Machine learning with the TCGA-HNSC dataset: improving usability by addressing inconsistency, sparsity, and high-dimensionality

[1]  Kyung-ah Sohn,et al.  Integrative pathway-based survival prediction utilizing the interaction between gene expression and DNA methylation in breast cancer , 2018, BMC Medical Genomics.

[2]  B. Habermann,et al.  Integrative analysis and machine learning on cancer genomics data using the Cancer Systems Biology Database (CancerSysDB) , 2018, BMC Bioinform..

[3]  K. Patel,et al.  TCGA Data on Head and Neck Squamous Cell Carcinoma Suggest Therapy-Specific Implications of Intratumor Heterogeneity , 2018 .

[4]  Jian Pan,et al.  Bioinformatic analysis of PFN2 dysregulation and its prognostic value in head and neck squamous carcinoma. , 2018, Future oncology.

[5]  Lei Wang,et al.  FSCN1 is upregulated by SNAI2 and promotes epithelial to mesenchymal transition in head and neck squamous cell carcinoma , 2017, Cell Biology International.

[6]  Jian Zhang,et al.  Transcriptional response profiles of paired tumor-normal samples offer novel perspectives in pan-cancer analysis , 2017, Oncotarget.

[7]  Graham J. Williams,et al.  wsrf: An R Package for Classification with Scalable Weighted Subspace Random Forests , 2017 .

[8]  Kumardeep Chaudhary,et al.  Deep Learning–Based Multi-Omics Integration Robustly Predicts Survival in Liver Cancer , 2017, Clinical Cancer Research.

[9]  Anushya Muruganujan,et al.  PANTHER version 11: expanded annotation data from Gene Ontology and Reactome pathways, and data analysis tool enhancements , 2016, Nucleic Acids Res..

[10]  The Gene Ontology Consortium Expansion of the Gene Ontology knowledgebase and resources , 2016, Nucleic Acids Res..

[11]  Zhongheng Zhang,et al.  Multiple imputation with multivariate imputation by chained equation (MICE) package. , 2016, Annals of translational medicine.

[12]  Andrew Feber,et al.  Human Papillomavirus Drives Tumor Development Throughout the Head and Neck: Improved Prognosis Is Associated With an Immune Response Largely Restricted to the Oropharynx. , 2016, Journal of clinical oncology : official journal of the American Society of Clinical Oncology.

[13]  Hsi-Yuan Huang,et al.  An Integrative Analysis for Cancer Studies , 2016, 2016 IEEE 16th International Conference on Bioinformatics and Bioengineering (BIBE).

[14]  Allison P. Heath,et al.  Toward a Shared Vision for Cancer Genomic Data. , 2016, The New England journal of medicine.

[15]  Brian O'Sullivan,et al.  Human Papillomavirus Genotype Association With Survival in Head and Neck Squamous Cell Carcinoma. , 2016, JAMA oncology.

[16]  Yi Deng,et al.  Multiple Imputation for General Missing Data Patterns in the Presence of High-dimensional Data , 2016, Scientific Reports.

[17]  Max Kuhn,et al.  caret: Classification and Regression Training , 2015 .

[18]  Ljubomir J. Buturovic,et al.  Cross-validation pitfalls when selecting and assessing regression and classification models , 2014, Journal of Cheminformatics.

[19]  Stef van Buuren,et al.  MICE: Multivariate Imputation by Chained Equations in R , 2011 .

[20]  Agostino Di Ciaccio,et al.  Computational Statistics and Data Analysis Measuring the Prediction Error. a Comparison of Cross-validation, Bootstrap and Covariance Penalty Methods , 2022 .

[21]  Richa Agarwala,et al.  PedHunter 2.0 and its usage to characterize the founder structure of the Old Order Amish of Lancaster County , 2010, BMC Medical Genetics.

[22]  Achim Zeileis,et al.  BMC Bioinformatics BioMed Central Methodology article Conditional variable importance for random forests , 2008 .

[23]  Pedro Larrañaga,et al.  A review of feature selection techniques in bioinformatics , 2007, Bioinform..

[24]  P. Royston,et al.  Patrick Royston model with a binary outcome A comparison of imputation techniques for handling missing predictor values in a risk , 2007 .

[25]  Achim Zeileis,et al.  Bias in random forest variable importance measures: Illustrations, sources and a solution , 2007, BMC Bioinformatics.

[26]  T. Hampton,et al.  The Cancer Genome Atlas , 2020, Indian Journal of Medical and Paediatric Oncology.

[27]  R. Tibshirani,et al.  Sparse Principal Component Analysis , 2006 .

[28]  M. Ashburner,et al.  Gene Ontology: tool for the unification of biology , 2000, Nature Genetics.