Random Subspace Aggregation for Cancer Prediction with Gene Expression Profiles

scientific article published on 24 November 2016

Random Subspace Aggregation for Cancer Prediction with Gene Expression Profiles is …
instance of (P31):
scholarly articleQ13442814

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P356DOI10.1155/2016/4596326
P932PMC publication ID5143691
P698PubMed publication ID27999797

P50authorJianhua WeiQ96142894
Liying YangQ88144990
Zhimin LiuQ96142893
P2093author name stringJunying Zhang
Xiguo Yuan
P2860cites workMulti-class BCGA-ELM based classifier that identifies biomarkers associated with hallmarks of cancerQ35634621
iPcc: a novel feature extraction method for accurate disease class discovery and predictionQ37080324
A high-resolution spatiotemporal atlas of gene expression of the developing mouse brainQ38475717
Random subspace ensembles for FMRI classification.Q45917647
Combining multiple approaches for gene microarray classificationQ48004443
Methods of forward feature selection based on the aggregation of classifiers generated by single attributeQ51571429
Support-vector networksQ55922708
The random subspace method for constructing decision forestsQ56502470
Gene Selection for Cancer Classification using Support Vector MachinesQ56535529
An ensemble of filters and classifiers for microarray data classificationQ58036728
Gene expression correlates of clinical prostate cancer behaviorQ60156349
Identifying Important Risk Factors for Survival in Kidney Graft Failure Patients Using Random Survival ForestsQ22673963
A combinational feature selection and ensemble neural network method for classification of gene expression dataQ24799711
Distinct types of diffuse large B-cell lymphoma identified by gene expression profilingQ27860529
Gene expression profiling predicts clinical outcome of breast cancerQ27860732
Molecular classification of cancer: class discovery and class prediction by gene expression monitoringQ27861072
Prediction of central nervous system embryonal tumour outcome based on gene expressionQ29618619
Broad patterns of gene expression revealed by clustering analysis of tumor and normal colon tissues probed by oligonucleotide arraysQ29618684
Translation of microarray data into clinically relevant cancer diagnostic tests using gene expression ratios in lung cancer and mesotheliomaQ30718501
Use of proteomic patterns in serum to identify ovarian cancerQ30819686
Ensemble machine learning on gene expression data for cancer classification.Q30929145
Minimum redundancy feature selection from microarray gene expression dataQ30988046
A genetic filter for cancer classification on gene expression dataQ30997263
Classification of gene expression data: A hubness-aware semi-supervised approachQ31061445
Using uncorrelated discriminant analysis for tissue classification with gene expression dataQ31068182
Cancer classification from gene expression data by NPPC ensembleQ33579902
A Sparse Learning Machine for High-Dimensional Data with Application to Microarray Gene AnalysisQ33732538
Automated identification of cell-type-specific genes in the mouse brain by image computing of expression patternsQ33835800
A study of performance on microarray data sets for a classifier based on information theoretic learningQ33942721
Weighted random subspace method for high dimensional data classificationQ34019831
Gene network modular-based classification of microarray samplesQ34324671
Improving accuracy for cancer classification with a new algorithm for genes selectionQ34475554
DNA microarray and cancerQ35029862
FIREWACh: high-throughput functional detection of transcriptional regulatory modules in mammalian cellsQ35128053
Deep convolutional neural networks for annotating gene expression patterns in the mouse brainQ35623697
P275copyright licenseCreative Commons Attribution 4.0 InternationalQ20007257
P6216copyright statuscopyrightedQ50423863
P407language of work or nameEnglishQ1860
P304page(s)4596326
P577publication date2016-11-24
P1433published inBioMed Research InternationalQ17509958
P1476titleRandom Subspace Aggregation for Cancer Prediction with Gene Expression Profiles
P478volume2016

Reverse relations

Q62495329RNA-seq assistant: machine learning based methods to identify more transcriptional regulated genescites workP2860

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