Mike A. Nalls

15 papers A* 2B 1Journal 12
YearRankTypeTitle / Venue / Authors
2025 J jnl
BiomedSQL: Text-to-SQL for Scientific Reasoning on Biomedical Knowledge Bases.
CoRR
Mathew J. Koretsky, Maya Willey, Adi Asija, Owen Bianchi, Chelsea X. Alvarado, Tanay Nayak, Nicole Kuznetsov, Sungwon Kim, Mike A. Nalls, Daniel Khashabi, Faraz Faghri
2025 J jnl
Lost in the Haystack: Smaller Needles are More Difficult for LLMs to Find.
CoRR
Owen Bianchi, Mathew J. Koretsky, Maya Willey, Chelsea X. Alvarado, Tanay Nayak, Adi Asija, Nicole Kuznetsov, Mike A. Nalls, Faraz Faghri, Daniel Khashabi
2025 J jnl
ProtPipe: A Multifunctional Data Analysis Pipeline for Proteomics and Peptidomics.
Genom. Proteom. Bioinform.
Ziyi Li, Cory A. Weller, Syed Shah, Nicholas L. Johnson, Ying Hao, Paige B. Jarreau, Jessica Roberts, Deyaan Guha, Colleen Bereda, Sydney Klaisner, Pedro Machado, Matteo Zanovello, Mercedes Prudencio, Björn Oskarsson, Nathan P. Staff, Dennis W. Dickson, Pietro Fratta, Leonard Petrucelli, Priyanka Narayan, Mark R. Cookson, Michael E. Ward, Andrew B. Singleton, Mike A. Nalls, Yue A. Qi
2025 J jnl
SECONDGRAM: Self-conditioned diffusion with gradient manipulation for longitudinal MRI imputation.
Patterns
Brandon Theodorou, Anant Dadu, Mike A. Nalls, Faraz Faghri, Jimeng Sun
2024 J jnl
Federated learning for multi-omics: A performance evaluation in Parkinson's disease.
Patterns
Benjamin P. Danek, Mary B. Makarious, Anant Dadu, Dan Vitale, Paul Suhwan Lee, Andrew B. Singleton, Mike A. Nalls, Jimeng Sun, Faraz Faghri
2024 A* conf
Instruction Tuning Large Language Models to Understand Electronic Health Records.
NeurIPS
Zhenbang Wu, Anant Dadu, Mike A. Nalls, Faraz Faghri, Jimeng Sun
2024 A* conf
Multimodal Patient Representation Learning with Missing Modalities and Labels.
ICLR
Zhenbang Wu, Anant Dadu, Nicholas J. Tustison, Brian B. Avants, Mike A. Nalls, Jimeng Sun, Faraz Faghri
2023 J jnl
Application of Aligned-UMAP to longitudinal biomedical studies.
Patterns
Anant Dadu, Vipul Satone, Rachneet Kaur, Mathew J. Koretsky, Hirotaka Iwaki, Yue A. Qi, Daniel M. Ramos, Brian B. Avants, Jacob Hesterman, Roger N. Gunn, Mark R. Cookson, Michael E. Ward, Andrew B. Singleton, Roy H. Campbell, Mike A. Nalls, Faraz Faghri
2022 J jnl
PhenoExam: gene set analyses through integration of different phenotype databases.
BMC Bioinform.
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
2021 J jnl
GenoML: Automated Machine Learning for Genomics.
CoRR
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
2021 J jnl
Modeling multifunctionality of genes with secondary gene co-expression networks in human brain provides novel disease insights.
Bioinform.
Juan A. Sánchez, Ana Luisa Gil-Martínez, Alejandro Cisterna, Sonia García-Ruíz, Alicia Gómez-Pascual, Regina H. Reynolds, Mike A. Nalls, John Hardy, Mina Ryten, Juan A. Botía
2021 J jnl
Uncovering the complexities of biological structures with network-based learning: An application in SARS-CoV-2.
Patterns
Faraz Faghri, Mike A. Nalls
2018 J jnl
Learning the progression and clinical subtypes of Alzheimer's disease from longitudinal clinical data.
CoRR
Vipul Satone, Rachneet Kaur, Faraz Faghri, Mike A. Nalls, Andrew B. Singleton, Roy H. Campbell
2017 J jnl
Toward Scalable Machine Learning and Data Mining: the Bioinformatics Case.
CoRR
Faraz Faghri, Sayed Hadi Hashemi, Mohammad Babaeizadeh, Mike A. Nalls, Saurabh Sinha, Roy H. Campbell
2007 B conf
Segmentation of magnetic resonance images of the thighs for a new National Institutes of Health initiative.
Image Processing
A. Monzon, Paul F. Hemler, Mike A. Nalls, Todd M. Manini, Brian C. Clark, T. B. Harris, Matthew J. McAuliffe