Shrinking classification trees for bootstrap aggregation. - Wei Pan 011 (Pattern Recognit. Lett., 1999)

A comparative review of statistical methods for discovering differentially expressed genes in replicated microarray experiments. - Wei Pan 011 (Bioinform., 2002)

Linear regression and two-class classification with gene expression data. - Xiaohong Huang; Wei Pan 011 (Bioinform., 2003)

On the Use of Permutation in and the Performance of A Class of Nonparametric Methods to Detect Differential Gene Expression. - Wei Pan 011 (Bioinform., 2003)

Modified Nonparametric Approaches to Detecting Differentially Expressed Genes in Replicated Microarray Experiments. - Yanli Zhao; Wei Pan 011 (Bioinform., 2003)

Modeling the relationship between LVAD support time and gene expression changes in the human heart by penalized partial least squares. - Xiaohong Huang; Wei Pan 011; Soon J. Park; Xinqiang Han; Leslie W. Miller; Jennifer Hall (Bioinform., 2004)

A note on using permutation-based false discovery rate estimates to compare different analysis methods for microarray data. - Yang Xie; Wei Pan 011; Arkady B. Khodursky (Bioinform., 2005)

A comparative study of discriminating human heart failure etiology using gene expression profiles. - Xiaohong Huang; Wei Pan 011; Suzanne Grindle; Xinqiang Han; Yingjie Chen; Soon J. Park; Leslie W. Miller; Jennifer Hall (BMC Bioinform., 2005)

Borrowing information from relevant microarray studies for sample classification using weighted partial least squares. - Xiaohong Huang; Wei Pan 011; Xinqiang Han; Yingjie Chen; Leslie W. Miller; Jennifer Hall (Comput. Biol. Chem., 2005)

Using Weighted Permutation Scores to Detect Differential Gene Expression with Microarray Data. - Xu Guo; Wei Pan 011 (J. Bioinform. Comput. Biol., 2005)

Gene Function Prediction by a Combined Analysis of Gene Expression Data and Protein-protein Interaction Data. - Guanghua Xiao; Wei Pan 011 (J. Bioinform. Comput. Biol., 2005)

Incorporating biological knowledge into distance-based clustering analysis of microarray gene expression data. - Desheng Huang; Wei Pan 011 (Bioinform., 2006)

Incorporating gene functions as priors in model-based clustering of microarray gene expression data. - Wei Pan 011 (Bioinform., 2006)

Semi-supervised learning via penalized mixture model with application to microarray sample classification. - Wei Pan 011; Xiaotong Shen; Aixiang Jiang; Robert P. Hebbel (Bioinform., 2006)

Cluster analysis using multivariate normal mixture models to detect differential gene expression with microarray data. - Yi He; Wei Pan 011; Jizhen Lin (Comput. Stat. Data Anal., 2006)

Incorporating prior knowledge of predictors into penalized classifiers with multiple penalty terms. - Feng Tai; Wei Pan 011 (Bioinform., 2007)

Incorporating prior knowledge of gene functional groups into regularized discriminant analysis of microarray data. - Feng Tai; Wei Pan 011 (Bioinform., 2007)

A Practical Question Based on Cross-Platform microarray Data Normalization: are Boec More Like Large Vessel or microvascular Endothelial Cells or Neither of Them? - Aixiang Jiang; Wei Pan 011; Liming C. Milbauer; Yu Shyr; Robert P. Hebbel (J. Bioinform. Comput. Biol., 2007)

A Parametric Joint Model of DNA-Protein Binding, Gene Expression and DNA Sequence Data to Detect Target Genes of a Transcription Factor. - Wei Pan 011; Peng Wei 005; Arkady B. Khodursky (Pacific Symposium on Biocomputing, 2008)

Incorporating gene networks into statistical tests for genomic data via a spatially correlated mixture model. - Peng Wei 005; Wei Pan 011 (Bioinform., 2008)

Incorporating Gene Functions into Regression Analysis of DNA-Protein Binding Data and Gene Expression Data to Construct Transcriptional Networks. - Peng Wei 005; Wei Pan 011 (IEEE ACM Trans. Comput. Biol. Bioinform., 2008)

Network-based multiple locus linkage analysis of expression traits. - Wei Pan 011 (Bioinform., 2009)

Network-based support vector machine for classification of microarray samples. - Yanni Zhu; Xiaotong Shen; Wei Pan 011 (BMC Bioinform., 2009)

Penalized mixtures of factor analyzers with application to clustering high-dimensional microarray data. - Benhuai Xie; Wei Pan 011; Xiaotong Shen (Bioinform., 2010)

Maximum Likelihood Estimation Over Directed Acyclic Gaussian Graphs. - Yiping Yuan; Xiaotong Shen; Wei Pan 011 (Stat. Anal. Data Min., 2012)

Penalized regression and risk prediction in genome-wide association studies. - Erin Austin; Wei Pan 011; Xiaotong Shen (Stat. Anal. Data Min., 2013)

Testing Group Differences in Brain Functional Connectivity: Using Correlations or Partial Correlations? - Junghi Kim; Jeffrey R. Wozniak; Bryon A. Mueller; Wei Pan 011 (Brain Connect., 2015)

A cautionary note on using secondary phenotypes in neuroimaging genetic studies. - Junghi Kim; Wei Pan 011 (NeuroImage, 2015)

Nonlinear joint latent variable models and integrative tumor subtype discovery. - Binghui Liu; Xiaotong Shen; Wei Pan 011 (Stat. Anal. Data Min., 2016)

Gene- and pathway-based association tests for multiple traits with GWAS summary statistics. - Il-Youp Kwak; Wei Pan 011 (Bioinform., 2017)

Imaging-wide association study: Integrating imaging endophenotypes in GWAS. - Zhiyuan Xu; Chong Wu; Wei Pan 011 (NeuroImage, 2017)

Integration of methylation QTL and enhancer-target gene maps with schizophrenia GWAS summary results identifies novel genes. - Chong Wu; Wei Pan 011 (Bioinform., 2019)

A simple convolutional neural network for prediction of enhancer-promoter interactions with DNA sequence data. - Zhong Zhuang; Xiaotong Shen; Wei Pan 011 (Bioinform., 2019)

Implicating causal brain imaging endophenotypes in Alzheimer's disease using multivariable IWAS and GWAS summary data. - Katherine A. Knutson; Yangqing Deng; Wei Pan 011 (NeuroImage, 2020)

A powerful and versatile colocalization test. - Yangqing Deng; Wei Pan 011 (PLoS Comput. Biol., 2020)

Penalized regression and model selection methods for polygenic scores on summary statistics. - Jack Pattee; Wei Pan 011 (PLoS Comput. Biol., 2020)

Integrative analysis of multi-omics data for discovering low-frequency variants associated with low-density lipoprotein cholesterol levels. - Tianzhong Yang; Peng Wei 005; Wei Pan 011 (Bioinform., 2021)

Model checking via testing for direct effects in Mendelian Randomization and transcriptome-wide association studies. - Yangqing Deng; Wei Pan 011 (PLoS Comput. Biol., 2021)

Significance Tests of Feature Relevance for a Black-Box Learner. - Ben Dai; Xiaotong Shen; Wei Pan 011 (IEEE Trans. Neural Networks Learn. Syst., 2024)

Extracting Genetically-Imputed Causal Features From ECG Data. - Yuchen Yao; Zhaotong Lin; Xiaotong Shen; Lin Yee Chen; Wei Pan 011 (Stat. Anal. Data Min., 2025)