GSM7265441[Accession] - GEO DataSets

Warning: The NCBI web site requires JavaScript to function. more...

Format

Summary
Summary (text)
Unique Identifier List

Sort by

Default order
Number of Samples (High to Low)
Number of Samples (Low to High)

Send to:

Choose Destination

File
Clipboard
Collections

Search results

Items: 4

Select item 2002313451.

Predicting gene level sensitivity to JAK-STAT signaling perturbation using a mechanistic-to-machine learning framework

(Submitter supplied) This SuperSeries is composed of the SubSeries listed below.

Organism:: Mus musculus

Type:: Expression profiling by high throughput sequencing

Platform:: GPL30172
60 Samples

Download data

Series

Accession:: GSE231345

ID:: 200231345

PubMed Full text in PMC Similar studies

Select item 2002313442.

Predicting gene level sensitivity to JAK-STAT signaling perturbation using a mechanistic-to-machine learning framework II

(Submitter supplied) To inhibit JAK2 upon IL-6 and IL-10-induced JAK-STAT signaling and quantify gene expression in bone marrow derived macrophages (BMDMs). Bulk RNAseq was done on cytokine-stimulated BMDM with and without Fedratinib treatment in order to profile the JAK2-inhibited cytokine-induced response.