2013
DNA-COMPACT: DNA COMpression Based on a Pattern-Aware Contextual Modeling Technique
Li P, Wang S, Kim J, Xiong H, Ohno-Machado L, Jiang X. DNA-COMPACT: DNA COMpression Based on a Pattern-Aware Contextual Modeling Technique. PLOS ONE 2013, 8: e80377. PMID: 24282536, PMCID: PMC3840021, DOI: 10.1371/journal.pone.0080377.Peer-Reviewed Original ResearchConceptsReference-free compressionDisk storage capacityCompression algorithmDecompression costData transferringArt algorithmsCompression performanceFile sizeGenome compressionCompression rateBit rateAlgorithmDNA compressionBiomedical researchersPerformance advantagesGenome dataModeling techniquesContextual modelImportant concernResearch purposesCompressionPerformanceStorage capacityBitsReference sequence
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
2001
Effects of Case Removal in Prognostic Models
Ohno-Machado L, Vinterbo S. Effects of Case Removal in Prognostic Models. Methods Of Information In Medicine 2001, 40: 32-38. PMID: 11310157, DOI: 10.1055/s-0038-1634461.Peer-Reviewed Original Research
2000
Unsupervised learning from complex data: the matrix incision tree algorithm.
Kim J, Ohno-Machado L, Kohane I. Unsupervised learning from complex data: the matrix incision tree algorithm. Biocomputing 2000, 30-41. PMID: 11262950, DOI: 10.1142/9789814447362_0004.Peer-Reviewed Original ResearchConceptsHigh-dimensional spaceTree algorithmComplex high-dimensional spacesPredictive model buildingData setsLarge-scale gene expression dataLow-dimensional spaceKnowledge discoveryUnsupervised learningData structureComplex dataNovel methodMeaningful structuresMicroarray data setsDNA microarray data setsAlgorithm