ArticleStem cell reports2023
A single cell-based computational platform to identify chemical compounds targeting desired sets of transcription factors for cellular conversion.
Article in Stem cell reports, 2023. 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.
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Who cites it
6 citing papers in PubMed, 6 citations in OpenAlex.
- Computational blueprints for cell fate programming.Stem cell reports · 2026Review
- Simulation-guided chemical direct reprogramming informed by temporal cellular conversion processes at the single-cell level.Communications chemistry · 2026Article
- Identification of a Small-Molecule Modulator of Astrocyte Reactivity for Optic Nerve Protection.Investigative ophthalmology & visual science · 2026Article
- Chemical reprogramming of fibroblasts into retinal pigment epithelium cells for vision restoration.Nature communications · 2025Article
- Refate identifies chemical compounds to target trans-regulatory networks for cellular conversion.bioRxiv : the preprint server for biology · 2025Article
- A two-step strategy to expand primary human hepatocytes in vitro with efficient metabolic and regenerative capacities.Stem cell research & therapy · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 4 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Cellular conversion can be induced by perturbing a handful of key transcription factors (TFs). Replacement of direct manipulation of key TFs with chemical compounds offers a less laborious and safer strategy to drive cellular conversion for regenerative medicine. Nevertheless, identifying optimal chemical compounds currently requires large-scale screening of chemical libraries, which is resource intensive. Existing computational methods aim at predicting cell conversion TFs, but there are no methods for identifying chemical compounds targeting these TFs. Here, we develop a single cell-based platform (SiPer) to systematically prioritize chemical compounds targeting desired TFs to guide cellular conversions. SiPer integrates a large compendium of chemical perturbations on non-cancer cells with a network model and predicted known and novel chemical compounds in diverse cell conversion examples. Importantly, we applied SiPer to develop a highly efficient protocol for human hepatic maturation. Overall, SiPer provides a valuable resource to efficiently identify chemical compounds for cell conversion.
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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.