Mining MEDLINE: Abstracts, Sentences, or Phrases? - Jing Ding; Daniel Berleant; Dan Nettleton; Eve Syrkin Wurtele (Pacific Symposium on Biocomputing, 2002)

Expression pattern of yeast sporulation: a case study for regulatory changes after yeast genome duplication. - Wei Huang 032; Dan Nettleton; Xun Gu 002 (Inf. Sci., 2002)

Principal Components Regression With Data Chosen Components and Related Methods. - J. T. Gene Hwang; Dan Nettleton (Technometrics, 2003)

BarleyBase - an expression profiling database for plant genomics. - Lishuang Shen; Jian Gong; Rico A. Caldo; Dan Nettleton; Dianne Cook; Roger P. Wise; Julie A. Dickerson (Nucleic Acids Res., 2005)

Scanning microarrays at multiple intensities enhances discovery of differentially expressed genes. - David S. Skibbe; Xiujuan Wang; Xuefeng Zhao; Lisa A. Borsuk; Dan Nettleton; Patrick S. Schnable (Bioinform., 2006)

Identifying differentially expressed genes in unreplicated multiple-treatment microarray timecourse experiments. - Rhonda DeCook; Dan Nettleton; Carol Foster; Eve Syrkin Wurtele (Comput. Stat. Data Anal., 2006)

Pooling mRNA in microarray experiments and its effect on power. - Wuyan Zhang; Alicia L. Carriquiry; Dan Nettleton; Jack C. M. Dekkers (Bioinform., 2007)

Identification of differentially expressed gene categories in microarray studies using nonparametric multivariate analysis. - Dan Nettleton; Justin Recknor; James M. Reecy (Bioinform., 2008)

An Efficient and Scalable Implementation of SNP-Pair Interaction Testing for Genetic Association Studies. - Lars Koesterke; Daniel Stanzione; Matthew W. Vaughn; Stephen M. Welch; Waclaw Kusnierczyk; Jinliang Yang; Cheng-Ting Yeh; Dan Nettleton; Patrick S. Schnable (IPDPS Workshops, 2011)

An improved method for computing q-values when the distribution of effect sizes is asymmetric. - Megan Orr; Peng Liu 012; Dan Nettleton (Bioinform., 2014)

Copy number variation detection using next generation sequencing read counts. - Heng Wang; Dan Nettleton; Kai Ying (BMC Bioinform., 2014)

SimSeq: a nonparametric approach to simulation of RNA-sequence datasets. - Sam Benidt; Dan Nettleton (Bioinform., 2015)

A hidden Markov tree model for testing multiple hypotheses corresponding to Gene Ontology gene sets. - Kun Liang 004; Chuanlong Du; Hankun You; Dan Nettleton (BMC Bioinform., 2018)

Crowdsourcing image analysis for plant phenomics to generate ground truth data for machine learning. - Naihui Zhou; Zachary D. Siegel; Scott Zarecor; Nigel Lee; Darwin A. Campbell; Carson M. Andorf; Dan Nettleton; Carolyn J. Lawrence-Dill; Baskar Ganapathysubramanian; Jonathan W. Kelly; Iddo Friedberg (PLoS Comput. Biol., 2018)

Regression-Enhanced Random Forests. - Haozhe Zhang; Dan Nettleton; Zhengyuan Zhu (CoRR, 2019)

Sparse model identification and learning for ultra-high-dimensional additive partially linear models. - Xinyi Li; Li Wang 035; Dan Nettleton (J. Multivar. Anal., 2019)

rmRNAseq: differential expression analysis for repeated-measures RNA-seq data. - Yet Nguyen; Dan Nettleton (Bioinform., 2020)

Conformal Prediction Intervals for Neural Networks Using Cross Validation. - Saeed Khaki; Dan Nettleton (CoRR, 2020)

Tree aggregation for random forest class probability estimation. - Andrew J. Sage; Ulrike Genschel; Dan Nettleton (Stat. Anal. Data Min., 2020)

Variable importance assessments and backward variable selection for multi-sample problems. - Liuhua Peng; Long Qu; Dan Nettleton (J. Multivar. Anal., 2021)

Stability of Random Forests and Coverage of Random-Forest Prediction Intervals. - Yan Wang; Huaiqing Wu; Dan Nettleton (NeurIPS, 2023)

Adjusting for gene-specific covariates to improve RNA-seq analysis. - Hyeongseon Jeon; Kyu-Sang Lim; Yet Nguyen; Dan Nettleton (Bioinform., 2023)