ArticleCell2014
CellNet--where your cells are standing.
Article in Cell, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 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
3 citing papers in PubMed.
- Article
- Reconstructed cell fate-regulatory programs in stem cells reveal hierarchies and key factors of neurogenesis.Genome research · 2016Article
- Reconstruction of gene regulatory networks reveals chromatin remodelers and key transcription factors in tumorigenesis.Genome medicine · 2016Article
Corrections and comments
- Comment on
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The manufacturing of clinically relevant cells is a widely used strategy in regenerative medicine. Cahan et al. develop a network biology platform named CellNet to accurately assess the fidelity of such cells and spot aberrant regulatory networks, and Morris et al. apply this platform to improve cell manufacturing.
Indexed as
Identifiers
25126778What 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.