2020
Comprehensive characterization of hepatocyte-derived extracellular vesicles identifies direct miRNA-based regulation of hepatic stellate cells and DAMP-based hepatic macrophage IL-1β and IL-17 upregulation in alcoholic hepatitis mice
Eguchi A, Yan R, Pan S, Wu R, Kim J, Chen Y, Ansong C, Smith R, Tempaku M, Ohno-Machado L, Takei Y, Feldstein A, Tsukamoto H. Comprehensive characterization of hepatocyte-derived extracellular vesicles identifies direct miRNA-based regulation of hepatic stellate cells and DAMP-based hepatic macrophage IL-1β and IL-17 upregulation in alcoholic hepatitis mice. Journal Of Molecular Medicine 2020, 98: 1021-1034. PMID: 32556367, PMCID: PMC7810220, DOI: 10.1007/s00109-020-01926-7.Peer-Reviewed Original ResearchConceptsHepatic stellate cellsAlcoholic liver diseaseAlcoholic hepatitisAH miceIL-1βHepatic macrophagesStellate cellsExtracellular vesiclesPrimary hepatic stellate cellsIL-17 upregulationIL-17 productionUpregulated IL-1βHepatocyte-derived extracellular vesiclesNovel murine modelTLR9-dependent mannerMacrophage IL-1βHepatitis miceIL-17Liver diseaseControl miceCytokine productionLiver pathologyLiver fibrogenesisMurine modelΑ-SMA
2017
Extracellular vesicles released by hepatocytes from gastric infusion model of alcoholic liver disease contain a MicroRNA barcode that can be detected in blood
Eguchi A, Lazaro R, Wang J, Kim J, Povero D, Willliams B, Ho S, Stärkel P, Schnabl B, Ohno‐Machado L, Tsukamoto H, Feldstein A. Extracellular vesicles released by hepatocytes from gastric infusion model of alcoholic liver disease contain a MicroRNA barcode that can be detected in blood. Hepatology 2017, 65: 475-490. PMID: 27639178, PMCID: PMC5407075, DOI: 10.1002/hep.28838.Peer-Reviewed Original ResearchMeSH KeywordsAdultAgedAnalysis of VarianceAnimalsBiopsy, NeedleCells, CulturedDisease Models, AnimalExtracellular VesiclesFatty Liver, AlcoholicHepatocytesHumansImmunoblottingImmunohistochemistryMiceMicroRNAsMiddle AgedRandom AllocationReal-Time Polymerase Chain ReactionSampling StudiesSeverity of Illness IndexStatistics, NonparametricYoung AdultConceptsBlood extracellular vesiclesLiver injuryExtracellular vesiclesNuclear factor kappa BAlcoholic liver diseaseChronic liver injuryWeeks of infusionBile duct ligationB-cell lymphoma 2Levels of EVsFactor kappa BSteatohepatitis developmentNonalcoholic steatohepatitisLiver diseaseObese miceHepatic macrophagesDuct ligationKappa BMiR-340Cell originLymphoma 2Intragastric infusionMiceMiRNA signatureTime pointsMiRIAD update: using alternative polyadenylation, protein interaction network analysis and additional species to enhance exploration of the role of intragenic miRNAs and their host genes
Hinske L, dos Santos F, Ohara D, Ohno-Machado L, Kreth S, Galante P. MiRIAD update: using alternative polyadenylation, protein interaction network analysis and additional species to enhance exploration of the role of intragenic miRNAs and their host genes. Database 2017, 2017: bax053. PMID: 29220447, PMCID: PMC5569676, DOI: 10.1093/database/bax053.Peer-Reviewed Original Research
2014
miRIAD—integrating microRNA inter- and intragenic data
Hinske L, França G, Torres H, Ohara D, Lopes-Ramos C, Heyn J, Reis L, Ohno-Machado L, Kreth S, Galante P. miRIAD—integrating microRNA inter- and intragenic data. Database 2014, 2014: bau099. PMID: 25288656, PMCID: PMC4186326, DOI: 10.1093/database/bau099.Peer-Reviewed Original ResearchConceptsProtein-coding genesIntragenic miRNAsHost genesGene expressionProtein-protein interaction dataSmall non-coding RNAsHost gene functionHost gene expressionMiRNA binding sitesNon-coding RNAsMajority of miRNAsGene functionGenomic contextFunctional annotationFunctional network analysisTarget mRNAsExpression correlationExonic regionsGenesMiRNAsDifferent tissuesInteraction dataBinding sitesGenomic classificationSilico validation
2012
Setting Up an Intronic miRNA Database
Hinske L, Heyn J, Galante P, Ohno-Machado L, Kreth S. Setting Up an Intronic miRNA Database. Methods In Molecular Biology 2012, 936: 69-76. PMID: 23007499, DOI: 10.1007/978-1-62703-083-0_5.Peer-Reviewed Original ResearchConceptsAvailable information resourcesWeb-based toolInformation resourcesGenome-wide analysisHost gene transcriptionAnalysis techniquesIntergenic miRNAsIntragenic microRNAsWide analysisUseful analysis techniqueHost genesMiRNA databaseGene transcriptionMiRNA dataDifferent analysis techniquesMiRNAsSignificant attentionTranscriptionDatabaseMore informationRecent pastBasic structureTechniqueUnique linkageGenes
2011
Twist1-Induced Invadopodia Formation Promotes Tumor Metastasis
Eckert M, Lwin T, Chang A, Kim J, Danis E, Ohno-Machado L, Yang J. Twist1-Induced Invadopodia Formation Promotes Tumor Metastasis. Cancer Cell 2011, 19: 372-386. PMID: 21397860, PMCID: PMC3072410, DOI: 10.1016/j.ccr.2011.01.036.Peer-Reviewed Original ResearchMeSH KeywordsAdaptor Proteins, Vesicular TransportAnimalsBase SequenceBreast NeoplasmsCell LineCell Line, TumorCell MovementCell Surface ExtensionsElectrophoresis, Polyacrylamide GelEpithelial-Mesenchymal TransitionFemaleHEK293 CellsHumansMiceMice, NudeNeoplasm MetastasisNeoplasmsNuclear ProteinsReceptor, Platelet-Derived Growth Factor alphaReverse Transcriptase Polymerase Chain ReactionRNA InterferenceSignal TransductionSrc Homology DomainsTwist-Related Protein 1ConceptsInvadopodia formationTumor metastasisFormation of invadopodiaDirect transcriptional targetTwist1 transcription factorEMT-inducing signalsMatrix degradationPromotes Tumor MetastasisMembrane protrusionsExtracellular matrix degradationTranscriptional targetsTranscription factorsInvadopodiaPDGFRα expressionMesenchymal transitionTwist1Central mediatorPDGFRαKey functionsSnail2 is an Essential Mediator of Twist1-Induced Epithelial Mesenchymal Transition and Metastasis
Casas E, Kim J, Bendesky A, Ohno-Machado L, Wolfe C, Yang J. Snail2 is an Essential Mediator of Twist1-Induced Epithelial Mesenchymal Transition and Metastasis. Cancer Research 2011, 71: 245-254. PMID: 21199805, PMCID: PMC3025803, DOI: 10.1158/0008-5472.can-10-2330.Peer-Reviewed Original Research
2010
A potential role for intragenic miRNAs on their hosts' interactome
Hinske L, Galante P, Kuo W, Ohno-Machado L. A potential role for intragenic miRNAs on their hosts' interactome. BMC Genomics 2010, 11: 533. PMID: 20920310, PMCID: PMC3091682, DOI: 10.1186/1471-2164-11-533.Peer-Reviewed Original ResearchConceptsIntragenic miRNAsHost genesAdenylate/uridylate-rich elementsMiRNA targetsMRNA targetsHost interactomeGene cohortsMiRNA biogenesis pathwayNon-coding RNA moleculesHigh-confidence setMiRNA target genesProtein-coding regionsKEGG pathway analysisTight regulatory controlNegative feedback regulatorIntronic miRNAsMore intronsBiogenesis pathwayMiRNA genesNegative feedback loopUridylate-rich elementsCellular homeostasisTarget genesRNA moleculesInteractomeDSGeo: Software tools for cross-platform analysis of gene expression data in GEO
Lacson R, Pitzer E, Kim J, Galante P, Hinske C, Ohno-Machado L. DSGeo: Software tools for cross-platform analysis of gene expression data in GEO. Journal Of Biomedical Informatics 2010, 43: 709-715. PMID: 20435161, PMCID: PMC2934864, DOI: 10.1016/j.jbi.2010.04.007.Peer-Reviewed Original ResearchConceptsAggregation of dataData loaderRelational databaseGene expression dataUser preferencesData browserData browsingCross-platform dataSoftware toolsSeamless integrationCross-platform analysisGroups of dataQueriesExpression dataPublic gene expression dataSpecific sample characteristicsLarge resourcesBrowserToolBrowsingAnnotatingUsersRetrievalApplicationsPlatformTGF-beta1 interactome: metastasis and beyond.
Perera M, Tsang C, Distel R, Lacy J, Ohno-Machado L, Ricchiuti V, Samaranayake L, Smejkal G, Smith M, Trachtenberg A, Kuo W. TGF-beta1 interactome: metastasis and beyond. Cancer Genomics & Proteomics 2010, 7: 217-29. PMID: 20656987.Peer-Reviewed Reviews, Practice Guidelines, Standards, and Consensus StatementsConceptsDifferential expression profilesCancer therapeuticsPersonalized cancer therapeuticsRegulation of tumorEffective cancer therapeuticsNovel cancer biomarkersGenomic dataExpression profilesMetastatic attributesInteractomeUbiquitous cytokineTumor progressionCancer biomarkersPolarity changeTherapeuticsValuable insightsImmense valueRegulationInsightsInducerImportant stepMappingGrowth
2008
Validation of oligoarrays for quantitative exploration of the transcriptome
Nygaard V, Liu F, Holden M, Kuo W, Trimarchi J, Ohno-Machado L, Cepko C, Frigessi A, Glad I, van de Wiel M, Hovig E, Lyng H. Validation of oligoarrays for quantitative exploration of the transcriptome. BMC Genomics 2008, 9: 258. PMID: 18513391, PMCID: PMC2430212, DOI: 10.1186/1471-2164-9-258.Peer-Reviewed Original Research
2007
Comparison of hybridization-based and sequencing-based gene expression technologies on biological replicates
Liu F, Jenssen T, Trimarchi J, Punzo C, Cepko C, Ohno-Machado L, Hovig E, Patrick Kuo W. Comparison of hybridization-based and sequencing-based gene expression technologies on biological replicates. BMC Genomics 2007, 8: 153. PMID: 17555589, PMCID: PMC1899500, DOI: 10.1186/1471-2164-8-153.Peer-Reviewed Original ResearchConceptsDNA microarray platformMicroarray platformSequencing-based approachesSequencing-based technologiesGene expression technologyGene expression profilingTranscriptome profilingBiological replicatesExpression profilingExpression technologyGene expressionDifferential expressionBiomarker discoveryProfilingExpressionMicroarrayImportant tool
2006
Approximation properties of haplotype tagging
Vinterbo S, Dreiseitl S, Ohno-Machado L. Approximation properties of haplotype tagging. BMC Bioinformatics 2006, 7: 8. PMID: 16401341, PMCID: PMC1395335, DOI: 10.1186/1471-2105-7-8.Peer-Reviewed Original ResearchConceptsApproximation propertiesCombinatorial optimization problemsOptimization problemImplementable algorithmComputational effortSolution qualityTerms of complexitySimple algorithmSize m.Population membersSingle processor machineAlgorithmProblemAsymptoticsApproximationProcessor machineHaplotype taggingNPsUnique identification
2005
Representation in stochastic search for phylogenetic tree reconstruction
Weber G, Ohno-Machado L, Shieber S. Representation in stochastic search for phylogenetic tree reconstruction. Journal Of Biomedical Informatics 2005, 39: 43-50. PMID: 16359929, DOI: 10.1016/j.jbi.2005.11.001.Peer-Reviewed Original Research
2004
Genomic Analysis of Mouse Retinal Development
Blackshaw S, Harpavat S, Trimarchi J, Cai L, Huang H, Kuo W, Weber G, Lee K, Fraioli R, Cho S, Yung R, Asch E, Ohno-Machado L, Wong W, Cepko C. Genomic Analysis of Mouse Retinal Development. PLOS Biology 2004, 2: e247. PMID: 15226823, PMCID: PMC439783, DOI: 10.1371/journal.pbio.0020247.Peer-Reviewed Original ResearchMeSH KeywordsAnimalsBromodeoxyuridineCell LineageChromosome MappingCluster AnalysisComputational BiologyDatabases, GeneticExpressed Sequence TagsGene Expression RegulationGene Expression Regulation, DevelopmentalGene LibraryGenomeIn Situ HybridizationInterneuronsMiceMitosisMolecular Sequence DataNeurogliaOpen Reading FramesRetinaRNA, MessengerStem CellsTime FactorsConceptsMitotic progenitor cellsRetinal cell typesGene expressionCell typesExpression patternsRetinal developmentDevelopmental gene expression patternsGene expression patternsMajor retinal cell typesOpen reading frameProgenitor cellsMüller gliaPhotoreceptor-enriched genesGene expression profilesMouse retinal developmentMajor cell typesRetinal disease genesGenomic analysisMultiple retinal cell typesChromosomal intervalMolecular atlasMultiple transcriptsReading frameTaxonomic classificationDisease genes