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Biorxiv : the Preprint Server for Biology
|
November 24, 2025
Adaptive resampling for improved machine learning in imbalanced single-cell datasets
Zeinab Navidi, Akshaya Thoutam, Madeline Hughes, et al.
Nature Communications
|
January 6, 2026
Deep learning guided design of protease substrates
Carmen Martin-Alonso, Sarah Alamdari, Tahoura S Samad, et al.
Cell
|
April 17, 2026
Tackling the complexity of cancer with generative models
Ashley Mae Conard, Madeline Hughes, James Hall, et al.
American Journal of Human Genetics
|
March 13, 2025
Artificial variables help to avoid over-clustering in single-cell RNA sequencing
Alan DenAdel, Michelle L Ramseier, Andrew W Navia, et al.
Nature Communications
|
February 5, 2024
Protein structure generation via folding diffusion
Kevin E Wu, Kevin K Yang, Rianne van den Berg, et al.
Biorxiv : the Preprint Server for Biology
|
March 10, 2025
Consequences of training data composition for deep learning models in single-cell biology
Ajay Nadig, Akshaya Thoutam, Madeline Hughes, et al.
Nature Methods
|
June 9, 2026
Evaluating the role of pretraining dataset size and diversity on single-cell foundation model performance
Alan DenAdel, Madeline Hughes, Akshaya Thoutam, et al.
Biorxiv : the Preprint Server for Biology
|
November 24, 2025
Evaluating the role of pre-training dataset size and diversity on single-cell foundation model performance
Alan DenAdel, Madeline Hughes, Akshaya Thoutam, et al.
Cell Reports Methods
|
March 13, 2026
Scalable nonparametric clustering with unified marker gene selection for single-cell RNA-seq data
Chibuikem Nwizu, Madeline Hughes, Michelle L Ramseier, et al.
Biorxiv : the Preprint Server for Biology
|
February 26, 2024
Scalable nonparametric clustering with unified marker gene selection for single-cell RNA-seq data
Chibuikem Nwizu, Madeline Hughes, Michelle L Ramseier, et al.
Page
of 3
Search research articles
Search
Showing results (11-20 of 26) with videos related to
Sort By:
Page
of 3
Biorxiv : the Preprint Server for Biology
|
November 24, 2025
Adaptive resampling for improved machine learning in imbalanced single-cell datasets
Zeinab Navidi, Akshaya Thoutam, Madeline Hughes, et al.
Nature Communications
|
January 6, 2026
Deep learning guided design of protease substrates
Carmen Martin-Alonso, Sarah Alamdari, Tahoura S Samad, et al.
Cell
|
April 17, 2026
Tackling the complexity of cancer with generative models
Ashley Mae Conard, Madeline Hughes, James Hall, et al.
American Journal of Human Genetics
|
March 13, 2025
Artificial variables help to avoid over-clustering in single-cell RNA sequencing
Alan DenAdel, Michelle L Ramseier, Andrew W Navia, et al.
Nature Communications
|
February 5, 2024
Protein structure generation via folding diffusion
Kevin E Wu, Kevin K Yang, Rianne van den Berg, et al.
Biorxiv : the Preprint Server for Biology
|
March 10, 2025
Consequences of training data composition for deep learning models in single-cell biology
Ajay Nadig, Akshaya Thoutam, Madeline Hughes, et al.
Nature Methods
|
June 9, 2026
Evaluating the role of pretraining dataset size and diversity on single-cell foundation model performance
Alan DenAdel, Madeline Hughes, Akshaya Thoutam, et al.
Biorxiv : the Preprint Server for Biology
|
November 24, 2025
Evaluating the role of pre-training dataset size and diversity on single-cell foundation model performance
Alan DenAdel, Madeline Hughes, Akshaya Thoutam, et al.
Cell Reports Methods
|
March 13, 2026
Scalable nonparametric clustering with unified marker gene selection for single-cell RNA-seq data
Chibuikem Nwizu, Madeline Hughes, Michelle L Ramseier, et al.
Biorxiv : the Preprint Server for Biology
|
February 26, 2024
Scalable nonparametric clustering with unified marker gene selection for single-cell RNA-seq data
Chibuikem Nwizu, Madeline Hughes, Michelle L Ramseier, et al.
Page
of 3