ArticleCell2014
CellNet: network biology applied to stem cell engineering.
Article in Cell, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 315 papers, 2 of them syntheses that pooled it.
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
315 citing papers in PubMed, 2 syntheses or guidelines pooled it, 539 citations in OpenAlex.
- A comprehensive transcriptomic comparison of hepatocyte model systems improves selection of models for experimental use.Communications biology · 2022Pooled it
- Current strategies and opportunities to manufacture cells for modeling human lungs.Advanced drug delivery reviews · 2020Pooled it
- Computational Network Analysis for Defining Transcriptional Programs.Methods in molecular biology (Clifton, N.J.) · 2027Article
- Article
- In Vivo Direct Reprogramming: Current Progress and Future Prospects from Mechanisms to Therapeutic Application.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Review
- Synthetic developmental engineering of human liver organogenesis.Development (Cambridge, England) · 2026Review
- Prediction of parsimonious and temporally sensitive sets of cell fate engineering transcription factors with IMCell.bioRxiv : the preprint server for biology · 2026Article
- Computational blueprints for cell fate programming.Stem cell reports · 2026Review
- Computational modelling of cell identity.The Biochemical journal · 2026Review
- Tunable gene control via RNA splicing with a clinically approved small molecule.Nature communications · 2026Article
- Combinatorial transcription factor interactions drive modular gene regulatory networks.bioRxiv : the preprint server for biology · 2026Article
- Redefining cellular reprogramming with advanced genomic technologies.Nature reviews. Genetics · 2026Review
- Directing stem cell differentiation by chromatin state approximation.Nucleic acids research · 2026Article
- Navigating the landscape of direct cellular reprogramming with DiReG.NPJ systems biology and applications · 2026Article
- A comparison of computational methods for expression forecasting.Genome biology · 2025Article
- Article
- Refate identifies chemical compounds to target trans-regulatory networks for cellular conversion.bioRxiv : the preprint server for biology · 2025Article
- Iterative transcription factor screening enables rapid generation of microglia-like cells from human iPSC.Nature communications · 2025Article
- TFcomb identifies transcription factor combinations for cellular reprogramming based on single-cell multiomics data.Genome research · 2025Article
- SCIG: Machine learning uncovers cell identity genes in single cells by genetic sequence codes.Nucleic acids research · 2025Article
255 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
6 authors at 5 institutions in 2 countries.
Funding
Abstract
Somatic cell reprogramming, directed differentiation of pluripotent stem cells, and direct conversions between differentiated cell lineages represent powerful approaches to engineer cells for research and regenerative medicine. We have developed CellNet, a network biology platform that more accurately assesses the fidelity of cellular engineering than existing methodologies and generates hypotheses for improving cell derivations. Analyzing expression data from 56 published reports, we found that cells derived via directed differentiation more closely resemble their in vivo counterparts than products of direct conversion, as reflected by the establishment of target cell-type gene regulatory networks (GRNs). Furthermore, we discovered that directly converted cells fail to adequately silence expression programs of the starting population and that the establishment of unintended GRNs is common to virtually every cellular engineering paradigm. CellNet provides a platform for quantifying how closely engineered cell populations resemble their target cell type and a rational strategy to guide enhanced cellular engineering.
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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.