Integrated Analysis of Pharmacokinetic, Clinical, and SNP Microarray Data Using Projection onto the Most Interesting Statistical Evidence with Adaptive Permutation Testing. - Stan Pounds; Xueyuan Cao; Cheng Cheng; Jun J. Yang; Dario Campana; William E. Evans; Ching-Hon Pui; Mary Relling (BIBM, 2009)

PROMISE: a tool to identify genomic features with a specific biologically interesting pattern of associations with multiple endpoint variables. - Stan Pounds; Cheng Cheng; Xueyuan Cao; Kristine R. Crews; William Plunkett; Varsha Gandhi; Jeffrey Rubnitz; Raul C. Ribeiro; James R. Downing; Jatinder Lamba (Bioinform., 2009)

Integrated analysis of pharmacologic, clinical and SNP microarray data using Projection Onto the Most Interesting Statistical Evidence with Adaptive Permutation Testing. - Stan Pounds; Xueyuan Cao; Cheng Cheng; Jun J. Yang; Dario Campana; Ching-Hon Pui; William E. Evans; Mary Relling (Int. J. Data Min. Bioinform., 2011)

CC-PROMISE effectively integrates two forms of molecular data with multiple biologically related endpoints. - Xueyuan Cao; Kristine R. Crews; James R. Downing; Jatinder Lamba; Stanley Pounds (BMC Bioinform., 2016)

Proceedings of the 15th Annual UT-KBRIN Bioinformatics Summit 2016: Cadiz, KY, USA. 8-10 April 2016. - Eric C. Rouchka; Julia H. Chariker; Benjamin J. Harrison; Juw Won Park; Xueyuan Cao; Stanley Pounds; Susana C. Raimondi; James R. Downing; Raul C. Ribeiro; Jeffrey Rubnitz; Jatinder Lamba; Bernie J. Daigle Jr.; et al. (BMC Bioinform., 2016)

POST: A framework for set-based association analysis in high-dimensional data. - Xueyuan Cao; E. Olusegun George; Mingjuan Wang; Dale B. Armstrong; Cheng Cheng; Susana C. Raimondi; Jeffrey E. Rubnitz; James R. Downing; Mondira Kundu; Stanley Pounds (BIBM, 2017)

Pan-cancer genome and transcriptome analyses of 1, 699 paediatric leukaemias and solid tumours. - Xiaotu Ma; Yu Liu; Yanling Liu; Ludmil B. Alexandrov; Michael N. Edmonson; Charles Gawad; Xin Zhou; Yongjin Li; Michael Rusch; John Easton; Robert Huether; Veronica Gonzalez-Pena; et al. (Nat., 2018)

Gene-set distance analysis (GSDA): a powerful tool for gene-set association analysis. - Xueyuan Cao; Stan Pounds (BMC Bioinform., 2021)