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Mapping regulatory variation in sensory neurons using IPS lines from the HIPSCI project

ChEBI2017-01-06 更新2026-07-12 收录

iPSC神经分化

感觉神经元调控基因组学

数据链接：

https://www.ebi.ac.uk/biostudies/ArrayExpress/studies/E-ERAD-596 数据链接链接失效反馈

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资源简介：

Mapping regulatory variation in sensory neurons using IPS lines from the HIPSCI project

应用场景：

创建时间：

2017-01-06

iPSC神经分化

神经细胞分析

(A) Protocols for differentiation of IPSC-derived NPC into different brain cell types (neurons, Ast and OLs). (B) Morphology of different brain cell types as phase contrast images at the end of differ

NIAID Data Ecosystem60

Neuronal and glial Gene expression from control and healthy patient iPSC-derived cortical neurons

iPSC神经分化

神经细胞基因表达

This SuperSeries is composed of the SubSeries listed below. Refer to individual Series

NIAID Data Ecosystem30

REST and Neural Gene Network Dysregulation in iPS Cell Models of Alzheimer’s Disease (RNA-seq data set)

阿尔茨海默病分子机制

iPSC神经分化

Alzheimer’s disease (AD) is preceded by a long prodromal period of decades during which pathology accumulates in the brain prior to the onset of dementia. The molecular basis of these changes as well

NIAID Data Ecosystem30

Functional neurons generated from T cell-derived iPSCs for neurological disease modeling. Functional neurons generated from T cell-derived iPSCs for neurological disease modeling

iPSC神经分化

疾病建模

This SuperSeries is composed of the SubSeries listed below. Overall design: Refer to individual Series

NIAID Data Ecosystem40

Reproducibility of molecular phenotypes after long-term differentiation to Human iPSC-Derived Neurons: a multi-site omics study [bulk]. Reproducibility of molecular phenotypes after long-term differentiation to Human iPSC-Derived Neurons: a multi-site omics study [bulk]

iPSC神经分化

多中心组学可重复性

Reproducibility in molecular and cellular studies is fundamental to scientific discovery. To establish the reproducibility of a well-defined long term neuronal differentiation protocol, we repeated th

NIAID Data Ecosystem30

Mapping regulatory variation in sensory neurons using IPS lines from the HIPSCI project

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