2018
Predict effective drug combination by deep belief network and ontology fingerprints
Chen G, Tsoi A, Xu H, Zheng W. Predict effective drug combination by deep belief network and ontology fingerprints. Journal Of Biomedical Informatics 2018, 85: 149-154. PMID: 30081101, DOI: 10.1016/j.jbi.2018.07.024.Peer-Reviewed Original Research
2017
Finding useful data across multiple biomedical data repositories using DataMed
Ohno-Machado L, Sansone S, Alter G, Fore I, Grethe J, Xu H, Gonzalez-Beltran A, Rocca-Serra P, Gururaj A, Bell E, Soysal E, Zong N, Kim H. Finding useful data across multiple biomedical data repositories using DataMed. Nature Genetics 2017, 49: 816-819. PMID: 28546571, PMCID: PMC6460922, DOI: 10.1038/ng.3864.Peer-Reviewed Original ResearchMeSH KeywordsBiological OntologiesBiomedical ResearchComputational BiologyDatabases, FactualHumansMetadataSoftwareSystems IntegrationConceptsBiomedical data repositoriesHealth big dataData setsKnowledge discoveryBig dataMultiple repositoriesSearch enginesData indexFAIR principlesDataMedData repositoryService providersKnowledge initiativesKnowledge expertsBiomedical research communityResearch communityRepositoryScience landscapeUseful dataInteroperabilityMetadataFindabilitySetEngineData
2016
Leveraging syntactic and semantic graph kernels to extract pharmacokinetic drug drug interactions from biomedical literature
Zhang Y, Wu H, Xu J, Wang J, Soysal E, Li L, Xu H. Leveraging syntactic and semantic graph kernels to extract pharmacokinetic drug drug interactions from biomedical literature. BMC Systems Biology 2016, 10: 67. PMID: 27585838, PMCID: PMC5009562, DOI: 10.1186/s12918-016-0311-2.Peer-Reviewed Original ResearchMeSH KeywordsBiomedical ResearchComputational BiologyComputer GraphicsData MiningDrug InteractionsPharmacokineticsPublicationsSemanticsConceptsPaths graph kernelGraph kernelsSemantic classesSemantic informationBiomedical literatureShallow semantic representationsText mining techniquesBest F-scoreAutomatic DDI extractionProblem of sparsenessDependency structureSemantic graphDDI detectionKnowledge basesDDI corpusF-scoreDDI extractionSemantic representationNovel approachExperimental resultsKernelHigh precisionInformationSparsenessGraphChemical named entity recognition in patents by domain knowledge and unsupervised feature learning
Zhang Y, Xu J, Chen H, Wang J, Wu Y, Prakasam M, Xu H. Chemical named entity recognition in patents by domain knowledge and unsupervised feature learning. Database 2016, 2016: baw049. PMID: 27087307, PMCID: PMC4834204, DOI: 10.1093/database/baw049.Peer-Reviewed Original ResearchConceptsMachine learning-based systemsLearning-based systemConditional Random FieldsDomain knowledgeEntity recognitionMatthews correlation coefficientDrug Named Entity RecognitionBioCreative V challengeInformation extraction systemWord representation featuresUnsupervised feature learningUnsupervised learning algorithmNamed Entity RecognitionSemantic type informationSupport vector machinePrecision-recall curveBrown clusteringFeature learningFeature engineeringUnsupervised featureIndividual subtasksMining systemNER taskLearning algorithmCPD taskToward Repurposing Metformin as a Precision Anti-Cancer Therapy Using Structural Systems Pharmacology
Hart T, Dider S, Han W, Xu H, Zhao Z, Xie L. Toward Repurposing Metformin as a Precision Anti-Cancer Therapy Using Structural Systems Pharmacology. Scientific Reports 2016, 6: 20441. PMID: 26841718, PMCID: PMC4740793, DOI: 10.1038/srep20441.Peer-Reviewed Original ResearchConceptsPrecision anti-cancer therapyMolecular basisAnti-cancer therapyStructural systems pharmacologyProtein-protein interactionsDrug target identificationNetwork biology analysisMolecular targetsInteractomic dataGenetic interactionsStructural proteomeGenetic networksKey molecular targetsPhenotypic responsesKinase targetsBiology analysisCancer mutationsPleiotropic effectsAnti-cancer effectsNetwork biomarkersTarget identificationGenetic biomarkersSystems pharmacology approachKey nodesTarget
2015
Deciphering Signaling Pathway Networks to Understand the Molecular Mechanisms of Metformin Action
Sun J, Zhao M, Jia P, Wang L, Wu Y, Iverson C, Zhou Y, Bowton E, Roden D, Denny J, Aldrich M, Xu H, Zhao Z. Deciphering Signaling Pathway Networks to Understand the Molecular Mechanisms of Metformin Action. PLOS Computational Biology 2015, 11: e1004202. PMID: 26083494, PMCID: PMC4470683, DOI: 10.1371/journal.pcbi.1004202.Peer-Reviewed Original ResearchConceptsGWAS datasetsPathway networkDisease genesGenome-wide association study datasetDrug targetsSignal transduction networksSignal transduction cascadeMultiple signaling pathwaysDrug-induced gene expressionNovel drug targetsTransduction networksTransduction cascadeEnrichment analysisGene expressionCommon genesMolecular mechanismsSignaling pathwaysGenesNovel MycLiterature miningMolecular modePathwayMetformin actionDrug actionDisease pathogenesisA weighted and integrated drug-target interactome: drug repurposing for schizophrenia as a use case
Huang L, Soysal E, Zheng W, Zhao Z, Xu H, Sun J. A weighted and integrated drug-target interactome: drug repurposing for schizophrenia as a use case. BMC Systems Biology 2015, 9: s2. PMID: 26100720, PMCID: PMC4474536, DOI: 10.1186/1752-0509-9-s4-s2.Peer-Reviewed Original ResearchEducation, collaboration, and innovation: intelligent biology and medicine in the era of big data
Ruan J, Jin V, Huang Y, Xu H, Edwards J, Chen Y, Zhao Z. Education, collaboration, and innovation: intelligent biology and medicine in the era of big data. BMC Genomics 2015, 16: s1. PMID: 26099197, PMCID: PMC4474420, DOI: 10.1186/1471-2164-16-s7-s1.Peer-Reviewed Original ResearchA comparative study of disease genes and drug targets in the human protein interactome
Sun J, Zhu K, Zheng W, Xu H. A comparative study of disease genes and drug targets in the human protein interactome. BMC Bioinformatics 2015, 16: s1. PMID: 25861037, PMCID: PMC4402590, DOI: 10.1186/1471-2105-16-s5-s1.Peer-Reviewed Original ResearchConceptsGenome-wide association studiesDisease genesDrug targetsHuman protein-coding genesHuman protein-protein interaction networkProtein-protein interaction networkProtein-coding genesHuman protein interactomeComplex diseasesNovel drug targetsProtein interactomeAnatomical Therapeutic Chemical (ATC) classificationInteraction networksDisease proteinAssociation studiesGenesDisease categoriesInteractomeProteinMajor disease categoriesDifferent disease categoriesFirst comprehensive comparisonTargetTreatment efficacyHigh betweenness
2014
Integrative Genomics and Computational Systems Medicine
McDermott J, Huang Y, Zhang B, Xu H, Zhao Z. Integrative Genomics and Computational Systems Medicine. BioMed Research International 2014, 2014: 945253. PMID: 25025078, PMCID: PMC4082850, DOI: 10.1155/2014/945253.Peer-Reviewed Original ResearchComputational methods for omics data.
Zhao Z, Zhang B, Huang Y, Xu H, McDermott J. Computational methods for omics data. International Journal Of Computational Biology And Drug Design 2014, 7: 97-101. PMID: 24878722, DOI: 10.1504/ijcbdd.2014.Peer-Reviewed Original ResearchComputational Biology
2013
Interdisciplinary dialogue for education, collaboration, and innovation: Intelligent Biology and Medicine in and beyond 2013
Zhang B, Huang Y, McDermott J, Posey R, Xu H, Zhao Z. Interdisciplinary dialogue for education, collaboration, and innovation: Intelligent Biology and Medicine in and beyond 2013. BMC Genomics 2013, 14: s1. PMID: 24564388, PMCID: PMC4042234, DOI: 10.1186/1471-2164-14-s8-s1.Peer-Reviewed Original Research
2012
Genetic studies of complex human diseases: Characterizing SNP-disease associations using Bayesian networks
Han B, Chen X, Talebizadeh Z, Xu H. Genetic studies of complex human diseases: Characterizing SNP-disease associations using Bayesian networks. BMC Systems Biology 2012, 6: s14. PMID: 23281790, PMCID: PMC3524021, DOI: 10.1186/1752-0509-6-s3-s14.Peer-Reviewed Original ResearchMeSH KeywordsAlgorithmsAlzheimer DiseaseArtificial IntelligenceAutistic DisorderBayes TheoremComputational BiologyComputer SimulationDatabases, GeneticEpistasis, GeneticGenome-Wide Association StudyHumansMacular DegenerationMarkov ChainsModels, GeneticMonte Carlo MethodPolymorphism, Single NucleotideConceptsEpistatic interaction detectionBayesian network structure learning methodTwo-layer Bayesian networkBayesian network-based methodBayesian networkInteraction detectionMarkov chain Monte Carlo methodsStructure learning methodReal disease dataNetwork-based methodReal GWAS datasetMonte Carlo methodHigh-order epistatic interactionsMachine learningSearch spaceLearning methodsDisease datasetCarlo methodTarget nodeModel complexityStatistical methodsReal dataNew scoring functionComplex human diseasesDatasetAdvances in systems biology: computational algorithms and applications
Huang Y, Zhao Z, Xu H, Shyr Y, Zhang B. Advances in systems biology: computational algorithms and applications. BMC Systems Biology 2012, 6: s1. PMID: 23281622, PMCID: PMC3524016, DOI: 10.1186/1752-0509-6-s3-s1.Peer-Reviewed Original ResearchMeSH KeywordsAlgorithmsAnimalsBiomedical ResearchComputational BiologyGene Regulatory NetworksGenetic Association StudiesGenomicsHumansModels, AnimalSystems BiologyGenomics in 2012: challenges and opportunities in the next generation sequencing era
Zhao Z, Huang Y, Zhang B, Shyr Y, Xu H. Genomics in 2012: challenges and opportunities in the next generation sequencing era. BMC Genomics 2012, 13: s1. PMID: 23281891, PMCID: PMC3535713, DOI: 10.1186/1471-2164-13-s8-s1.Peer-Reviewed Original ResearchMeSH KeywordsComputational BiologyDatabases, FactualGenomicsHigh-Throughput Nucleotide SequencingHumansSystems BiologyConceptsNext-generation sequencing eraDTome: a web-based tool for drug-target interactome construction
Sun J, Wu Y, Xu H, Zhao Z. DTome: a web-based tool for drug-target interactome construction. BMC Bioinformatics 2012, 13: s7. PMID: 22901092, PMCID: PMC3372450, DOI: 10.1186/1471-2105-13-s9-s7.Peer-Reviewed Original ResearchMeSH KeywordsAlgorithmsClozapineComputational BiologyDatabases, FactualDrug DiscoveryDrug InteractionsHumansInternetProteinsSoftwareUser-Computer InterfaceConceptsWeb-based toolUser-friendly web interfaceWeb-based queriesRich data sourceDifferent knowledge basesDatabase schemaWeb interfaceVisualization processKnowledge basesComputational workflowDiscovery processData sourcesNetworkDrug-target interactionsDrugs' primary targetsDrug-target networkWorkflowEarly-stage drug discoveryNetwork analysisQueriesToolPromising approachDrug discovery processSchemaDetailed network analysis
2011
RANKING GENE-DRUG RELATIONSHIPS IN BIOMEDICAL LITERATURE USING LATENT DIRICHLET ALLOCATION
Altman R, Dunker A, Hunter L, Murray T, Klein T, WU Y, LIU M, ZHENG W, ZHAO Z, XU H. RANKING GENE-DRUG RELATIONSHIPS IN BIOMEDICAL LITERATURE USING LATENT DIRICHLET ALLOCATION. Biocomputing 2011, 422-33. PMID: 22174297, PMCID: PMC4095990, DOI: 10.1142/9789814366496_0041.Peer-Reviewed Original Research
2006
Natural language processing and visualization in the molecular imaging domain
Tulipano P, Tao Y, Millar W, Zanzonico P, Kolbert K, Xu H, Yu H, Chen L, Lussier Y, Friedman C. Natural language processing and visualization in the molecular imaging domain. Journal Of Biomedical Informatics 2006, 40: 270-281. PMID: 17084109, DOI: 10.1016/j.jbi.2006.08.002.Peer-Reviewed Original ResearchMeSH KeywordsAnimalsCell LineComputational BiologyDatabases, BibliographicDatabases, GeneticDiagnostic ImagingGenomicsHumansInformation Storage and RetrievalNatural Language ProcessingPhenotypeProgramming LanguagesSoftwareSystems IntegrationTerminology as TopicUser-Computer InterfaceVocabulary, ControlledConceptsImaging domainNatural language processing systemsNatural language processingLanguage processing systemJava viewerNLP systemsFormal evaluation studiesLanguage processingInformation resourcesProcessing systemMedical imagingIndex imagesSystem performanceBiological informationInformationImagesVisualizationBioMedLEEPerformanceNLPEvaluation studyDomainGenomics literatureSystemSimultaneous visualizationMachine learning and word sense disambiguation in the biomedical domain: design and evaluation issues
Xu H, Markatou M, Dimova R, Liu H, Friedman C. Machine learning and word sense disambiguation in the biomedical domain: design and evaluation issues. BMC Bioinformatics 2006, 7: 334. PMID: 16822321, PMCID: PMC1550263, DOI: 10.1186/1471-2105-7-334.Peer-Reviewed Original ResearchConceptsNatural language processingBiomedical domainInformation retrieval systemsML methodsWSD classifierSense disambiguationMachine learning methodsVector machine classifierError rateWord sense disambiguationRetrieval systemMachine learningML techniquesText miningBiomedical abbreviationsLanguage processingLearning methodsCross-validation methodWSD problemMachine classifierAccurate accessSense distributionClassifierBiomolecular entitiesWSD task