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Series GSE231345 Query DataSets for GSE231345
Status Public on Aug 07, 2023
Title Predicting gene level sensitivity to JAK-STAT signaling perturbation using a mechanistic-to-machine learning framework
Organism Mus musculus
Experiment type Expression profiling by high throughput sequencing
Summary This SuperSeries is composed of the SubSeries listed below.
 
Overall design Refer to individual Series
 
Citation(s) 37292918
Submission date Apr 30, 2023
Last update date Aug 07, 2023
Contact name Rachel A. Gottschalk
E-mail(s) [email protected]
Organization name University of Pittsburgh
Department Immunology
Street address 200 Lothrop St., W1047 BST
City Pittsburgh
State/province Pennsylvania
ZIP/Postal code 15261
Country USA
 
Platforms (1)
GPL30172 NextSeq 2000 (Mus musculus)
Samples (60)
GSM7265400 Control 1, biol rep 1
GSM7265401 IL-6 1 ng/ml, 1 H, biol rep 1
GSM7265402 IL-6 1 ng/ml, 2 H, biol rep 1
This SuperSeries is composed of the following SubSeries:
GSE231343 Predicting gene level sensitivity to JAK-STAT signaling perturbation using a mechanistic-to-machine learning framework I
GSE231344 Predicting gene level sensitivity to JAK-STAT signaling perturbation using a mechanistic-to-machine learning framework II
Relations
BioProject PRJNA964441

Download family Format
SOFT formatted family file(s) SOFTHelp
MINiML formatted family file(s) MINiMLHelp
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Supplementary data files not provided
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