| scholarly article | Q13442814 |
| P8978 | DBLP publication ID | journals/jcb/KimWA11 |
| P356 | DOI | 10.1089/CMB.2010.0085 |
| P953 | full work available at URL | http://www.liebertpub.com/doi/full-xml/10.1089/cmb.2010.0085 |
| http://www.liebertpub.com/doi/pdf/10.1089/cmb.2010.0085 | ||
| https://doi.org/10.1089/cmb.2010.0085 | ||
| https://europepmc.org/articles/PMC3179615 | ||
| https://europepmc.org/articles/pmc3179615?pdf=render | ||
| https://europepmc.org/articles/PMC3179615?pdf=render | ||
| P932 | PMC publication ID | 3179615 |
| P698 | PubMed publication ID | 21457009 |
| P5875 | ResearchGate publication ID | 50986087 |
| P50 | author | Hoon Kim | Q59545155 |
| P2093 | author name string | Dimitris Anastassiou | |
| John Watkinson | |||
| P2860 | cites work | Cancer Research | Q326097 |
| Bioconductor: open software development for computational biology and bioinformatics | Q21194861 | ||
| Joint analysis of two microarray gene-expression data sets to select lung adenocarcinoma marker genes | Q24792469 | ||
| New feature subset selection procedures for classification of expression profiles | Q24793696 | ||
| Feature selection and classification for microarray data analysis: evolutionary methods for identifying predictive genes | Q24815392 | ||
| Gene selection and classification of microarray data using random forest. | Q25255911 | ||
| Gene expression profiling predicts clinical outcome of breast cancer | Q27860732 | ||
| Molecular classification of cancer: class discovery and class prediction by gene expression monitoring | Q27861072 | ||
| Exploration, normalization, and summaries of high density oligonucleotide array probe level data | Q27861098 | ||
| A multigene assay to predict recurrence of tamoxifen-treated, node-negative breast cancer | Q28297827 | ||
| Rank products: a simple, yet powerful, new method to detect differentially regulated genes in replicated microarray experiments | Q29616371 | ||
| A Bayesian framework for the analysis of microarray expression data: regularized t -test and statistical inferences of gene changes | Q29618085 | ||
| Broad patterns of gene expression revealed by clustering analysis of tumor and normal colon tissues probed by oligonucleotide arrays | Q29618684 | ||
| On differential variability of expression ratios: improving statistical inference about gene expression changes from microarray data | Q30651425 | ||
| Gene selection for sample classification based on gene expression data: study of sensitivity to choice of parameters of the GA/KNN method | Q30667225 | ||
| Nonparametric methods for identifying differentially expressed genes in microarray data | Q30746017 | ||
| Genetic algorithms applied to multi-class prediction for the analysis of gene expression data | Q30757687 | ||
| Gene selection from microarray data for cancer classification--a machine learning approach. | Q30981694 | ||
| Regularized ROC method for disease classification and biomarker selection with microarray data | Q31012130 | ||
| A two-sample Bayesian t-test for microarray data | Q31034018 | ||
| Predicting the prognosis of breast cancer by integrating clinical and microarray data with Bayesian networks. | Q31050064 | ||
| Identification of gene interactions associated with disease from gene expression data using synergy networks | Q31144746 | ||
| An efficient and robust statistical modeling approach to discover differentially expressed genes using genomic expression profiles | Q35033254 | ||
| S100A4 accelerates tumorigenesis and invasion of human prostate cancer through the transcriptional regulation of matrix metalloproteinase 9 | Q35075493 | ||
| Clinical biomarkers in drug discovery and development | Q35167912 | ||
| A review of feature selection techniques in bioinformatics | Q36919689 | ||
| Translation regulatory factor RBM3 is a proto-oncogene that prevents mitotic catastrophe | Q37180861 | ||
| Biomarker Identification by Feature Wrappers | Q40415443 | ||
| Computational analysis of the synergy among multiple interacting genes | Q42253998 | ||
| Expression profiling reveals hepsin overexpression in prostate cancer. | Q43691850 | ||
| Significance of gene ranking for classification of microarray samples. | Q45965712 | ||
| Tissue classification with gene expression profiles. | Q52926963 | ||
| Gene Selection for Cancer Classification using Support Vector Machines | Q56535529 | ||
| Shared MHC class II-dependent melanoma ribosomal protein L8 identified by phage display | Q56894337 | ||
| Gene expression correlates of clinical prostate cancer behavior | Q60156349 | ||
| Classification, subtype discovery, and prediction of outcome in pediatric acute lymphoblastic leukemia by gene expression profiling | Q61910882 | ||
| Feature Subset Selection by Bayesian network-based optimization | Q62637475 | ||
| Improved gene selection for classification of microarrays | Q73041240 | ||
| In biomarkers we trust? | Q81517118 | ||
| P433 | issue | 10 | |
| P407 | language of work or name | English | Q1860 |
| P921 | main subject | statistics | Q12483 |
| biomarker | Q864574 | ||
| statistical model | Q3284399 | ||
| tumor biomarker | Q66205818 | ||
| statistical data interpretation | Q67369489 | ||
| P304 | page(s) | 1329-1338 | |
| P577 | publication date | 2011-04-01 | |
| P1433 | published in | Journal of Computational Biology | Q6295003 |
| P1476 | title | Biomarker discovery using statistically significant gene sets | |
| Biomarker Discovery Using Statistically Significant Gene Sets | |||
| P478 | volume | 18 |
| Q38881960 | Detecting pairwise interactive effects of continuous random variables for bimarker identification with small sample size |
| Q52339616 | Feature selection with interactions in logistic regression models using multivariate synergies for a GWAS application |
| Q39298842 | Unraveling toxicological mechanisms and predicting toxicity classes with gene dysregulation networks |
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