Analysis of High-throughput DNA Methylation Bead Arrays Utilizing Bayesian Genotyping Algorithms. - Yuanyuan Xiao; Mark R. Segal; Eugene Andres Houseman; Joseph Wiemels; John K. Wiencke; Shichun Zheng; Margaret R. Wrensch; Brock C. Christensen; Carmen J. Marsit; Karl T. Kelsey; Heather H. Nelson; Margaret R. Karagas; et al. (BMEI (1), 2008)

Model-based clustering of DNA methylation array data: a recursive-partitioning algorithm for high-dimensional data arising as a mixture of beta distributions. - Eugene Andres Houseman; Brock C. Christensen; Ru-Fang Yeh; Carmen J. Marsit; Margaret R. Karagas; Margaret R. Wrensch; Heather H. Nelson; Joseph Wiemels; Shichun Zheng; John K. Wiencke; Karl T. Kelsey (BMC Bioinform., 2008)

Copy number variation has little impact on bead-array-based measures of DNA methylation. - Eugene Andres Houseman; Brock C. Christensen; Margaret R. Karagas; Margaret R. Wrensch; Heather H. Nelson; Joseph Wiemels; Shichun Zheng; John K. Wiencke; Karl T. Kelsey; Carmen J. Marsit (Bioinform., 2009)

Semi-supervised recursively partitioned mixture models for identifying cancer subtypes. - Devin C. Koestler; Carmen J. Marsit; Brock C. Christensen; Margaret R. Karagas; Raphael Bueno; David J. Sugarbaker; Karl T. Kelsey; Eugene Andres Houseman (Bioinform., 2010)

DNA methylation arrays as surrogate measures of cell mixture distribution. - Eugene Andres Houseman; William P. Accomando; Devin C. Koestler; Brock C. Christensen; Carmen J. Marsit; Heather H. Nelson; John K. Wiencke; Karl T. Kelsey (BMC Bioinform., 2012)

OxyBS: estimation of 5-methylcytosine and 5-hydroxymethylcytosine from tandem-treated oxidative bisulfite and bisulfite DNA. - Eugene Andres Houseman; Kevin C. Johnson; Brock C. Christensen (Bioinform., 2016)

methyLiftover: cross-platform DNA methylation data integration. - Alexander J. Titus; Eugene Andres Houseman; Kevin C. Johnson; Brock C. Christensen (Bioinform., 2016)

Improving cell mixture deconvolution by identifying optimal DNA methylation libraries (IDOL). - Devin C. Koestler; Meaghan J. Jones; Joseph Usset; Brock C. Christensen; Rondi A. Butler; Michael S. Kobor; John K. Wiencke; Karl T. Kelsey (BMC Bioinform., 2016)

A New Dimension of Breast Cancer Epigenetics - Applications of Variational Autoencoders with DNA Methylation. - Alexander J. Titus; Carly A. Bobak; Brock C. Christensen (BIOINFORMATICS, 2018)

PyMethylProcess - convenient high-throughput preprocessing workflow for DNA methylation data. - Joshua J. Levy; Alexander J. Titus; Lucas A. Salas; Brock C. Christensen (Bioinform., 2019)

Preliminary Evaluation of the Utility of Deep Generative Histopathology Image Translation at a Mid-sized NCI Cancer Center. - Joshua J. Levy; Christopher R. Jackson; Aravindhan Sriharan; Brock C. Christensen; Louis J. Vaickus (BIOINFORMATICS, 2020)

PathFlowAI: A High-Throughput Workflow for Preprocessing, Deep Learning and Interpretation inDigital Pathology. - Joshua J. Levy; Lucas A. Salas; Brock C. Christensen; Aravindhan Sriharan; Louis J. Vaickus (PSB, 2020)

MethylNet: an automated and modular deep learning approach for DNA methylation analysis. - Joshua J. Levy; Alexander J. Titus; Curtis L. Petersen; Youdinghuan Chen; Lucas A. Salas; Brock C. Christensen (BMC Bioinform., 2020)

Longevity Associated Geometry Identified in Satellite Images: Sidewalks, Driveways and Hiking Trails. - Joshua J. Levy; Rebecca M. Lebeaux; Anne G. Hoen; Brock C. Christensen; Louis J. Vaickus; Todd A. MacKenzie (CoRR, 2020)

Topological Feature Extraction and Visualization of Whole Slide Images using Graph Neural Networks. - Joshua J. Levy; Christian Haudenschild; Clark Barwick; Brock C. Christensen; Louis J. Vaickus (PSB, 2021)

Graph Neural Networks Ameliorate Potential Impacts of Imprecise Large-Scale Autonomous Immunofluorescence Labeling of Immune Cells on Whole Slide Images. - Ramya Reddy; Ram Reddy; Cyril Sharma; Christopher R. Jackson; Scott Palisoul; Rachael Barney; Fred Kolling; Lucas A. Salas; Brock C. Christensen; Gabriel Brooks; Gregory J. Tsongalis; Louis J. Vaickus; et al. (GeoMedIA, 2022)

Development of biologically interpretable multimodal deep learning model for cancer prognosis prediction. - Zarif L. Azher; Louis J. Vaickus; Lucas A. Salas; Brock C. Christensen; Joshua J. Levy (SAC, 2022)

Assessment of emerging pretraining strategies in interpretable multimodal deep learning for cancer prognostication. - Zarif L. Azher; Anish Suvarna; Ji-Qing Chen; Ze Zhang; Brock C. Christensen; Lucas A. Salas; Louis J. Vaickus; Joshua J. Levy (BioData Min., 2023)

An initial game-theoretic assessment of enhanced tissue preparation and imaging protocols for improved deep learning inference of spatial transcriptomics from tissue morphology. - Michael Y. Fatemi; Yunrui Lu; Alos B. Diallo; Gokul Srinivasan; Zarif L. Azher; Brock C. Christensen; Lucas A. Salas; Gregory J. Tsongalis; Scott Palisoul; Laurent Perreard; Frederick W. Kolling IV; Louis J. Vaickus; et al. (Briefings Bioinform., 2024)

Feasibility of Inferring Spatial Transcriptomics from Single-Cell Histological Patterns for Studying Colon Cancer Tumor Heterogeneity. - Michael Y. Fatemi; Yunrui Lu; Zarif L. Azher; Cyril Sharma; Eric Feng; Alos B. Diallo; Gokul Srinivasan; Grace M. Rosner; Kelli B. Pointer; Brock C. Christensen; Lucas A. Salas; Gregory J. Tsongalis; et al. (BIOSTEC (1), 2025)