ArticleStem cell reports2021
Automatic identification of small molecules that promote cell conversion and reprogramming.
Article in Stem cell reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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Who cites it
17 citing papers in PubMed.
- 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
- Cell and tissue reprogramming: Unlocking a new era in medical drug discovery.Pharmacological reviews · 2025Review
- Refate identifies chemical compounds to target trans-regulatory networks for cellular conversion.bioRxiv : the preprint server for biology · 2025Article
- Assisted Reproductive Technology: A Ray of Hope for Infertility.ACS omega · 2025Review
- AI identifies potent inducers of breast cancer stem cell differentiation based on adversarial learning from gene expression data.Briefings in bioinformatics · 2024Article
- DIRECTEUR: transcriptome-based prediction of small molecules that replace transcription factors for direct cell conversion.Bioinformatics (Oxford, England) · 2024Article
- iPSC-derived cells for whole liver bioengineering.Frontiers in bioengineering and biotechnology · 2024Review
- Chemical Transdifferentiation of Somatic Cells: Unleashing the Power of Small Molecules.Biomedicines · 2023Review
- PC3T: a signature-driven predictor of chemical compounds for cellular transition.Communications biology · 2023Article
- Pluripotent Stem Cells of Order Carnivora: Technical Perspective.International journal of molecular sciences · 2023Review
- A single cell-based computational platform to identify chemical compounds targeting desired sets of transcription factors for cellular conversion.Stem cell reports · 2023Article
- ChemPert: mapping between chemical perturbation and transcriptional response for non-cancer cells.Nucleic acids research · 2023Article
- Microfluidics for Neuronal Cell and Circuit Engineering.Chemical reviews · 2022Review
- Computational approaches for direct cell reprogramming: from the bulk omics era to the single cell era.Briefings in functional genomics · 2022Article
- Determination of protoplast growth properties using quantitative single-cell tracking analysis.Plant methods · 2022Article
- Automatic identification of small molecules that promote cell conversion and reprogramming.Stem cell reports · 2021Article
Corrections and comments
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Authors and funding
15 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Controlling cell fate has great potential for regenerative medicine, drug discovery, and basic research. Although transcription factors are able to promote cell reprogramming and transdifferentiation, methods based on their upregulation often show low efficiency. Small molecules that can facilitate conversion between cell types can ameliorate this problem working through safe, rapid, and reversible mechanisms. Here, we present DECCODE, an unbiased computational method for identification of such molecules based on transcriptional data. DECCODE matches a large collection of drug-induced profiles for drug treatments against a large dataset of primary cell transcriptional profiles to identify drugs that either alone or in combination enhance cell reprogramming and cell conversion. Extensive validation in the context of human induced pluripotent stem cells shows that DECCODE is able to prioritize drugs and drug combinations enhancing cell reprogramming. We also provide predictions for cell conversion with single drugs and drug combinations for 145 different cell types.
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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.