The PACRAT system: an extensible WWW-based system for correlated sequence retrieval, storage and analysis. - William C. Ray; Charles J. Daniels (Bioinform., 2001)

Tricross : using dot-plots in sequence-id space to detect uncataloged intergenic features. - William C. Ray; Robert S. Munson Jr.; Charles J. Daniels (Bioinform., 2001)

PACRAT: a database and analysis system for archaeal and bacterial intergenic sequence features. - William C. Ray; Charles J. Daniels (Nucleic Acids Res., 2003)

A Time Series Analysis of Microarray Data. - Selnur Erdal; Ozgur Ozturk; David L. Armbruster; Hakan Ferhatosmanoglu; William C. Ray (BIBE, 2004)

MAVL and StickWRLD: visually exploring relationships in nucleic acid sequence alignments. - William C. Ray (Nucleic Acids Res., 2004)

Modeling the fluffy lens: construction of the virtual chinchilla. - William C. Ray; Joseph A. Jurcisek (SIGGRAPH Posters, 2005)

Discovering biostructure constraints using VRML visualization. - William C. Ray; Hatice Gulcin Ozer (SIGGRAPH Posters, 2005)

MAVL/StickWRLD for protein: visualizing protein sequence families to detect non-consensus features. - William C. Ray (Nucleic Acids Res., 2005)

Using flow-visualization for studying sub-molecular motions. - William C. Ray; Abhilash Mohan; Jeffrey Bartlett (SIGGRAPH Research Posters, 2006)

MAVL/StickWRLD: analyzing structural constraints using interpositional dependencies in biomolecular sequence alignments. - Hatice Gulcin Ozer; William C. Ray (Nucleic Acids Res., 2006)

Informative Motifs in Protein Family Alignments. - Hatice Gulcin Ozer; William C. Ray (WABI, 2007)

Visualizing molecular uncertainty: a path to the path. - Shareef Dabdoub; Abhilash Mohan; William C. Ray (SIGGRAPH Posters, 2008)

A Visual Analytics approach to identifying protein structural constraints. - William C. Ray (IEEE VAST, 2010)

FIND: A new software tool and development platform for enhanced multicolor flow analysis. - Shareef Dabdoub; William C. Ray; Sheryl S. Justice (BMC Bioinform., 2011)

An eQTL biological data visualization challenge and approaches from the visualization community. - Christopher W. Bartlett; Soo Yeon Cheong; Liping Hou; Jesse Paquette; Pek Yee Lum; Günter Jäger; Florian Battke; Corinna Vehlow; Julian Heinrich; Kay Nieselt; Ryo Sakai; Jan Aerts; et al. (BMC Bioinform., 2012)

Addressing the unmet need for visualizing conditional random fields in biological data. - William C. Ray; Samuel L. Wolock; Nicholas W. Callahan; Min Dong; Qingshun Quinn Li; Chun Liang; Thomas J. Magliery; Christopher W. Bartlett (BMC Bioinform., 2014)

Invasive Measurements Can Provide an Objective Ceiling for Non-invasive Machine Learning Predictions. - Christopher W. Bartlett; Jamie Bossenbroek; Yukie Ueyama; Patricia E. Mccallinhart; Aaron J. Trask; William C. Ray (SIGMAP, 2021)

The Importance of Weakly Co-Evolving Residue Networks in Proteins is Revealed by Visual Analytics. - Sidharth Mohan; Hatice Gulcin Ozer; William C. Ray (Frontiers Bioinform., 2022)

Invasive or More Direct Measurements Can Provide an Objective Early-Stopping Ceiling for Training Deep Neural Networks on Non-invasive or Less-Direct Biomedical Data. - Christopher W. Bartlett; Jamie Bossenbroek; Yukie Ueyama; Patricia E. Mccallinhart; Olivia A. Peters; Donna A. Santillan; Mark K. Santillan; Aaron J. Trask; William C. Ray (SN Comput. Sci., 2023)