ArticleFrontiers in molecular neuroscience2018
Patch-Seq Protocol to Analyze the Electrophysiology, Morphology and Transcriptome of Whole Single Neurons Derived From Human Pluripotent Stem Cells.
Article in Frontiers in molecular neuroscience, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 26 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
26 citing papers in PubMed.
- Mapping human brain cell type origin and diseases through single-cell transcriptomics.Translational psychiatry · 2025Review
- Patch-walking, a coordinated multi-pipette patch clamp for efficiently finding synaptic connections.eLife · 2024Article
- Patch-walking: Coordinated multi-pipette patch clamp for efficiently finding synaptic connections.bioRxiv : the preprint server for biology · 2024Article
- Rigor and reproducibility in human brain organoid research: Where we are and where we need to go.Stem cell reports · 2024Review
- Multimodal Nature of the Single-cell Primate Brain Atlas: Morphology, Transcriptome, Electrophysiology, and Connectivity.Neuroscience bulletin · 2024Review
- Integrating single-cell transcriptomics with cellular phenotypes: cell morphology, CaBiophysical reviews · 2024Review
- Patch-seq: Advances and Biological Applications.Cellular and molecular neurobiology · 2023Review
- Druggable transcriptomic pathways revealed in Parkinson's patient-derived midbrain neurons.NPJ Parkinson's disease · 2022Article
- Patch-to-Seq and Transcriptomic Analyses Yield Molecular Markers of Functionally Distinct Brainstem Serotonin Neurons.Frontiers in synaptic neuroscience · 2022Article
- Review
- Joint single-cell multiomic analysis in Wnt3a induced asymmetric stem cell division.Nature communications · 2021Article
- Scaled, high fidelity electrophysiological, morphological, and transcriptomic cell characterization.eLife · 2021Article
- Review
- Basic and Preclinical Research for Personalized Medicine.Journal of personalized medicine · 2021Review
- The difficulty to model Huntington's disease in vitro using striatal medium spiny neurons differentiated from human induced pluripotent stem cells.Scientific reports · 2021Article
- How well do brain organoids capture your brain?iScience · 2021Review
- Patch-seq: Past, Present, and Future.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2021Review
- Cell Surface Protein mRNAs Show Differential Transcription in Pyramidal and Fast-Spiking Cells as Revealed by Single-Cell Sequencing.Cerebral cortex (New York, N.Y. : 1991) · 2021Article
- Protocol for Patch-Seq of Small Interneurons.STAR protocols · 2020Article
- Review
Corrections and comments
- Erratum issued
Authors and funding
5 authors.
Funding
Abstract
The human brain is composed of a complex assembly of about 171 billion heterogeneous cellular units (86 billion neurons and 85 billion non-neuronal glia cells). A comprehensive description of brain cells is necessary to understand the nervous system in health and disease. Recently, advances in genomics have permitted the accurate analysis of the full transcriptome of single cells (scRNA-seq). We have built upon such technical progress to combine scRNA-seq with patch-clamping electrophysiological recording and morphological analysis of single human neurons
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.