Jeffrey A. Thompson

Relevant Word Order Vectorization for Improved Natural Language Processing in Electronic Health Records

Dinesh Pal Mudaranthakam, Devin C. Koestler, Matthew S. Mayo, 2019, Scientific Reports.

A workflow for the computational identification of candidate regulatory elements in noncoding DNA

Jeffrey A. Thompson, Clare Bates Congdon, Craig R. Lessard, 2014, BCB.

Training Distribution Matching (TDM) Evaluation and Results

Casey S. Greene, Jeffrey A. Thompson, C. Greene, 2015 .

pwrEWAS: a user-friendly tool for comprehensive power estimation for epigenome wide association studies (EWAS)

Devin C. Koestler, Jeffrey A. Thompson, Stefan Graw, 2019, BMC Bioinformatics.

Initial Results In Using de Novo Motif Inference to Detect Cis-Regulatory Modules

Jeffrey A. Thompson, Clare Bates Congdon, 2013, BCB.

Improving Survival Prediction Using a Novel Feature Selection and Feature Reduction FrameworkBased on the Integration of Clinical and Molecular Data

Devin C. Koestler, Jeffrey A. Thompson, Lisa Neums, 2019, PSB.

An automated pipeline for discovering gene expression patterns associated with increased cancer survival time

Peter Marks, Jeffrey A. Thompson, Clare Bates Congdon, 2014, BCB.

Training Distribution Matching (TDM) Results: Analysis Code for Accepted TDM Manuscript

Casey S. Greene, Jeffrey A. Thompson, 2016 .

Using genetic algorithms for the inference of motifs that are represented in only a subset of sequences of interest

Jeffrey A. Thompson, Clare Bates Congdon, Jeffrey A. Thompson, 2011, 2011 IEEE International Conference on Bioinformatics and Biomedicine Workshops (BIBMW).

GAMI-CRM: Using de novo motif inference to detect cis-regulatory modules

Jeffrey A. Thompson, Clare Bates Congdon, 2014, 2014 IEEE Congress on Evolutionary Computation (CEC).

An exploration into improving DNA motif inference by looking for highly conserved core regions

Jeffrey A. Thompson, Clare Bates Congdon, Jeffrey A. Thompson, 2013, 2013 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB).

A Methylation-to-Expression Feature Model for Generating Accurate Prognostic Risk Scores and Identifying Disease Targets in Clear Cell Kidney Cancer

Jeffrey A. Thompson, Carmen J. Marsit, Jeffrey A. Thompson, 2017, PSB.