Computer applications of the visible human dataset. - John P. Clyne; Don Middleton (SIGGRAPH Visual Proceedings, 1996)

Interactive Direct Volume Rendering of Time-Varying Data. - John P. Clyne; John M. Dennis (VisSym, 1999)

Texture Hardware Assisted Rendering of Time-Varying Volume Data. - Eric B. Lum; Kwan-Liu Ma; John P. Clyne (IEEE Visualization, 2001)

A Hardware-Assisted Scalable Solution for Interactive Volume Rendering of Time-Varying Data. - Eric B. Lum; Kwan-Liu Ma; John P. Clyne (IEEE Trans. Vis. Comput. Graph., 2002)

A prototype discovery environment for analyzing and visualizing terascale turbulent fluid flow simulations. - John P. Clyne; Mark Rast (Visualization and Data Analysis, 2005)

End-to-End Data Reduction and Hardware Accelerated Rendering Techniques for Visualizing Time-Varying Non-uniform Grid Volume Data. - Hiroshi Akiba; Kwan-Liu Ma; John P. Clyne (VG, 2005)

Ultra-scale visualization - Workshop on ultra-scale visualization. - James P. Ahrens; Hank Childs; John P. Clyne; Wes Bethel; Jian Huang 007; Scott Klasky; Kwan-Liu Ma; Kenneth Moreland; Michael E. Papka; Valerio Pascucci; Han-Wei Shen; Deborah Silver (SC, 2006)

Compressible thermal starting plume. - Mark Rast; Joseph Mendoza; John P. Clyne (J. Vis., 2007)

Visualization-Driven Structural and Statistical Analysis of Turbulent Flows. - Kenny Gruchalla; Mark Rast; Elizabeth Bradley; John P. Clyne; Pablo D. Mininni (IDA, 2009)

Stellar magnetism. - Carson Brownlee; Benjamin Brown; John P. Clyne; Chems Touati; Kelly P. Gaither; Charles D. Hansen (SC Companion, 2011)

Progressive Data Access for Regular Grids. - John P. Clyne (High Performance Visualization, 2012)

The VAPOR Visualization Application. - Alan Norton; John P. Clyne (High Performance Visualization, 2012)

Physically-Based Feature Tracking for CFD Data. - John P. Clyne; Pablo D. Mininni; Alan Norton (IEEE Trans. Vis. Comput. Graph., 2013)

Evaluating the efficacy of wavelet configurations on turbulent-flow data. - Shaomeng Li; Kenny Gruchalla; Kristin Potter; John P. Clyne; Hank Childs (LDAV, 2015)

Multiresolution visualization of digital earth data via hexagonal box-spline wavelets. - Mohammad Imrul Jubair; Usman R. Alim; Niklas Röber; John P. Clyne; Ali Mahdavi-Amiri; Faramarz Samavati (SciVis, 2015)

Icosahedral Maps for a Multiresolution Representation of Earth Data. - Mohammad Imrul Jubair; Usman R. Alim; Niklas Röber; John P. Clyne; Ali Mahdavi-Amiri (VMV, 2016)

Spatiotemporal Wavelet Compression for Visualization of Scientific Simulation Data. - Shaomeng Li; Sudhanshu Sane; Leigh Orf; Pablo D. Mininni; John P. Clyne; Hank Childs (CLUSTER, 2017)

Achieving Portable Performance For Wavelet Compression Using Data Parallel Primitives. - Shaomeng Li; Nicole Marsaglia; Vincent Chen; Christopher M. Sewell; John P. Clyne; Hank Childs (EGPGV@EuroVis, 2017)

Performance Impacts of In Situ Wavelet Compression on Scientific Simulations. - Shaomeng Li; Matthew Larsen; John P. Clyne; Hank Childs (ISAV@SC, 2017)

Toward a Multi-method Approach: Lossy Data Compression for Climate Simulation Data. - Allison H. Baker; Haiying Xu; Dorit M. Hammerling; Shaomeng Li; John P. Clyne (ISC Workshops, 2017)

Data Reduction Techniques for Simulation, Visualization and Data Analysis. - Shaomeng Li; Nicole Marsaglia; Christoph Garth; Jonathan Woodring; John P. Clyne; Hank Childs (Comput. Graph. Forum, 2018)

Using Neural Networks for Two Dimensional Scientific Data Compression. - Lucas Hayne; John P. Clyne; Shaomeng Li (IEEE BigData, 2021)

The Geoscience Community Analysis Toolkit: An Open Development, Community Driven Toolkit in the Scientific Python Ecosystem. - Orhan Eroglu; Anissa Zacharias; Michaela Sizemore; Alea Kootz; Heather Craker; John P. Clyne (SciPy, 2022)

Development of NCL equivalent serial and parallel python routines for meteorological data analysis. - Jatin Gharat; Bipin Kumar; Leena Ragha; Amit Barve; Shaik Mohammad Jeelani; John P. Clyne (Int. J. High Perform. Comput. Appl., 2022)

Lossy Scientific Data Compression With SPERR. - Shaomeng Li; Peter Lindstrom 001; John P. Clyne (IPDPS, 2023)