Mike A. Nalls

According to our database, Mike A. Nalls authored at least 9 papers between 2007 and 2024.

Collaborative distances:

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

2024

Federated learning for multi-omics: A performance evaluation in Parkinson's disease.

Benjamin P. Danek, Mary B. Makarious, Anant Dadu, Dan Vitale, Paul Suhwan Lee, Andrew B. Singleton, Mike A. Nalls, Jimeng Sun, Faraz Faghri

Patterns, March, 2024

2023

Application of Aligned-UMAP to longitudinal biomedical studies.

Anant Dadu, Vipul Satone, Rachneet Kaur, Mathew J. Koretsky, Hirotaka Iwaki, Yue A. Qi, Daniel M. Ramos, Brian B. Avants, Jacob Hesterman, Roger Gunn, Mark R. Cookson, Michael E. Ward, Andrew B. Singleton, Roy H. Campbell, Mike A. Nalls, Faraz Faghri

Patterns, June, 2023

2022

PhenoExam: gene set analyses through integration of different phenotype databases.

Alejandro Cisterna, Aurora González-Vidal, Daniel Ruiz, Jordi Ortiz, Alicia Gómez-Pascual, Zhongbo Chen, Mike A. Nalls, Faraz Faghri, John Hardy, Irene Díez, Paolo Maietta, Sara Álvarez, Mina Ryten, Juan A. Botía

BMC Bioinform., December, 2022

2021

Uncovering the complexities of biological structures with network-based learning: An application in SARS-CoV-2.

Faraz Faghri, Mike A. Nalls

Patterns, 2021

GenoML: Automated Machine Learning for Genomics.

Mary B. Makarious, Hampton L. Leonard, Dan Vitale, Hirotaka Iwaki, David Saffo, Lana Sargent, Anant Dadu, Eduardo Salmerón Castaño, John F. Carter, Melina Maleknia, Juan A. Botía, Cornelis Blauwendraat, Roy H. Campbell, Sayed Hadi Hashemi, Andrew B. Singleton, Mike A. Nalls, Faraz Faghri

CoRR, 2021

Modeling multifunctionality of genes with secondary gene co-expression networks in human brain provides novel disease insights.

Juan A. Sánchez, Ana L. Gil-Martinez, Alejandro Cisterna, Sonia García-Ruíz, Alicia Gómez-Pascual, Regina H. Reynolds, Mike A. Nalls, John Hardy, Mina Ryten, Juan A. Botía

Bioinform., 2021

2018

Learning the progression and clinical subtypes of Alzheimer's disease from longitudinal clinical data.

Vipul Satone, Rachneet Kaur, Faraz Faghri, Mike A. Nalls, Andrew B. Singleton, Roy H. Campbell

CoRR, 2018

2017

Toward Scalable Machine Learning and Data Mining: the Bioinformatics Case.

Faraz Faghri, Sayed Hadi Hashemi, Mohammad Babaeizadeh, Mike A. Nalls, Saurabh Sinha, Roy H. Campbell

CoRR, 2017

2007

Segmentation of magnetic resonance images of the thighs for a new National Institutes of Health initiative.

A. Monzon, Paul F. Hemler, Mike A. Nalls, T. Manini, B. C. Clark, T. B. Harris, Matthew J. McAuliffe

Proceedings of the Medical Imaging 2007: Image Processing, 2007