Joseph D. Romano

According to our database, Joseph D. Romano authored at least 17 papers between 2015 and 2026.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2026

Learnable protein representations in computational biology for predicting drug-target affinity.

Rachit Kumar, Joseph D. Romano, Marylyn D. Ritchie

J. Cheminformatics, December, 2026

2025

Towards symbolic regression for interpretable clinical decision scores.

Guilherme Seidyo Imai Aldeia, Joseph D. Romano, Fabrício Olivetti de França, Daniel S. Herman, William G. La Cava

CoRR, December, 2025

Network-based analyses of multiomics data in biomedicine.

Rachit Kumar, Joseph D. Romano, Marylyn D. Ritchie

BioData Min., 2025

CASTER-DTA: equivariant graph neural networks for predicting drug-target affinity.

Rachit Kumar, Joseph D. Romano, Marylyn D. Ritchie

Briefings Bioinform., 2025

Enhancing Molecular Representation Learning Through the Combination of 3D and 2D Graph Machine Learning (Student Abstract).

Ian Tong Pan, Joseph D. Romano

Proceedings of the Thirty-Ninth AAAI Conference on Artificial Intelligence, 2025

2023

Extending Tree-Based Automated Machine Learning to Biomedical Image and Text Data Using Custom Feature Extractors.

Rachit Kumar, Joseph D. Romano, Marylyn D. Ritchie, Jason H. Moore

Proceedings of the Companion Proceedings of the Conference on Genetic and Evolutionary Computation, 2023

2022

Knowledge-guided deep learning models of drug toxicity improve interpretation.

Yun Hao, Joseph D. Romano, Jason H. Moore

Patterns, 2022

PMLB v1.0: an open-source dataset collection for benchmarking machine learning methods.

Joseph D. Romano, Trang T. Le, William G. La Cava, John T. Gregg, Daniel J. Goldberg, Praneel Chakraborty, Natasha L. Ray, Daniel S. Himmelstein, Weixuan Fu, Jason H. Moore

Bioinform., 2022

2021

TPOT-NN: augmenting tree-based automated machine learning with neural network estimators.

Joseph D. Romano, Trang T. Le, Weixuan Fu, Jason H. Moore

Genet. Program. Evolvable Mach., 2021

2020

Ten simple rules for writing a paper about scientific software.

Joseph D. Romano, Jason H. Moore

PLoS Comput. Biol., 2020

Is deep learning necessary for simple classification tasks?

Joseph D. Romano, Trang T. Le, Weixuan Fu, Jason H. Moore

CoRR, 2020

Embedding covariate adjustments in tree-based automated machine learning for biomedical big data analyses.

Elisabetta Manduchi, Weixuan Fu, Joseph D. Romano, Stefano Ruberto, Jason H. Moore

BMC Bioinform., 2020

2019

Hasasia: A Python package for Pulsar Timing Array Sensitivity Curves.

Jeffrey S. Hazboun, Joseph D. Romano, Tristan L. Smith

J. Open Source Softw., 2019

2018

Using model classifications as quantitative traits to estimate stroke heritability.

Phyllis M. Thangaraj, Fernanda C. Polubriaginof, Benjamin Kummer, Rami Vanguri, Tal Lorberbaum, Joseph D. Romano, Kayla Quinnies, Alexandre Yahi, Mitchell S. V. Elkind, Nicholas P. Tatonetti

Proceedings of the AMIA 2018, 2018

2017

Deep recurrent neural networks identify transgender patients.

Joseph D. Romano, Kenrick Cato, Rami Vanguri, Nicholas P. Tatonetti

Proceedings of the AMIA 2017, 2017

The Use of Informatics to Reduce Disparities in Transgender Health.

Kenrick Cato, Joseph D. Romano, Rami Vanguri, Nicholas P. Tatonetti

Proceedings of the AMIA 2017, 2017

2015

Adapting simultaneous analysis phylogenomic techniques to study complex disease gene relationships.

Joseph D. Romano, William G. Tharp, Indra Neil Sarkar

J. Biomed. Informatics, 2015