2001
Global Analysis of Protein Activities Using Proteome Chips
Zhu H, Bilgin M, Bangham R, Hall D, Casamayor A, Bertone P, Lan N, Jansen R, Bidlingmaier S, Houfek T, Mitchell T, Miller P, Dean R, Gerstein M, Snyder M. Global Analysis of Protein Activities Using Proteome Chips. Science 2001, 293: 2101-2105. PMID: 11474067, DOI: 10.1126/science.1062191.Peer-Reviewed Original ResearchMeSH KeywordsAmino Acid MotifsAmino Acid SequenceCalmodulinCalmodulin-Binding ProteinsCell MembraneCloning, MolecularFungal ProteinsGlucoseLiposomesMembrane ProteinsMolecular Sequence DataOpen Reading FramesPeptide LibraryPhosphatidylcholinesPhosphatidylinositolsPhospholipidsProtein BindingProteomeRecombinant Fusion ProteinsSaccharomyces cerevisiaeSignal TransductionStreptavidinConceptsYeast proteome microarraysDiverse biochemical activitiesOpen reading framePotential binding motifsProtein-drug interactionsEukaryotic proteomesYeast proteomeProteome chipsPosttranslational modificationsReading frameCorresponding proteinNew calmodulinProtein activityBinding motifBiochemical activityProteome microarrayProteinProteomeMicroarrayCalmodulinGlobal analysisMotifPhospholipidsActivityIntegration of Multidisciplinary Sensory Data
Miller P, Nadkarni P, Singer M, Marenco L, Hines M, Shepherd G. Integration of Multidisciplinary Sensory Data. Journal Of The American Medical Informatics Association 2001, 8: 34-48. PMID: 11141511, PMCID: PMC134590, DOI: 10.1136/jamia.2001.0080034.Peer-Reviewed Original ResearchConceptsNeuroinformatics researchFlexible data modelDiverse heterogeneous dataHuman Brain ProjectNew informatics technologiesHeterogeneous dataData modelSensory dataRelated toolsInformatics technologiesBrain ProjectBuilding databaseSingle unifying frameworkUnifying frameworkProject approachIntegrationComputer model
1997
Olfactory Receptor Database (ORDB): A Resource for Sharing and Analyzing Published and Unpublished Data
Healy M, Smith J, Singer M, Nadkarni P, Skoufos E, Miller P, Shepherd G. Olfactory Receptor Database (ORDB): A Resource for Sharing and Analyzing Published and Unpublished Data. Chemical Senses 1997, 22: 321-326. PMID: 9218144, DOI: 10.1093/chemse/22.3.321.Peer-Reviewed Original Research
1991
Parallel computation and FASTA: confronting the problem of parallel database search for a fast sequence comparison algorithm
Miller P, Nadkarni P, Carriero N. Parallel computation and FASTA: confronting the problem of parallel database search for a fast sequence comparison algorithm. Bioinformatics 1991, 7: 71-78. PMID: 2004277, DOI: 10.1093/bioinformatics/7.1.71.Peer-Reviewed Original ResearchMeSH KeywordsAlgorithmsAmino Acid SequenceComputer SystemsMathematical ComputingMolecular Sequence DataProgramming LanguagesSoftware DesignConceptsSequence comparison algorithmAmount of computationMachine-independent parallel programming languageComparison algorithmsDisk I/OParallel programming languageParallel program runsO bottleneck problemDifferent parallel machinesBiological sequence comparisonNumber of processorsTime-consuming computationProgramming languageParallelization strategyParallel computationParallel machinesProgram design strategiesProgram runBottleneck problemFASTA algorithmFASTAAlgorithmComputationBottleneckGeneral problemParallel computation for biological sequence comparison: comparing a portable model to the native model for the Intel Hypercube.
Nadkarni P, Miller P. Parallel computation for biological sequence comparison: comparing a portable model to the native model for the Intel Hypercube. AMIA Annual Symposium Proceedings 1991, 404-8. PMID: 1807632, PMCID: PMC2247563.Peer-Reviewed Original ResearchConceptsMachine-independent parallel programming languageIntel HypercubeVirtual parallel machineParallel programming languageBiological sequence comparisonNumber of processorsParallel programmingParallel programsProgramming languageParallel computationDesktop workstationsParallel machinesProgramming commandsApplication areasPortable modelProcessorsLindaBenchmark testsNative modelsHypercubeParallelizationCase studyWorkstationsVersionMachine