A New Approach to Gene Prediction Using the Self-Organizing Map. - Shaun Mahony; Terry J. Smith; James O. McInerney; Aaron Golden (CSB, 2003)

Gene prediction using the Self-Organizing Map: automatic generation of multiple gene models. - Shaun Mahony; James O. McInerney; Terry J. Smith; Aaron Golden (BMC Bioinform., 2004)

Improved detection of DNA motifs using a self-organized clustering of familial binding profiles. - Shaun Mahony; Aaron Golden; Terry J. Smith; Panayiotis V. Benos (ISMB (Supplement of Bioinformatics), 2005)

Self-Organizing Maps of Position Weight Matrices for Motif Discovery in Biological Sequences. - Shaun Mahony; David Hendrix; Terry J. Smith; Aaron Golden (Artif. Intell. Rev., 2005)

Transcription factor binding site identification using the self-organizing map. - Shaun Mahony; David Hendrix; Aaron Golden; Terry J. Smith; Daniel S. Rokhsar (Bioinform., 2005)

Gene Prediction in Metagenomic Libraries Using the Self Organising Map and High Performance Computing Techniques. - Nigel McCoy; Shaun Mahony; Aaron Golden (GCCB, 2006)

Self-organizing neural networks to support the discovery of DNA-binding motifs. - Shaun Mahony; Panayiotis V. Benos; Terry J. Smith; Aaron Golden (Neural Networks, 2006)

Inferring protein-DNA dependencies using motif alignments and mutual information. - Shaun Mahony; Philip E. Auron; Panayiotis V. Benos (ISMB/ECCB (Supplement of Bioinformatics), 2007)

STAMP: a web tool for exploring DNA-binding motif similarities. - Shaun Mahony; Panayiotis V. Benos (Nucleic Acids Res., 2007)

DNA Familial Binding Profiles Made Easy: Comparison of Various Motif Alignment and Clustering Strategies. - Shaun Mahony; Philip E. Auron; Panayiotis V. Benos (PLoS Comput. Biol., 2007)

ORegAnno: an open-access community-driven resource for regulatory annotation. - Obi L. Griffith; Stephen B. Montgomery; Bridget Bernier; Bryan Chu; Katayoon Kasaian; Stein Aerts; Shaun Mahony; Monica C. Sleumer; Mikhail Bilenky; Maximilian Haeussler; Malachi Griffith; Steven M. Gallo; et al. (Nucleic Acids Res., 2008)

Discovering homotypic binding events at high spatial resolution. - Yuchun Guo; Georgios Papachristoudis; Robert C. Altshuler; Georg K. Gerber; Tommi S. Jaakkola; David K. Gifford; Shaun Mahony (Bioinform., 2010)

High Resolution Genome Wide Binding Event Finding and Motif Discovery Reveals Transcription Factor Spatial Binding Constraints. - Yuchun Guo; Shaun Mahony; David K. Gifford (PLoS Comput. Biol., 2012)

An Integrated Model of Multiple-Condition ChIP-Seq Data Reveals Predeterminants of Cdx2 Binding. - Shaun Mahony; Matthew D. Edwards; Esteban O. Mazzoni; Richard Sherwood; Akshay Kakumanu; Carolyn A. Morrison; Hynek Wichterle; David K. Gifford (RECOMB, 2014)

Phenome-Wide Interaction Study (PheWIS) in Aids Clinical Trials Group Data (ACTG). - Shefali S. Verma; Alex T. Frase; Anurag Verma; Sarah A. Pendergrass; Shaun Mahony; David W. Haas; Marylyn D. Ritchie (PSB, 2016)

miniMDS: 3D structural inference from high-resolution Hi-C data. - Lila Rieber; Shaun Mahony (Bioinform., 2017)

Deconvolving sequence features that discriminate between overlapping regulatory annotations. - Akshay Kakumanu; Silvia Velasco; Esteban O. Mazzoni; Shaun Mahony (PLoS Comput. Biol., 2017)

Characterizing Protein-DNA Binding Event Subtypes in ChIP-Exo Data. - Naomi Yamada; William K. M. Lai; Nina Farrell; B. Franklin Pugh; Shaun Mahony (RECOMB, 2018)

Direct prediction of regulatory elements from partial data without imputation. - Yu Zhang; Shaun Mahony (PLoS Comput. Biol., 2019)

PEGR: a management platform for ChIP-based next generation sequencing pipelines. - Danying Shao; Gretta Kellogg; Shaun Mahony; William K. M. Lai; B. Franklin Pugh (PEARC, 2020)

ChExMix: A Method for Identifying and Classifying Protein-DNA Interaction Subtypes. - Naomi Yamada; Prashant Kumar Kuntala; B. Franklin Pugh; Shaun Mahony (J. Comput. Biol., 2020)

S3V2-IDEAS: a package for normalizing, denoising and integrating epigenomic datasets across different cell types. - Guanjue Xiang; Belinda Giardine; Shaun Mahony; Yu Zhang 002; Ross C. Hardison (Bioinform., 2021)

SEM: Size-Based Expectation Maximization for Characterizing Nucleosome Positions and Subtypes. - Jianyu Yang; Kuangyu Yen; Shaun Mahony (RECOMB, 2024)