ReviewJournal of the Royal Society, Interface2012
Quantitative biology of single neurons.
Review in Journal of the Royal Society, Interface, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 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
9 citing papers in PubMed.
- Technological advances in cancer immunity: from immunogenomics to single-cell analysis and artificial intelligence.Signal transduction and targeted therapy · 2021Review
- Article
- Single cell transcriptomics of noncoding RNAs and their cell-specificity.Wiley interdisciplinary reviews. RNA · 2017Review
- Cellular Deconstruction: Finding Meaning in Individual Cell Variation.Trends in cell biology · 2015Review
- Experience and the ever-changing brain: what the transcriptome can reveal.BioEssays : news and reviews in molecular, cellular and developmental biology · 2014Review
- Divergence of RNA localization between rat and mouse neurons reveals the potential for rapid brain evolution.BMC genomics · 2014Article
- Single-cell RNA-seq: advances and future challenges.Nucleic acids research · 2014Review
- Atomic force microscopic detection enabling multiplexed low-cycle-number quantitative polymerase chain reaction for biomarker assays.Analytical chemistry · 2014Article
- Transcriptome in vivo analysis (TIVA) of spatially defined single cells in live tissue.Nature methods · 2014Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
15 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The building blocks of complex biological systems are single cells. Fundamental insights gained from single-cell analysis promise to provide the framework for understanding normal biological systems development as well as the limits on systems/cellular ability to respond to disease. The interplay of cells to create functional systems is not well understood. Until recently, the study of single cells has concentrated primarily on morphological and physiological characterization. With the application of new highly sensitive molecular and genomic technologies, the quantitative biochemistry of single cells is now accessible.
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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.