Investigating the efficacy of nonlinear dimensionality reduction schemes in classifying gene and protein expression studies

IEEE/ACM Transactions on Computational Biology and Bioinformatics

Volumn 5, Issue 3, 2008, Pages 368-384

  Lee, George ^a   Rodriguez, Carlos ^b   Madabhushi, Anant ^a  

^a RUTGERS UNIVERSITY   (United States)

^b Evri Inc   (United States)

Author keywords

Bioinformatics; Data clustering; Data visualization; Dimensionality reduction; Gene expression; Lung cancer; Machine learning; Manifold learning; Nonlinear dimensionality reduction; Ovarian cancer; Principal Component Analysis (PCA); Prostate cancer; Proteomics

Indexed keywords

BIOINFORMATICS; BIOMEDICAL DATA; CANCER DATA; CANCER DIAGNOSTICS; CLUSTER VALIDITY MEASURES; COMPUTER VISION PROBLEMS; CURSE OF DIMENSIONALITY; DATA CLUSTERING; DIMENSIONAL DATA; DIMENSIONALITY REDUCTION; DISCRIMINABILITY; EMBEDDINGS; EUCLIDEAN DISTANCES; EVALUATION MEASURES; EXPRESSION PROFILING; FACE DETECTION AND RECOGNITION; FEATURE PRUNING; GENE EXPRESSION; HIGH-DIMENSIONAL; HIGH-DIMENSIONAL DATA; INDIVIDUAL OBJECTS; INFORMATIVE GENES; LAPLACIAN EIGENMAPS; LINEAR DISCRIMINANT ANALYSIS; LOCALLY LINEAR EMBEDDING; LOW-DIMENSIONAL REPRESENTATION; LOW-DIMENSIONAL SPACE; LUNG CANCER; MACHINE LEARNING; MACHINE LEARNING TOOLS; MANIFOLD LEARNING; METHODS FOR ANALYSIS; MULTI-DIMENSIONAL SCALING; NON-LINEAR STRUCTURES; NONLINEAR DIMENSIONALITY REDUCTION; OVARIAN CANCER; PRINCIPAL COMPONENT ANALYSIS (PCA); PROSTATE CANCER; PROTEIN EXPRESSION PROFILE; PROTEIN EXPRESSIONS; PROTEOMICS; QUALITATIVE EVALUATIONS; SUBSPACE REPRESENTATION; SUPERVISED CLASSIFIERS;

AMINES; ARTIFICIAL INTELLIGENCE; CHLORINE COMPOUNDS; CLASSIFICATION (OF INFORMATION); COMPUTER VISION; DATA VISUALIZATION; DECISION MAKING; DECISION THEORY; DECISION TREES; DISCRIMINANT ANALYSIS; FACE RECOGNITION; FINANCIAL DATA PROCESSING; GENES; IMAGE PROCESSING; IMAGE RETRIEVAL; IMAGING TECHNIQUES; KNOWLEDGE BASED SYSTEMS; LEARNING SYSTEMS; MACHINE TOOLS; MEDICAL IMAGING; NONLINEAR ANALYSIS; PRINCIPAL COMPONENT ANALYSIS; PROTEINS; SUPPORT VECTOR MACHINES; TREES (MATHEMATICS); VECTORS;

QUALITY CONTROL;

ALGORITHM; ARTICLE; AUTOMATED PATTERN RECOGNITION; COMPUTER PROGRAM; GENE EXPRESSION PROFILING; METHODOLOGY; NONLINEAR SYSTEM; REPRODUCIBILITY; SENSITIVITY AND SPECIFICITY; STATISTICAL ANALYSIS;

ALGORITHMS; DATA INTERPRETATION, STATISTICAL; GENE EXPRESSION PROFILING; NONLINEAR DYNAMICS; PATTERN RECOGNITION, AUTOMATED; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY; SOFTWARE;

EID: 49249124314     PISSN: 15455963     EISSN: None     Source Type: Journal    
DOI: 10.1109/TCBB.2008.36     Document Type: Conference Paper

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