Combining multiple approaches for gene microarray classification.
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Gene expression prediction using low-rank matrix completion.Recognition of multiple imbalanced cancer types based on DNA microarray data using ensemble classifiers.A kernel-based multivariate feature selection method for microarray data classificationGene selection for cancer identification: a decision tree model empowered by particle swarm optimization algorithmiPcc: a novel feature extraction method for accurate disease class discovery and prediction.Gene expression profiling for targeted cancer treatment.Random Subspace Aggregation for Cancer Prediction with Gene Expression ProfilesGene expression profiles for predicting metastasis in breast cancer: a cross-study comparison of classification methods.SSAW: A new sequence similarity analysis method based on the stationary discrete wavelet transform.RankProd Combined with Genetic Algorithm Optimized Artificial Neural Network Establishes a Diagnostic and Prognostic Prediction Model that Revealed C1QTNF3 as a Biomarker for Prostate Cancer.
P2860
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P2860
Combining multiple approaches for gene microarray classification.
description
2012 nî lūn-bûn
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2012年の論文
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2012年学术文章
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2012年学术文章
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2012年学术文章
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2012年学术文章
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name
Combining multiple approaches for gene microarray classification.
@en
Combining multiple approaches for gene microarray classification.
@nl
type
label
Combining multiple approaches for gene microarray classification.
@en
Combining multiple approaches for gene microarray classification.
@nl
prefLabel
Combining multiple approaches for gene microarray classification.
@en
Combining multiple approaches for gene microarray classification.
@nl
P356
P1433
P1476
Combining multiple approaches for gene microarray classification.
@en
P2093
Loris Nanni
Sheryl Brahnam
P304
P356
10.1093/BIOINFORMATICS/BTS108
P407
P577
2012-03-05T00:00:00Z