Minimum redundancy feature selection from microarray gene expression data.
about
Bioimage informatics: a new area of engineering biology.Delineating antibody recognition in polyclonal sera from patterns of HIV-1 isolate neutralizationConvergence of biomarkers, bioinformatics and nanotechnology for individualized cancer treatmentClassifying vulnerability to sleep deprivation using baseline measures of psychomotor vigilanceRefinement of light-responsive transcript lists using rice oligonucleotide arrays: evaluation of gene-redundancyPrediction and analysis of protein hydroxyproline and hydroxylysineDISIS: prediction of drug response through an iterative sure independence screeningGene Ontology and KEGG Pathway Enrichment Analysis of a Drug Target-Based Classification SystemThe Use of Gene Ontology Term and KEGG Pathway Enrichment for Analysis of Drug Half-LifeDevelopment of a general analysis and unfolding scheme and its application to measure the energy spectrum of atmospheric neutrinos with IceCube: IceCube CollaborationREGULATOR: a database of metazoan transcription factors and maternal factors for developmental studiesPattern recognition software and techniques for biological image analysisA graph-theoretic approach for identifying non-redundant and relevant gene markers from microarray data using multiobjective binary PSOAlgorithmic approaches to protein-protein interaction site prediction.Crysalis: an integrated server for computational analysis and design of protein crystallization.Utilizing spatial and spectral features of photoacoustic imaging for ovarian cancer detection and diagnosis.Information theory filters for wavelet packet coefficient selection with application to corrosion type identification from acoustic emission signals.Combining multiple hypothesis testing and affinity propagation clustering leads to accurate, robust and sample size independent classification on gene expression data.Multiscale integration of -omic, imaging, and clinical data in biomedical informatics.The utility of data-driven feature selection: re: Chu et al. 2012.NetBenchmark: a bioconductor package for reproducible benchmarks of gene regulatory network inference.Feature Selection for high Dimensional DNA Microarray data using hybrid approaches.Experimental assessment of static and dynamic algorithms for gene regulation inference from time series expression data.Different perspectives on object oriented data analysis.Inference and validation of predictive gene networks from biomedical literature and gene expression data.Similarity-based prediction for Anatomical Therapeutic Chemical classification of drugs by integrating multiple data sources.GenInfoGuard--a robust and distortion-free watermarking technique for genetic data.Preprocessing of NMR metabolomics data.Hierarchical gene selection and genetic fuzzy system for cancer microarray data classification.Reverse Engineering of Genome-wide Gene Regulatory Networks from Gene Expression DataFrom genome-scale data to models of infectious disease: A Bayesian network-based strategy to drive model development.Using Data Independent Acquisition (DIA) to Model High-responding Peptides for Targeted Proteomics Experiments.A Robust Supervised Variable Selection for Noisy High-Dimensional DataMorphometric model for discrimination between glioblastoma multiforme and solitary metastasis using three-dimensional shape analysis.MetaBoot: a machine learning framework of taxonomical biomarker discovery for different microbial communities based on metagenomic data.Image-Based Tissue Distribution Modeling for Skeletal Muscle Quality Characterization.Discretization of gene expression data revised.Pan-cancer analysis for studying cancer stage using protein expression dataIntegration of multimodal RNA-seq data for prediction of kidney cancer survival.Applying Cost-Sensitive Extreme Learning Machine and Dissimilarity Integration to Gene Expression Data Classification.
P2860
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P2860
Minimum redundancy feature selection from microarray gene expression data.
description
2005 nî lūn-bûn
@nan
2005 թուականի Ապրիլին հրատարակուած գիտական յօդուած
@hyw
2005 թվականի ապրիլին հրատարակված գիտական հոդված
@hy
2005年の論文
@ja
2005年論文
@yue
2005年論文
@zh-hant
2005年論文
@zh-hk
2005年論文
@zh-mo
2005年論文
@zh-tw
2005年论文
@wuu
name
Minimum redundancy feature selection from microarray gene expression data.
@ast
Minimum redundancy feature selection from microarray gene expression data.
@en
type
label
Minimum redundancy feature selection from microarray gene expression data.
@ast
Minimum redundancy feature selection from microarray gene expression data.
@en
prefLabel
Minimum redundancy feature selection from microarray gene expression data.
@ast
Minimum redundancy feature selection from microarray gene expression data.
@en
P1476
Minimum redundancy feature selection from microarray gene expression data.
@en
P2093
Chris Ding
Hanchuan Peng
P304
P356
10.1142/S0219720005001004
P577
2005-04-01T00:00:00Z