P.GRI-230228-V1_2.4-Linear-Mixed-Model-for-Proteomics-Data Version 1
SEEK ID: https://fairdomhub.org/sops/686?version=1
Filename:
2.4 Linear Mixed Model for Proteomics Data.docx
Format: Word document
Size: 54.9 KB
Export PNG
Creators and SubmitterViews: 595 Downloads: 45
Created: 7th Nov 2023 at 20:39
Last updated: 17th Nov 2023 at 21:43
TagsThis item has not yet been tagged.
AttributionsNone
Version History
Version 1 (earliest) Created 7th Nov 2023 at 20:39 by Charles Demurjian
No revision comments
Related items
Projects: Hi-IMPAcTB, MIT SRP, MetNet, Endometriosis, Cancer Systems Biology Consortium (CSBC), Shoulders Lab
Institutions: Massachusetts Institute of Technology
Projects: MIT SRP, Hi-IMPAcTB, MetNet, Endometriosis, Cancer Systems Biology Consortium (CSBC), Shoulders Lab
Web page: https://nextseek.mit.edu/
Endometriosis research done by the Griffith lab (MIT) and the Goods lab (Dartmouth)
Programme: NExtSEEK
Public web page: Not specified
Submitter: Charles Demurjian
Studies: Integrating endometrial proteomic and single cell transcriptomic pipelin..., Organoid co-culture model of the cycling human endometrium in a fully-de...
Assays: All Metadata, All Metadata, Cell Culture Imaging - Data Linked, Cell Culture and Organoid Generation - Metadata, DNA Extraction - Metadata, DNA Extraction - Metadata, Elisa - Data Linked, Gene Expression Analysis - Data Linked, Immunohistochemistry - Data Linked, Linear Mixed Model - Data Linked, Luminex - Data Linked, Mass Spectrometry Proteomics - Data Linked, Mass Spectrometry Proteomics Analysis - Data Linked, Patient Visit - Metadata, Patient Visit - Metadata, Short Read Sequencing - Data Linked, Single Cell Expression Matrix Analysis - Data Linked, Single Cell Sequencing - Data Linked, Tissue Collection - Metadata, Tissue Collection - Metadata
Lauren Baugh, Brittany A. Goods, Juan S. Gnecco, Yunbeen Bae, Michael Retchin, Constantine N. Tzouanas, Megan Loring, Keith Isaacson, Alex K. Shalek, Douglas Lauffenburger, Linda Griffith
https://www.medrxiv.org/content/10.1101/2022.01.29.22269829v1
Endometriosis is a debilitating gynecological disorder affecting approximately 10% of the female population. Despite its prevalence, robust methods to classify and treat endometriosis remain elusive. Changes ...
Submitter: Charles Demurjian
Investigation: Endometriosis
Assays: All Metadata, DNA Extraction - Metadata, Immunohistochemistry - Data Linked, Linear Mixed Model - Data Linked, Mass Spectrometry Proteomics - Data Linked, Mass Spectrometry Proteomics Analysis - Data Linked, Patient Visit - Metadata, Single Cell Expression Matrix Analysis - Data Linked, Single Cell Sequencing - Data Linked, Tissue Collection - Metadata
Submitter: Charles Demurjian
Assay type: Experimental Assay Type
Technology type: Technology Type
Investigation: Endometriosis
