Search research articles
Contact Us
Filters
Showing results (1-10 of 56) with videos related to
Page
of 6
Sort By:
Arthritis Research & Therapy
|
June 8, 2004
B cell abnormalities in systemic lupus erythematosus
Amrie C Grammer, Peter E Lipsky
Rheumatic Diseases Clinics of North America
|
July 17, 2017
Drug Repositioning Strategies for the Identification of Novel Therapies for Rheumatic Autoimmune Inflammatory Diseases
Amrie C Grammer, Peter E Lipsky
The Journal of Allergy and Clinical Immunology
|
December 3, 2021
Deconvoluting the heterogeneity of SLE: The contribution of ancestry
Katherine A Owen, Amrie C Grammer, Peter E Lipsky
Current Opinion in Rheumatology
|
August 19, 2021
Transcriptomics data: pointing the way to subclassification and personalized medicine in systemic lupus erythematosus
Erika L Hubbard, Amrie C Grammer, Peter E Lipsky
Nature Reviews. Rheumatology
|
December 14, 2019
Drug repurposing to improve treatment of rheumatic autoimmune inflammatory diseases
Kathryn M Kingsmore, Amrie C Grammer, Peter E Lipsky
The Journal of Biological Chemistry
|
September 24, 2004
TRAF3 forms heterotrimers with TRAF2 and modulates its ability to mediate NF-{kappa}B activation
Liusheng He, Amrie C Grammer, Xiaoli Wu, et al.
Lupus Science & Medicine
|
May 14, 2025
Validation of eight endotypes of lupus based on whole-blood RNA profiles
Erika Hubbard, Prathyusha Bachali, Amrie C Grammer, et al.
International Journal of Molecular Sciences
|
March 11, 2023
Classification of COVID-19 Patients into Clinically Relevant Subsets by a Novel Machine Learning Pipeline Using Transcriptomic Features
Andrea R Daamen, Prathyusha Bachali, Amrie C Grammer, et al.
Nature Reviews. Rheumatology
|
November 3, 2021
An introduction to machine learning and analysis of its use in rheumatic diseases
Kathryn M Kingsmore, Christopher E Puglisi, Amrie C Grammer, et al.
Iscience
|
October 20, 2023
An interpretable machine learning pipeline based on transcriptomics predicts phenotypes of lupus patients
Emily L Leventhal, Andrea R Daamen, Amrie C Grammer, et al.
Page
of 6
Search research articles
Search
Showing results (1-10 of 56) with videos related to
Sort By:
Page
of 6
Arthritis Research & Therapy
|
June 8, 2004
B cell abnormalities in systemic lupus erythematosus
Amrie C Grammer, Peter E Lipsky
Rheumatic Diseases Clinics of North America
|
July 17, 2017
Drug Repositioning Strategies for the Identification of Novel Therapies for Rheumatic Autoimmune Inflammatory Diseases
Amrie C Grammer, Peter E Lipsky
The Journal of Allergy and Clinical Immunology
|
December 3, 2021
Deconvoluting the heterogeneity of SLE: The contribution of ancestry
Katherine A Owen, Amrie C Grammer, Peter E Lipsky
Current Opinion in Rheumatology
|
August 19, 2021
Transcriptomics data: pointing the way to subclassification and personalized medicine in systemic lupus erythematosus
Erika L Hubbard, Amrie C Grammer, Peter E Lipsky
Nature Reviews. Rheumatology
|
December 14, 2019
Drug repurposing to improve treatment of rheumatic autoimmune inflammatory diseases
Kathryn M Kingsmore, Amrie C Grammer, Peter E Lipsky
The Journal of Biological Chemistry
|
September 24, 2004
TRAF3 forms heterotrimers with TRAF2 and modulates its ability to mediate NF-{kappa}B activation
Liusheng He, Amrie C Grammer, Xiaoli Wu, et al.
Lupus Science & Medicine
|
May 14, 2025
Validation of eight endotypes of lupus based on whole-blood RNA profiles
Erika Hubbard, Prathyusha Bachali, Amrie C Grammer, et al.
International Journal of Molecular Sciences
|
March 11, 2023
Classification of COVID-19 Patients into Clinically Relevant Subsets by a Novel Machine Learning Pipeline Using Transcriptomic Features
Andrea R Daamen, Prathyusha Bachali, Amrie C Grammer, et al.
Nature Reviews. Rheumatology
|
November 3, 2021
An introduction to machine learning and analysis of its use in rheumatic diseases
Kathryn M Kingsmore, Christopher E Puglisi, Amrie C Grammer, et al.
Iscience
|
October 20, 2023
An interpretable machine learning pipeline based on transcriptomics predicts phenotypes of lupus patients
Emily L Leventhal, Andrea R Daamen, Amrie C Grammer, et al.
Page
of 6