AUC-RF: a new strategy for genomic profiling with random forest.
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Random Forest (RF) Wrappers for Waveband Selection and Classification of Hyperspectral Data.Toward the integration of Omics data in epidemiological studies: still a "long and winding road".Random forests for genomic data analysis.An AUC-based permutation variable importance measure for random forestsApplication of multi-SNP approaches Bayesian LASSO and AUC-RF to detect main effects of inflammatory-gene variants associated with bladder cancer risk.Discovery of a Novel Immune Gene Signature with Profound Prognostic Value in Colorectal Cancer: A Model of Cooperativity Disorientation Created in the Process from Development to Cancer.Microbiota-based model improves the sensitivity of fecal immunochemical test for detecting colonic lesionsLooking for a Signal in the Noise: Revisiting Obesity and the Microbiome.Comparison of different statistical approaches for urinary peptide biomarker detection in the context of coronary artery disease.Ensemble Merit Merge Feature Selection for Enhanced Multinomial Classification in Alzheimer's Dementia.DNA from fecal immunochemical test can replace stool for detection of colonic lesions using a microbiota-based modelCompensation of feature selection biases accompanied with improved predictive performance for binary classification by using a novel ensemble feature selection approach.A novel tool for predicting extracapsular extension during graded partial nerve sparing in radical prostatectomy.Effects of Plasma Transfusion on Perioperative Bleeding Complications: A Machine Learning ApproachRandom Forest Algorithm for the Classification of Neuroimaging Data in Alzheimer's Disease: A Systematic Review.Improved high-dimensional prediction with Random Forests by the use of co-data.Microbial Functional Gene Diversity Predicts Groundwater Contamination and Ecosystem Functioning.Genetic diversity and distribution of Senegalia senegal (L.) Britton under climate change scenarios in West Africa.Development and validation of a diagnostic model for early differentiation of sepsis and non-infectious SIRS in critically ill children - a data-driven approach using machine-learning algorithms.Fecal Microbiota Signatures Are Associated with Response to Ustekinumab Therapy among Crohn's Disease Patients.Clostridium difficile Alters the Structure and Metabolism of Distinct Cecal Microbiomes during Initial Infection To Promote Sustained Colonization.Dysbiosis of the salivary microbiota in pediatric-onset primary sclerosing cholangitis and its potential as a biomarker.A taxonomic signature of obesity in a large study of American adults.Rise and fall in diversity of Neogene marine vertebrates on the temperate Pacific coast of South AmericaQSAR and Molecular Modeling Approaches for Prediction of Drug MetabolismOverview of random forest methodology and practical guidance with emphasis on computational biology and bioinformatics
P2860
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P2860
AUC-RF: a new strategy for genomic profiling with random forest.
description
2011 nî lūn-bûn
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2011年の論文
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2011年学术文章
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2011年学术文章
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name
AUC-RF: a new strategy for genomic profiling with random forest.
@en
AUC-RF: a new strategy for genomic profiling with random forest.
@nl
type
label
AUC-RF: a new strategy for genomic profiling with random forest.
@en
AUC-RF: a new strategy for genomic profiling with random forest.
@nl
prefLabel
AUC-RF: a new strategy for genomic profiling with random forest.
@en
AUC-RF: a new strategy for genomic profiling with random forest.
@nl
P2860
P356
P1433
P1476
AUC-RF: a new strategy for genomic profiling with random forest.
@en
P2093
M Luz Calle
Victor Urrea
P2860
P304
P356
10.1159/000330778
P577
2011-10-11T00:00:00Z