuchdata.This
workshopfocusesonnovelmethodologiesandtheir
applicationsinaddressingtheseemerginghealthcare
analyticsproblemsfrombothacademiaandindustry.
8:30am-8:35amOpeningRemarks
8:35am-9:10amSession1
“UsingaSemi-AutomatedModelingEnvironmentto
ConstructaBayesian,SepsisDiagnosticSystem,”Peter
HaugandJeffreyFerraro
InvitedtalkbyDr.WanprachaArtChaovalitwongse,Talk
title:“OptimizationinMedicalAnalytics:FromDatato
KnowledgetoDecisions”
10:10am-10:30amCoffeeBreak
10:30am-11:05amSession2
“AutomaticclassificationofCo-occurringpatient
events,”AlexanderTitus,RebeccaFaillandAmarDas
“OnInterestingnessMeasuresforMiningStatistically
SignificantandNovelClinicalAssociationsfromEMRs,”
OrhanAbar,RichardJ.Charnigo,AbnerRayapatiand
RamakanthKavuluru
11:40am-1:30pmLunchBreak
1:30pm-3:05pmSession3
InvitedTalkbyDr.DanielaWitten,Talktitle:“Learning
fromtime”
“AutomatedVerificationofPhenotypesusingPubMed,”
RyanBridges,JetteHenderson,JoyceHo,ByronWallace
andJoydeepGhosh
3:05pm-3:30pmCoffeeBreak
3:30pm-5:20pmSession4
“PredictingFutureFrequentUsersofEmergency
DepartmentsinCaliforniaState,”MayanaPereira,
VikhyatiSingh,ChunPanHon,T.GregMcKelvey,Shanu
SushmitaandMartineDeCock
“Predictinghuman-immunodeficiencyvirusrebound
aftertherapyinitiation/switchusinggenetic,laboratory,
andclinicaldata,”MattiaProsperi,AlejandroPironti,
FrancescaIncardona,GiuseppeTradigoandMaurizio
Zazzi
“FeatureSelectionModelforDiagnosis,Electronic
MedicalRecordsandGeographicalDataCorrelation,”
GiovanniCanino,QiulingsSuo,PietroH.Guzzi,Giuseppe
Tradigo,AidongZhangandPierangeloVeltri
5:20pm-5:30pmClosingRemarks
14
3rdWorkshoponParallelSoftwareLibrariesfor
SequenceAnalysis(pSALSA)
8:25am-5:30pm,October2,2016
Organizers:
SrinivasAluru,GeorgiaTech.
http://psalsa.gatech.edu/
High-throughputDNAsequencinginstrumentsare
capableofgeneratingterabytesofsequencingdataina
singleexperimentatacostthatisaffordableona
routinebasis.Analyzingsuchdataisfundamentalto
manyapplicationsincludinggenomeresequencing,de
novogenomesequencing,transcriptomesampling,
metagenomics,andpopulationdiversitystudies.The
rateandvolumeofdatagenerationisexposingthe
limitationsofserialbioinformaticssoftware.Effective
exploitationofhighperformancecomputing
technologiesincludingmulticores,accelerators,cluster
andcloudcomputingplatformscanbridgethiscritical
gap.
Thegoalofthisworkshopistobringtogethera
communityofbioinformaticsresearchersinterestedin
developmentofparallelalgorithmsandhigh
performancecomputingsoftwareforhigh-throughput
DNAsequenceanalysisanditsmyriadapplications.In
particular,thisworkshopfocusesoncommunity-driven
developmentofparallelsoftwarelibrariestoenablethe
bioinformaticscommunitytomoreeasilyexploithigh
performancecomputingtechnologies.Developmentof
suchlibrariesisfeasiblebecausebioinformatics
applicationsoftenrelyonacommoncoreofindexand
datastructures–fore.g.,lookuptables,suffix
trees/arrays,deBruijngraphsetc.Suchlibrarieshave
provedenormouslyusefulinotherapplicationdomains
(e.g.BLASlibrariesforscientificcomputing),andsimilar
effortsarecurrentlyunderwayinotherapplication
domains(e.g.parallelgraphlibraries).
ThisworkshopissupportedinpartbyanNSF/NIHBig
Dataawardtodevelopparallelsoftwarelibrariesfor
highthroughputsequencing.
8:25am-8:30amOpeningRemarks
8:30am-9:15amNCBIPathogendetectionpipelinefor
foodsafety:SNPsandMLSTschemes
RichaAgarwala,NCBI,NIH
9:15am-10:00amSketchingBiologicalSequencesfor
StorageandComputation
JaroslawZola,SUNYBuffalo
10:00am-10:30amCoffeeBreak
10:30am-11:15amHigh-ThroughputSequencing
AnalysisontheAWScloud
MiaChampion,Amazon,Inc.
11:15am-12:00pmAnalyzingGenomicDataatScale
withADAM
FrankAustinNothaft,UCBerkeley
12pm-1:30pm LunchBreak
1:30pm-2:30pmKeynoteTalk:Atourofcontemporary
genomeassemblyalgorithmsandsoftware
AydınBuluç,LawrenceBerkeleyNationalLab
2:30pm-3:15pmSKESA:Fastandaccuratehaploid
genomeassemblerwithapplicationinPathogen
detection
AlexandreSouvorov,NCBI,NIH 3:15pm-3:35pmCoffeeBreak
3:45pm-4:30pmFastEtch:FastandEfficientGenome
AssemblyUsingSketching
PriyankaGhosh,WashingtonStateUniversity
4:30pm-5:15pmParBLiSS:Aparallelbioinformatics
libraryforshortsequences
SrinivasAluru,GeorgiaTech
5:15pm-5:30pmDiscussionandWrapUp
15
1stInternationalWorkshoponTopologicalData
AnalysisinBiomedicine(TDA-Bio)
8:50am-5pm,October2,2016
Organizers:
BalaKrishnamoorthy,WashingtonStateUniversity
BeiWangPhillips,UniversityofUtah
http://www.sci.utah.edu/~beiwang/acmbcbworkshop2
016/
Datasetsofdifferentformsinbiomedicalscienceshave
seenahugeincreaseinsizeandcomplexityinthepast
twodecades.Wehavemadesubstantialprogressin
variousaspectsofgenomics,e.g.,mappingofwhole
genomesofhumansaswellasothersmallandlarge
species.Similarly,alothasbeenexploredinthescope
ofthesequence-to-structure-to-functionparadigmfor
proteins.Atthesametime,currentdatachallengesin
biomedicinearemuchmorediverse,aswellasvariedin
scope.Thesheerscaleanddiversityofdatasourcesand
typesencounteredintoday'sbiomedicaldatasetsoften
rendertheroutinecomputationaltechniques
ineffective.Recently,asuiteofnewtechniquestermed
topologicaldataanalysis(TDA)hasshownalotof
promiseindiscoveringstructureinlarge,highdimensional,anddiversedatasetsthatothertraditional
techniquescouldnotfind.Therangeofapplications
includesgeneexpressionanalysis,voting,and
basketballplayers'performances,tonameafew.This
workshopwillpresentaconciseyetself-contained
overviewofthekeyaspectsofTDA,withaneyetoward
motivatingtheapplicationofthesetechniquesto
problemsinbioinformaticsandcomputationalbiology
(BCB).Whiletopologicaltechniqueshavebeenapplied
previouslyincertainsubfieldsofBCB(e.g.,tomodel
proteinandDNA/RNA3Dstructure),theyhaveproved
tobemuchmoreversatileandpowerfulthanthese
applicationsmightsuggest.Weaimtoshowcasethe
versatilityandstrengthofthissuiteoftechniquesinthis
workshop.
Thisworkshopwillexposetheaudiencetothekey
fundamentalaswellascomputationalaspectsof
topology.Thespeakerswillintroduce(withintheirtalks)
basicTDAconceptsandtechniques,suchassimplicial
complexes,homology,persistenthomology,Reeb
graphsandmapper.Theywillalsopresenthowthese
conceptsandtechniqueshavebeen,orpotentially
couldbe,employedtotackleinterestingproblemsin
severalareasofBCB.
8:50am-9:00amOpeningRemarks
9:00am-10:00amKeynoteTalkbyDr.YusuWang(The
OhioStateUniversity)
Title:TwoExamplesofApplicationofTopological
MethodsinNeuronDataAnalysis
10:00am-10:35amInvitedtalkbyDr.ChaoChen(City
UniversityofNewYork)
Title:ExtractingandUsingTopologicalStructuresinthe
AnalysisofBiomedicalImages
10:35am-10:50amCoffeeBreak
10:50am-11:30amInvitedtalkbyDr.ElizabethMuch
(UniversityofAlbany)
Title:UtilizingTopologicalDataAnalysistoDetect
Periodicity
11:30am-12:05pmInvitedtalkbyDr.BrittanyFasy
(MontanaStateUniversity)
Title:UsingTopologicalDataAnalysistoStudyGlandular
Architecture
12:05pm-1:30pmLunchBreak
1:30pm-2:30pmKeynoteTalkbyDr.GunnarCarlsson
(StanfordUniversity,Ayasdi)
Title:TheShapeofBiomedicalData
2:30pm-3:20pmDemobyDr.SvetlanaLockwood
(WashingtonStateUniversity)
Title:OpenSourceSoftwareforTDA
3:20pm-3:25pmCoffeeBreak
3:25pm-4:00pmInvitedtalkbyDr.BeiWangPhillips
(UniversityofUtah)
Title:TopologicalDataAnalysisforBrainNetworks
4:00pm-4:35pmInvitedtalkbyDr.MichaelRobinson
Title:FindingCross-SpeciesOrthologswithLocal
Topology
4:40pm-5:10pmPanelDiscussion
5:10pm-5:15pmClosingRemarks
16
5thInternationalWorkshoponParallelandCloudbasedBioinformaticsandBiomedicine(ParBio)
10am-12pm,October2,2016
Organizers:
MarioCannataro,University"MagnaGræcia"of
Catanzaro
JohnSpringer,PurdueUniversity
http://staff.icar.cnr.it/cannataro/parbio2016/
Duetotheavailabilityofhigh-throughputplatforms
(e.g.nextgenerationsequencing,microarrayandmass
spectrometry)andclinicaldiagnostictools(e.g.medical
imaging),arecenttrendinBioinformaticsand
Biomedicineistheincreasingproductionof
experimentalandclinicaldata.Consideringthecomplex
analysispipelineofthebiomedicalresearch,the
bottleneckismoreandmoremovingtowardthe
storage,integration,andanalysisofexperimentaldata,
aswellastheircorrelationandintegrationwithpublicly
availabledatabanks.ThegoaloftheParBioworkshopis
tobringtogetherscientistsinthefieldsofhigh
performanceandcloudcomputing,computational
biologyandmedicine,todiscuss,amongtheothers,the
organizationoflargescalebiologicalandbiomedical
databases,theparallel/service-basedimplementation
ofbioinformaticsandbiomedicalapplications,and
problemsandopportunitiesofmovingbiomedicaland
healthapplicationsonthecloud.
9:55am-10:00amOpeningRemarks
10:00am-12:00pmPaperSession
“High-performancedatastructuresfordenovo
assemblyofgenomes:cacheobliviousgeneric
programming,”FrancoMilicchio,GiuseppeTradigo,
PierangeloVeltri,MattiaProsperi
“G-quadruplexStructurePredictionandIntegrationin
theGenData2020DataModel,”GiuseppeTradigo,
FrancescaCristiano,StefanoAlcaro,SergioGreco,
GianlucaPollastri,PierangeloVeltri,MattiaProsperi
“AMulti-threadedAlgorithmforMiningMaximal
CohesiveDenseModulesfromInteractionNetworks
withGeneProfiles,”SaeedSalem,AdityaGoparaju
“ASurveyofSemanticIntegrationApproachesin
Bioinformatics,”ChaimaaMessaoudi,RachidaFissoune,
HassanBadir
17
The3rdInternationalWorkshoponDataMiningand
VisualizationforBrainScience(BrainKDD)
1pm-5pm,October2,2016
Organizers:
ShuiwangJi,WashingtonStateUniversity
LeiShi,ChineseAcademyofSciences
HanghangTong,ArizonaStateUniversity
ShuaiHuang,UniversityofWashington
PaulThompson,UniversityofSouthernCalifornia
https://sites.google.com/site/brainkdd2016/
Understandingbrainfunctionisoneofthegreatest
challengesfacingscience.Today,brainscienceisexperiencing
rapidchangesandisexpectedtoachievemajoradvancesin
thenearfuture.InApril2013,U.S.PresidentBarackObama
formallyannouncedtheBrainResearchthroughAdvancing
InnovativeNeurotechnologiesInitiative,theBRAINInitiative.
InEurope,theEuropeanCommissionhasrecentlylaunched
theEuropeanHumanBrainProject(HBP).Intheprivate
sector,theAllenInstituteforBrainScienceisembarkingona
new10-yearplantogeneratecomprehensive,large-scale
datainthemammaliancerebralcortexundertheMindScope
project.Theseongoingandemergingprojectsareexpected
togenerateadelugeofdatathatcapturethebrainactivities
atdifferentlevelsoforganization.Thereisthusacompelling
needtodevelopthenextgenerationofdatamining,
visualizationandknowledgediscoverytoolsthatallowoneto
makesenseofthisrawdataandtounderstandhow
neurologicalactivityencodesinformation.Thisworkshopwill
focusonexploringtheforefrontbetweencomputerscience
andbrainscienceandinspiringfundamentallynewwaysof
mining,visualizationandknowledgediscoveryfromavariety
ofbraindata.
1:00pm-1:10pmOpeningRemarks
1:10pm-2:10pmKeynoteTalkbyDr.HanchuanPeng(Allen
InstituteofBrainScience),
Talktitle:“MassiveBrainScaleInformatics”
2:10pm-2:50pmPaperSession1
“ENIGMA-Viewer:InteractiveVisualizationStrategiesfor
ConveyingEffectSizesinMeta-Analysis,”GuohaoZhang,
PeterKochunov,ElliotHong,NedaJahanshad,PaulThompson
andJianChen
“HierarchicalSpatio-temporalVisualAnalysisofCluster
EvolutioninElectrocorticographyData,”Sugeerth
Murugesan,KristoferBouchard,EdwardChang,Max
Dougherty,BerndHamannandGuntherH.Weber
2:50pm-3:20pmCoffeeBreak
3:20pm-4:20pmKeynoteTalkbyDr.BingniWenBrunton
(UniversityofWashington),
Talktitle:Data-intensiveapproachestounderstandingneurial
computationsunderlyingnaturalisticbehaviors
4:20pm-5:00pmPaperSession2
“Sub-networkbasedKernelsforBrainNetwork
Classification,”BiaoJie,MinxiaLiu,XiJiangandDaoqiang
Zhang
“UsingNetworkAlignmentforAnalysisofConnectomes:
ExperiencesfromaClinicalDataset,”PietroHiramGuzzi,
MariannaMilano,OlgaTymofiyeva,DuanXu,Christopher
HessandMarioCannataro
18
Tutorials
T1:Combinatorialmethodsfornucleicacidsequenceanalysis
SreeramKannanandMarkChaisson,UniversityofWashington
Abstract: By deciphering the sequences of genomes, we are able to determine the ‘blueprint’ of how our cells function.
Unfortunatelywhileourgenomesarepolymersofbillionsofnucleotides,methodsforreadingsequencesarelimitedtohundredsto
thousands of nucleotides. To determine the sequence of a genome, many small fragments of DNA are read, and the genome is
inferredthrough‘denovo’fragmentassembly,wheretheseshortfragmentsarestitchedtogethertoreconstructtheentiregenome.
In this tutorial, we will discuss information-theoretic barriers and algorithmic methods for reconstructing DNA, and the allied
combinatorialproblemsinvolvedforsolvinggenomestructure.Inparticular,wewilldiscussthefollowingaspectsindetail.
1. Thearchitectureofhumangenomesandhowthiscreateschallengesforfragmentassembly.
2. Thecharacteristicsofhigh-throughputsequencingdata.
3. Informationtheoreticbarriersforfragmentassembly
4. Combinatorial methods for de novo fragment assembly, including novel challenges for assembling reads from thirdgenerationlong-readsequencers.
5. ChallengesinRNAsequenceassembly
T2:NetworkSciencemeetsTissue-specificBiology
ShahinMohammadiandAnanthGrama,PurdueUniversity
Abstract:Networksareubiquitousacrossdisciplinestomodelsystems-levelcharacteristics.Inbiology,thesenetworkscanrepresent
interactionsamongadiversesetofbiomolecules,rangingfromgenes,proteins,non-codingRNAs,andmetabolites.Concurrentwith
advancesinhigh-throughputtechnologies,alargebodyofresearchhasbeendevotedtomethodsandmodelsaimedatextracting
information from the ever-increasing interaction datasets. However, unlike its counterpart in sequence analysis, a majority of
fundamentalproblemsinnetworkanalysisare“hard”tosolve.Inthistutorial,wereviewandexperimentwiththelatestnetwork
analysis tools, including alignment, community detection, and information flow analysis. We will illustrate how to utilize publicly
availabletissuecelltype-specificprofilestoconstruct“tissue-specificinteractomes”andhowtousethesespecializednetworksto
gainnovelbiologicalinsights.
T3:BigDataforDiscoveryScience
BenHeavner,InstituteforSystemsBiology
RaviMadduri,ArgonneNationalLab
JackVanHorn,UniversityofSouthernCalifornia
NaveenAshish,FredHutchinsonCancerResearchCenter
Abstract:This2hourtutorialwillpresentthe“BigData”biomedicaldiscoverytechnologies,end-to-endsolutions,andapplications
developedattheBigDataforDiscoveryScience(BDDS)CenterofExcellenceforBigDataComputinginBiomedicalResearch.The
BDDScenteritselfisuniquelyfocusedonhandlingbigdatainbiomedicalresearch.Thecenterintroducessolutionstokeybiomedical
informatics challenges such as big data organization, storage, processing, distribution, and sharing data across collaborative
networks. All BDDS developments aim for interaction of basic science, biological and engineering researchers using vast data
collections and distant computers and storage systems to explore, interact and understand what the data mean and to derive
knowledgefromthem.
This tutorial will describe and demonstrate the technologies that we are developing for addressing the complexity, scalability of
analysis,andeaseofinteractionwithbigdataandassociatedanalyticmethods.ParticipantswilllearnhowBDDSresearchersapply
thesetoolstoprocessgenomic,imaging,andotherdatafromtensofthousandsofpatients,andwillgaintheknowledgerequiredto
takethesetoolsbacktotheirinstitutionsandapplythemtotheirownbigdataproblems.Inthistutorial,attendeeswillbeableto
discover datasets of interest from public data repositories such as ENCODE, SRA, generate easily exchangeable BDBags of raw
datasets,generateuniquepermanentidentifierswithmetadata,transferthedatasetsbyleveraginghighperformancedatatransfer
services to cloud-based BDDS Globus Galaxy service. Using BDDS Galaxy, attendees can interactively analyze data or run existing
large-scaleoptimizedworkflowsforgeneexpressionandtranscriptomicregulatorynetworks.
LearningObjective1:Attendeeswillunderstandwhatspecificbigdataanalysistechnologiescanbeapplied,inanintegratedway,to
addresstheirparticularclinical,imagingandgeneticsdataanalysisneedsandthatcouldnotbeachievedbeforewiththepriorstate
oftheart.
19
Learning Objective 2: Attendees will learn how to use and further explore robust data analysis tools in the areas of clinical data
analysis,proteinfunctionanalysis,andgeneticanalysis.
TutorialContent:InBDDS,wearedevelopingtechnologiesthatenablesrapiddiscoveryinthefieldofbiomedicine.Specifically,we
are developing tools and services that enables discovery, exchange, identification, large-scale analysis and publication of big
biomedicaldata.
Thistutorialwillbehandsonandattendeesareexpectedtobringalaptop.
T4:DeepLearningforBioinformaticsandHealthInformatics
SungrohYoon,SeoulNationalUniversity
Abstract:Inthiseraofbigdata,transformationofbiomedicalbigdataintovaluableknowledgehasbeenoneofthemostimportant
problemsinbioinformatics.Meanwhile,deeplearninghasadvancedrapidlysincetheearly2000s,andnowdemonstratesstate-ofthe-art performance in various fields. Accordingly, the application of deep learning in bioinformatics to gain insight from data is
emphasizedbothinacademiaandindustry.Thistutorialwillreviewdeeplearninginthebioinformaticsandpresentsexamplesof
current research. To provide a useful and comprehensive perspective, the presenter will categorize related research both by
bioinformatics domain (i.e., omics, biomedical imaging, biomedical signal processing) and deep learning architecture (i.e., deep
neuralnetworks,convolutionalneuralnetworks,recurrentneuralnetworks,emergentarchitectures)andpresentbriefdescriptions
of each study. Additionally, there will be discussion on theoretical and practical issues of deep learning in bioinformatics and
suggestionsforfutureresearchdirections.Thistutorialwillprovidevaluableinsightandserveasastartingpointforresearchersto
applydeeplearningapproachesintheirbioinformaticsstudies.
T5:Data-DrivenAnalysisofUntargetedMetabolomicsDatasets
SohaHassoun,TuftsUniversity
Abstract:Metabolomicsisanexpandingfieldof‘omics’researchconcernedwiththecharacterizationofsmallmoleculemetabolites
inbiologicalsystems.Owingtorecenttechnologicaladvancesinmassspectrometry,itisnowpossibletosimultaneouslydetectinan
untargeted fashion a very large number of metabolites covering a substantial fraction of metabolites in a biological sample. This
presents an exciting opportunity to develop potentially transformative data-driven approaches to study and manipulate cells and
organisms.Amajorchallengeinrealizingmetabolomics’richpotentialisinanalyzingcollecteddata.Inthistutorial,wereviewrecent
computational techniques for automated assignment of chemical identities to spectral data collected through metabolomics. The
tutorialwillbeginwithanoverviewoftandemmassspectrometryplatformsandavailabledatabasesthatcataloguespectraldata.
The tutorial will then cover recent metabolite identification techniques including those based on biochemical transformation
analysis, metabolite fragmentation, and statistical methods including overrepresentation, pathway enrichment analysis, and
inference.Thetutorialconcludesbyoutliningchallengesandresearchopportunitiesinmetabolomics.Thistutorialwillbebeneficial
for researchers in systems biology, and those interested in integrating metabolomics with other ‘omics’ data and in tackling
challengesenabledbynovelmassspectrometrycollectionplatforms.
T6:EvolutionaryAlgorithmsforProteinStructureModeling
EmmanuelSapin,AmardaShehu,andKennethDeJong,GeorgeMasonUniversity
Abstract: In the last two decades, great progress has been made in molecular modeling through computational treatments of
biological molecules grounded in evolutionary search techniques. Evolutionary algorithms (EAs) are gaining popularity beyond
exploringtherelationshipbetweensequenceandfunctioninbiomolecules.Inparticular,recentworkisshowingthepromiseofEAs
inexploringstructurespacesofproteins,suchasdenovostructurepredictionandotherstructuremodelingproblems.Theobjective
of this tutorial is to introduce the Bioinformatics and Computational Biology, and Health Informatics community to the rapid
developments on EA-based frameworks for protein structure modeling through a concise but comprehensive review of
developmentsinthisdirectionoverthelastdecade.Thereviewwillbeaccompaniedwithspecificdetailedhighlightsandinteractive
software demonstrations of representative methods. The tutorial will introduce BCB researchers to solving open problems in
computationalstructuralbiologyusingpowerfulevolutionarysearchtechniques.
T7:TheISBCancerGenomicsCloud
SheilaM.Reynolds,InstituteforSystemsBiology
Abstract:TheISBCancerGenomicsCloud(ISB-CGC)isoneofthreepilotprojectsfundedbytheNationalCancerInstitutewiththe
goal 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 genomics
researchatunprecedentedscales.TheISB-CGCfacilitatescollaborativeresearchbyallowingscientiststosharedata,analyses,and
insights in a cloud environment. Tools, data, and resources that make up the ISB-CGC platform include an interactive web
application,dataleveragingvariousGoogleCloudtechnologiessuchasCloudStorage,BigQueryandGoogleGenomics,andopensourcecodeexamples.TheISB-CGCteamincludesscientistsandengineersfromtheInstituteforSystemsBiology(ISB),Google,and
CSRA.
T8:LivingtheDREAM:Crowdsourcingbiomedicalresearchthroughchallengesandensembles
GauravPandeyandRobertVogel,IcahnSchoolofMedicineatMountSinai
LaraMangraviteandSolveigSieberts,SageBionetworks
GustavoStolovitzky,IBMResearch
Abstract: The explosion in the scale, variety and complexity of biomedical datasets has necessitated an almost parallel growth of
advanced computational methods that can produce actionable knowledge from these datasets. This growth has led to a new
approach for addressing complex biomedical problems, namely the organization of unbiased crowdsourcing-based science
competitions/challenges. DREAM Challenges, the most prominent and comprehensive effort in this direction, engage
diversecommunitiesofexpertstoleveragethe“wisdomofcrowds”tosolvespecificbiomedicalproblemswithinfixedtimeperiods.
DREAMorganizershavelaunchedover35successfulchallenges,whichhaveattractedover8,000participantsandresultedinover
100publicationsusingDREAMdata.Thefirstpartofourtutorialwilldescribethemotivation,designandscientificimpactofDREAM
challenges. The participation of a large diverse community of experts in DREAM challenges offers a promising opportunity to
develop/learn challenge “ensembles” that automatically and effectively assimilate the rich knowledge embedded in the diverse
submissions made to the challenges. This diversity among the submissions calls for the development of novel heterogeneous
ensemblelearningmethods,whichwillbethefocusofthesecondpartofthetutorial.
Posters
1.
NoaRappaport,MichalTwik,RonNudel,InbarPlaschkes,TsippiInyStein,DanitOz-Levi,SimonFishilevich,MarilynSafran,
DoronLancet.IntegratedIdentificationofDisease-GeneLinksandtheirUtilityinNext-GenerationSequencing
Interpretation
2.
OmidGhiasvand,MaryShimoyama.IntroducingaTextAnnotationTool(OntoMate),AssistingCurationatRatGenome
Database
3.
Yoo-AhKim,SannaMadan,TeresaPrzytycka.WeSME:uncoveringmutualexclusivityofcancermutations
4.
IlyaZhbannikov,KonstantinArbeev,AnatoliyYashin.MultidimensionalStochasticProcessModelanditsApplicationsto
AnalysisofLongitudinalDatawithGeneticInformation
5.
ThomasHahn,HidayatRahman,RichardSegall.AdvancedFeature-DrivenDiseaseNamedEntityRecognitionUsing
ConditionalRandomFields
6.
EunjiKim,IvanIvanov,JianpingHua,RobertS.Chapkin,EdwardR.Dougherty.Model-basedstudyoftheEffectivenessof
ReportingListsofSmallFeatureSetsusingRNA-SeqData
7.
HasiniYatawatte,ChristianPoellabauer,SusanLatham.AutomatedCaptureofNaturalisticChildVocalizationsforHealth
Research
8.
ManalAlshehri,ImanRezaeian,AbedAlkhateeb,LuisRueda.AMachineLearningModelforDiscoveryofProteinIsoforms
asBiomarkers.
9.
SomyungOh,JeonghyeonHa,KyungwonLee,SejongOh.IntegratedVisualizationToolforDifferentiallyExpressedGenes
andGeneOntologyAnalysis
10. JaniquePeyper,NaomiWalker,RobertWilkinson,GraemeMeintjes,JonathanBlackburn.TheTB-IRISneutrophilproteome:
bioinformaticchallenges
11. RichardTillquist,ManuelLladser.Metric-spacePositioningSystems(MPS)forMachineLearning
12. ByunggilYoo,NeilMiller,GreysonTwist,ShaneCorder.TheCMHWarehouse-ACatalogofGeneticVariationinPatientsof
aChildren'sHospital
13. SalvadorEugenioCaoili.KineticandAffinityConstraintsonReactionsBetweenAntihaptenAntibodiesandNonpeptidicBCellEpitopes:ImplicationsforPredictingAntibody-MediatedModulationofPharmacokineticsandPharmacodynamics
14. TaeinKwon,EunjeongPark,HyukjaeChang.SmartRefrigeratorforHealthcareUsingFoodImageClassification
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15. MethunKamruzzaman,AnanthKalyanaraman,BalaKrishnamoorthy.CharacterizingtheRoleofEnvironmentonPhenotypic
TraitsusingTopologicalDataAnalysis
16. SurabhiAgrawal,ChunPanHon,SwatiGarg,AadarshSampath,ShanuSushmita,MartineDeCock.SequenceBased
PredictionofHospitalReadmissions
17. ChunPanHon,MayanaPereira,ShanuSushmita,AnkurTeredesai,MartineDeCock.RiskStratificationforHospital
ReadmissionofHeartFailurePatients:AMachineLearningApproach
18. NickThieme,KristinBennett.TimetoReactivationofLatentTuberculosisInfectionVariesbyLineage
19. MuhammadArifurRahman,NeilLawrence.AGaussianProcessModelforInferringtheDynamicTranscriptionFactor
Activity
20. FaizyAhsan,DoinaPrecup,MathieuBlanchette.PredictionofCellTypeSpecificTranscriptionFactorBindingSiteOccupancy
21. AmeliaBateman,ToddJ.Treangen,MihaiPop.LimitationsofCurrentApproachesforReference-Free,Graph-BasedVariant
Detection
22. PeterZ.Revesz.ALastGeneticContactTreeGenerationAlgorithmforaSetofHumanPopulations
23. BarneyPotter,JamesFix,AnnaRitz.ModelingCellSignalingNetworkswithPrize-CollectingSubhypernetworks
24. KarlMenzel,SuzyC.P.Renn,AnnaRitz.CopyNumberVariationandAdaptiveEvolutionaryRadiationsacrosstheAfrican
Cichlidphylogeny
25. TingWang,RichardH.Duerr,WeiChen.AnintegrativeanalysisofATAC-seqandRNA-seqdatainactivated,
CD4+CD45RO+CD196+humanTcellstreatedwithIL-1BandIL-23withorwithoutPGE2
26. ClaudioDaza,JosefaSantaMaria,IgnacioGomez,MarioBarbe,JavierTrincado,DanielCapurro.PhenotypingIntensiveCare
UnitPatientsUsingTemporalAbstractionsandTemporalPatternMatching
27. DanDeblasio,JohnKececioglu.AdaptiveLocalRealignmentviaParameterAdvising
28. ImanMohammadi,SeyedsasanHashemikhabir,TammyToscos,HuanmeiWu.HealthCareNeedsofUnderserved
PopulationsintheCityofIndianapolis
29. NicoleEzell,AnnaRitz.ReconstructingNeuronalSignalingPathwaysWiththePotentialforDisruptioninSchizophrenia
30. MohammadShahrokhEsfahani,AaronNewman,HenningStehr,FlorianScherer,JacobChabon,DavidKurtz,Robert
Tibshirani,MaximilianDiehn,AshAlizadeh.NoninvasiveCancerClassificationUsingDiverseGenomicFeaturesinCirculating
TumorDNA
31. NaveenaYanamala,LindseyBishop,VamsiKodali,PattiZeidler-Erdely,AaronErdely.Machinelearningtechniquespredict
andcharacterizetoxicitybetweendifferentmulti-walledcarbonnanotubes
32. HuananZhang,DavidRoe,RuiKuang.DetectingPopulation-differentiationCNVsinHumanPopulationTreebySparseGroup
Selection
33. JulienHerrmann,ZacharyWitter,NakulPatel,JonathanKho,DanielJanies,ÜmitV.Çatalyürek.Visualanalyticsonthe
spreadofpathogens
34. MarziehAyati,DanicaWiredja,DanielaSchlatzer,GouthamNarla,MarkRChance,MehmetKoyuturk.MoBaSon
PhosphorylationData
35. NeginBagherzadi,AlpOzgunBorcek,GulTokdemir,NergizCagiltay,HakanMaras.Analysisofneurooncologicaldatato
predictsuccessofoperationthroughclassification
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ProgramCommittee
NancyAmato,TexasA&MUniversity
RolfBackofen,UniversityofFreiburg
ChrisBailey-Kellogg,DartmouthCollege
AsaBen-Hur,ColoradoStateUniversity
CatherineBlake,Univ.ofIllinois,Urbana-Champaign
ChristinaBoucher,ColoradoStateUniversity
BethBritt,UniversityofWashington
DanielBrown,UniversityofWaterloo
YangCao,VirginiaTech
JohnChelico,NewYorkUniversity
BrianY.Chen,LehighUniversity
JakeChen,IndianaUniv.-PurdueUniv.Indianapolis
YiChen,NewJerseyInstituteofTechnology
JianlinJackCheng,UniversityofMissouri
Chih-LinChi,UniversityofMinnesota
A.ErcumentCicek,BilkentUniversity
MarkClement,BrighamYoungUniversity
TrevorCohen,UniversityofTexas,Houston
CarloCombi,UniversityofVerona
HectorCorradoBravo,Univ.ofMaryland,CollegePark
LenoreCowen,TuftsUniversity
BhaskarDasgupda,UniversityofIllinoisatChicago
PeterElkin,UniversityatBuffalo
EmreErtin,TheOhioStateUniversity
OliverEulenstein,IowaStateUniversity
JeffFerraro,TheUniversityofUtah
TerryGaasterland,UniversityofCalifornia,SanDiego
AndrewGentles,StanfordUniversity
AnanthGrama,PurdueUniversity
EricHall,CincinnatiChildren'sHospital
NuritHaspel,UniversityofMassachusetts,Boston
LenwoodHeath,VirginiaTech
VasantHonavar,PennsylvaniaStateUniversity
FereydounHormozdiari,UniversityofCalifornia,Davis
FilipJagodzinski,WesternWashingtonUniversity
XiaoqianJiang,UniversityofCalifornia,SanDiego
TamerKahveci,UniversityofFlorida
AnanthKalyanaraman,WashingtonStateUniversity
SreeramKannan,UniversityofWashington
JohnKececioglu,Co-Chair,UniversityofArizona
ZiaKhan,UniversityofMaryland,CollegePark
MehmetKoyuturk,CaseWesternReserveUniversity
AlbertLai,TheOhioStateUniversity
Su-InLee,UniversityofWashington
Hans-PeterLenhof,SaarlandUniversity
JingLi,CaseWesternReserveUniversity
HongfangLiu,MayoClinic
StefanoLonardi,UniversityofCalifornia,Riverside
ZhiyongLu,NationalInstitutesofHealth
HuiLu,UniversityofIllinoisatChicago
ShaunMahony,PennStateUniversity
BradMalin,VanderbiltUniversity
RamgopalMettu,TulaneUniversity
TijanaMilenkovic,UniversityofNotreDame
T.M.Murali,VirginiaTech
ChadMyers,UniversityofMinnesota
LuayNakhleh,RiceUniversity
ScottNarus,TheUniversityofUtah
WilliamStaffordNoble,UniversityofWashington
LaxmiParida,IBMTJWatsonResearchCenter
MihaiPop,UniversityofMaryland
GiuseppePozzi,PolitecnicodiMilano
TeresaPrzytycka,NationalInstitutesofHealth
PredragRadivojac,IndianaUniversity
SusanRea,IntermountainHealthcare
AnnaRitz,ReedCollege
LarryRuzzo,UniversityofWashington
FarrantSakaguchi,TheUniversityofUtah
HarmScherpbier,JeffersonCollege
RussellSchwartz,CarnegieMellonUniversity
SoumitraSengupta,ColumbiaUniversity
AmardaShehu,GeorgeMasonUniversity
XinghuaShi,UniversityofNorthCarolinaatCharlotte
MonaSingh,PrincetonUniversity
KristerSwenson,CNRS,UniversitédeMontpellier
JijunTang,UniversityofSouthCarolina
HaixuTang,IndianaUniversity
NurcanTuncbag,MassachusettsInstituteofTechnology
JasonWang,NewJerseyInstituteofTechnology
NicoleWeiskopf,OregonHealth&ScienceUniversity
ChunhuaWeng,ColumbiaUniversity
TravisWheeler,UniversityofMontana
AdamWilcox,Co-Chair,UniversityofWashington
AdamWright,BrighamandWomen'sHospital
JinboXu,ToyotaTechnologicalInstituteatChicago
NaveenaYanamala,CentersforDiseaseControland
Prevention
RuiZhang,UniversityofMinnesota
AidongZhang,Univ.atBuffalo,StateUniv.ofNewYork
MiZhang,MichiganStateUniversity
LiqingZhang,VirginiaTech
JieZhang,TheOhioStateUniversity
LiZhou,PartnersHealthcare
BinhaiZhu,MontanaStateUniversity
JaroslawZola,Univ.atBuffalo,StateUniv.ofNewYork
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