Recursive SVM feature selection and sample classification for mass-spectrometry and microarray data. - Wikidata - wikimedia - TriplyDB

Recursive SVM feature selection and sample classification for mass-spectrometry and microarray data.

Recursive SVM feature selection and sample classification for mass-spectrometry and microarray data.

http://www.wikidata.org/entity/Q31036404

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METAGENassist: a comprehensive web server for comparative metagenomics MetaboAnalyst: a web server for metabolomic data analysis and interpretation A survey of computational tools for downstream analysis of proteomic and other omic datasets Metabolism and breast cancer risk: frontiers in research and practice A Review of Feature Selection and Feature Extraction Methods Applied on Microarray Data Opportunities and limitations of SELDI-TOF-MS in biomedical research: practical advices Predictive Power Estimation Algorithm (PPEA)--a new algorithm to reduce overfitting for genomic biomarker discovery Cardiovascular genomics: a biomarker identification pipeline Intoxicated Speech Detection: A Fusion Framework with Speaker-Normalized Hierarchical Functionals and GMM Supervectors.Re-sampling strategy to improve the estimation of number of null hypotheses in FDR control under strong correlation structures.Signal processing for metagenomics: extracting information from the soup.Recursive cluster elimination (RCE) for classification and feature selection from gene expression data.Classification and biomarker identification using gene network modules and support vector machines Mass spectrometry cancer data classification using wavelets and genetic algorithm.Challenges of Inversely Estimating Jacobian from Metabolomics Data.Ensemble Feature Learning of Genomic Data Using Support Vector Machine.Classification and feature selection algorithms for multi-class CGH data.Use of SELDI-TOF mass spectrometry for identification of new biomarkers: potential and limitations.Estimation of relevant variables on high-dimensional biological patterns using iterated weighted kernel functions.A stable iterative method for refining discriminative gene clusters.A data-mining approach to biomarker identification from protein profiles using discrete stationary wavelet transform.DFP: a Bioconductor package for fuzzy profile identification and gene reduction of microarray data.Do serum biomarkers really measure breast cancer?New potential biomarkers in the diagnosis of esophageal squamous cell carcinoma.The validation and assessment of machine learning: a game of prediction from high-dimensional data.Convergent Random Forest predictor: methodology for predicting drug response from genome-scale data applied to anti-TNF response.A scale space approach for unsupervised feature selection in mass spectra classification for ovarian cancer detection.Ovarian cancer classification based on dimensionality reduction for SELDI-TOF data.Module-based prediction approach for robust inter-study predictions in microarray data.Effect of finite sample size on feature selection and classification: a simulation study Biomarker discovery and redundancy reduction towards classification using a multi-factorial MALDI-TOF MS T2DM mouse model dataset.Sequence features that drive human promoter function and tissue specificity.Top scoring pairs for feature selection in machine learning and applications to cancer outcome prediction.Segmentation of multi-isotope imaging mass spectrometry data for semi-automatic detection of regions of interest Pairwise protein expression classifier for candidate biomarker discovery for early detection of human disease prognosis.Peripheral blood gene expression as a novel genomic biomarker in complicated sarcoidosis.Revealing metabolite biomarkers for acupuncture treatment by linear programming based feature selection Are there any differences between features of proteins expressed in malignant and benign breast cancers?Alignment-free supervised classification of metagenomes by recursive SVM.Statistical analysis of a lung cancer spectral histopathology (SHP) data set.

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P2860

Recursive SVM feature selection and sample classification for mass-spectrometry and microarray data.

http://www.wikidata.org/entity/Q31036404

description

2006 nî lūn-bûn

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2006 թուականի Ապրիլին հրատարակուած գիտական յօդուած

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2006 թվականի ապրիլին հրատարակված գիտական հոդված

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2006年の論文

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2006年論文

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2006年論文

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2006年論文

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2006年論文

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2006年論文

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2006年论文

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Recursive SVM feature selectio ...... ctrometry and microarray data.

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Recursive SVM feature selectio ...... ctrometry and microarray data.

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Recursive SVM feature selectio ...... ctrometry and microarray data.

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Recursive SVM feature selectio ...... ctrometry and microarray data.

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Recursive SVM feature selectio ...... ctrometry and microarray data.

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Recursive SVM feature selectio ...... ctrometry and microarray data.

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Alexander Miron

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Hon-Chiu E Leung

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James D Iglehart

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Jun S Liu

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Lyndsay N Harris

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Qian Shi

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Wing H Wong

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Xin Lu

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Xiu-Qin Xu

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Xuegong Zhang

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P2860

Entropy-based gene ranking without selection bias for the predictive classification of microarray data

Gene expression patterns of breast carcinomas distinguish tumor subclasses with clinical implications

Gene expression profiling predicts clinical outcome of breast cancer

Molecular classification of cancer: class discovery and class prediction by gene expression monitoring

Molecular portraits of human breast tumours

Recursive partitioning for tumor classification with gene expression microarray data

Gene assessment and sample classification for gene expression data using a genetic algorithm/k-nearest neighbor method.

Selection bias in gene extraction on the basis of microarray gene-expression data.

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Use of proteomic patterns in serum to identify ovarian cancer.

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