angelova-targetedprojection-2006.pdf (162.9 kB)
Targeted projection pursuit for visualizing gene expression data classifications
journal contribution
posted on 2006-11-01, 00:00 authored by J Faith, R Mintram, Maia Angelova TurkedjievaMaia Angelova TurkedjievaUNLABELLED: We present a novel method for finding low-dimensional views of high-dimensional data: Targeted Projection Pursuit. The method proceeds by finding projections of the data that best approximate a target view. Two versions of the method are introduced; one version based on Procrustes analysis and one based on an artificial neural network. These versions are capable of finding orthogonal or non-orthogonal projections, respectively. The method is quantitatively and qualitatively compared with other dimension reduction techniques. It is shown to find 2D views that display the classification of cancers from gene expression data with a visual separation equal to, or better than, existing dimension reduction techniques. AVAILABILITY: source code, additional diagrams, and original data are available from
History
Journal
BioinformaticsVolume
22Issue
21Pagination
2667 - 2673Publisher
Oxford University PressLocation
Oxford, Eng.Publisher DOI
eISSN
1367-4811Language
engPublication classification
C1.1 Refereed article in a scholarly journalCopyright notice
2006, The AuthorUsage metrics
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AlgorithmsArtificial IntelligenceComputer GraphicsDatabase Management SystemsDatabases, GeneticGene Expression ProfilingInformation Storage and RetrievalOligonucleotide Array Sequence AnalysisPattern Recognition, AutomatedUser-Computer InterfaceScience & TechnologyLife Sciences & BiomedicineTechnologyPhysical SciencesBiochemical Research MethodsBiotechnology & Applied MicrobiologyComputer Science, Interdisciplinary ApplicationsMathematical & Computational BiologyStatistics & ProbabilityBiochemistry & Molecular BiologyComputer ScienceMathematicsCANCERPREDICTIONPATTERNS
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