ReviewNeuron2015
Cell-based screening: extracting meaning from complex data.
Review in Neuron, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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
21 citing papers in PubMed.
- An Open-Source Pipeline for Calcium Imaging and All-Optical Physiology in Human Stem Cell-Derived Neurons.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Integrated multi-omic characterizations of the synapse reveal RNA processing factors and ubiquitin ligases associated with neurodevelopmental disorders.Cell systems · 2025Article
- Superhuman cell death detection with biomarker-optimized neural networks.Science advances · 2021Article
- Genetically encoded cell-death indicators (GEDI) to detect an early irreversible commitment to neurodegeneration.Nature communications · 2021Article
- Rapid 3D phenotypic analysis of neurons and organoids using data-driven cell segmentation-free machine learning.PLoS computational biology · 2021Article
- Functional genomics, genetic risk profiling and cell phenotypes in neurodegenerative disease.Neurobiology of disease · 2020Review
- BrainPhys neuronal medium optimized for imaging and optogenetics in vitro.Nature communications · 2020Article
- Machine learning-enabled multiplexed microfluidic sensors.Biomicrofluidics · 2020Review
- Human pluripotent stem cell-derived models and drug screening in CNS precision medicine.Annals of the New York Academy of Sciences · 2020Review
- Cell death assays for neurodegenerative disease drug discovery.Expert opinion on drug discovery · 2019Review
- HDAC Inhibitors InduceInternational journal of molecular sciences · 2019Article
- Automated four-dimensional long term imaging enables single cell tracking within organotypic brain slices to study neurodevelopment and degeneration.Communications biology · 2019Article
- Review
- Review
- iPS cells in the study of PD molecular pathogenesis.Cell and tissue research · 2018Review
- Article
- Genome, transcriptome and proteome: the rise of omics data and their integration in biomedical sciences.Briefings in bioinformatics · 2018Review
- Advancing drug discovery for neuropsychiatric disorders using patient-specific stem cell models.Molecular and cellular neurosciences · 2016Review
- Concise Review: Progress and Challenges in Using Human Stem Cells for Biological and Therapeutics Discovery: Neuropsychiatric Disorders.Stem cells (Dayton, Ohio) · 2016Review
- Systems-level neurophysiological state characteristics for drug evaluation in an animal model of levodopa-induced dyskinesia.Journal of neurophysiology · 2016Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
Unbiased discovery approaches have the potential to uncover neurobiological insights into CNS disease and lead to the development of therapies. Here, we review lessons learned from imaging-based screening approaches and recent advances in these areas, including powerful new computational tools to synthesize complex data into more useful knowledge that can reliably guide future research and development.
Indexed as
Identifiers
What OpenQuestion holds
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.