Automatic Identification of Co-Occuring Patient Events. - Alexander Titus; Rebecca Faill; Amar Das (BCB, 2016)

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

Investigating Random Forest Classification on Publicly Available Tuberculosis Data to Uncover Robust Transcriptional Biomarkers. - Carly A. Bobak; Alexander J. Titus; Jane E. Hill (HEALTHINF, 2018)

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)

PySEAL: A Python wrapper implementation of the SEAL homomorphic encryption library. - Alexander J. Titus; Shashwat Kishore; Todd Stavish; Stephanie M. Rogers; Karl Ni (CoRR, 2018)

SIG-DB: Leveraging homomorphic encryption to securely interrogate privately held genomic databases. - Alexander J. Titus; Audrey Flower; Patrick Hagerty; Paul Gamble; Charlie Lewis; Todd Stavish; Kevin P. OConnell; Greg Shipley; Stephanie M. Rogers (PLoS Comput. Biol., 2018)

Comparison of common machine learning models for classification of tuberculosis using transcriptional biomarkers from integrated datasets. - Carly A. Bobak; Alexander J. Titus; Jane E. Hill (Appl. Soft Comput., 2019)

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

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)

Ten Quick Tips for Deep Learning in Biology. - Benjamin D. Lee; Anthony Gitter; Casey S. Greene; Sebastian Raschka; Finlay Maguire; Alexander J. Titus; Michael D. Kessler; Alexandra J. Lee; Marc G. Chevrette; Paul Allen Stewart; Thiago Britto-Borges; Evan M. Cofer; et al. (CoRR, 2021)

Ten quick tips for deep learning in biology. - Benjamin D. Lee; Anthony Gitter; Casey S. Greene; Sebastian Raschka; Finlay Maguire; Alexander J. Titus; Michael D. Kessler; Alexandra J. Lee; Marc G. Chevrette; Paul Allen Stewart; Thiago Britto-Borges; Evan M. Cofer; et al. (PLoS Comput. Biol., 2022)

Elephants and Algorithms: A Review of the Current and Future Role of AI in Elephant Monitoring. - Leandra L. Brickson; Fritz Vollrath; Alexander J. Titus (CoRR, 2023)

The Promise and Peril of Artificial Intelligence - Violet Teaming Offers a Balanced Path Forward. - Alexander J. Titus; Adam H. Russell (CoRR, 2023)

NHANES-GCP: Leveraging the Google Cloud Platform and BigQuery ML for reproducible machine learning with data from the National Health and Nutrition Examination Survey. - B. Ross Katz; Abdul Khan; James York-Winegar; Alexander J. Titus (CoRR, 2024)

Integrating MLSecOps in the Biotechnology Industry 5.0. - Naseela Pervez; Alexander J. Titus (CoRR, 2024)

Computing in the Life Sciences: From Early Algorithms to Modern AI. - Samuel A. Donkor; Matthew E. Walsh; Alexander J. Titus (CoRR, 2024)

Inclusivity in Large Language Models: Personality Traits and Gender Bias in Scientific Abstracts. - Naseela Pervez; Alexander J. Titus (CoRR, 2024)

Adaptable Embeddings Network (AEN). - Stan Loosmore; Alexander Titus (CoRR, 2024)