ArticleMolecular systems biology2022
Quantifying the phenotypic information in mRNA abundance.
Article in Molecular systems biology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 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
6 citing papers in PubMed, 7 citations in OpenAlex.
- Defining the heterogeneous molecular landscape of lung cancer cell responses to epigenetic inhibition.Communications biology · 2026Article
- Spatial Single-Cell Mapping of Transcriptional Differences Across Genetic Backgrounds in Mouse Brains.bioRxiv : the preprint server for biology · 2024Article
- Stimulus-response signaling dynamics characterize macrophage polarization states.Cell systems · 2024Article
- Integrating single-cell transcriptomics with cellular phenotypes: cell morphology, CaBiophysical reviews · 2024Review
- Bow-tie architectures in biological and artificial neural networks: Implications for network evolution and assay design.iScience · 2023Article
- Quantifying the phenotypic information in mRNA abundance.Molecular systems biology · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Quantifying the dependency between mRNA abundance and downstream cellular phenotypes is a fundamental open problem in biology. Advances in multimodal single-cell measurement technologies provide an opportunity to apply new computational frameworks to dissect the contribution of individual genes and gene combinations to a given phenotype. Using an information theory approach, we analyzed multimodal data of the expression of 83 genes in the Ca
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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.