ArticleHuman cell2021
Identification of an epigenetic signature in human induced pluripotent stem cells using a linear machine learning model.
Article in Human cell, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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The trial behind it
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Who cites it
13 citing papers in PubMed.
- Chondrogenic Differentiation of Stem Cells for Cartilage Regeneration: Advances and Future Perspectives.Tissue engineering and regenerative medicine · 2026Review
- Machine Learning in Stem Cell Research: From Biological Data to Clinical Translation.Computational and structural biotechnology journal · 2026Review
- Cell and tissue reprogramming: Unlocking a new era in medical drug discovery.Pharmacological reviews · 2025Review
- Stem Cell Therapy Approaches for Ischemia: Assessing Current Innovations and Future Directions.International journal of molecular sciences · 2025Review
- Review
- Epigenetic memory as crucial contributing factor in directing the differentiation of human iPSC into pancreatic β-cells in vitro.Cell and tissue research · 2025Review
- Supervised machine learning of outbred mouse genotypes to predict hepatic immunological tolerance of individuals.Scientific reports · 2024Article
- Recent Findings on Therapeutic Cancer Vaccines: An Updated Review.Biomolecules · 2024Review
- The use of artificial intelligence in induced pluripotent stem cell-based technology over 10-year period: A systematic scoping review.PloS one · 2024Article
- Advances in physiological and clinical relevance of hiPSC-derived brain models for precision medicine pipelines.Frontiers in cellular neuroscience · 2024Review
- Stem cell therapy for heart failure in the clinics: new perspectives in the era of precision medicine and artificial intelligence.Frontiers in physiology · 2023Review
- Machine Learning in Epigenomics: Insights into Cancer Biology and Medicine.Biochimica et biophysica acta. Reviews on cancer · 2021Review
- Recent trends in stem cell-based therapies and applications of artificial intelligence in regenerative medicine.World journal of stem cells · 2021Review
Corrections and comments
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Authors and funding
7 authors.
Funding
Abstract
The use of human induced pluripotent stem cells (iPSCs), used as an alternative to human embryonic stem cells (ESCs), is a potential solution to challenges, such as immune rejection, and does not involve the ethical issues concerning the use of ESCs in regenerative medicine, thereby enabling developments in biological research. However, comparative analyses from previous studies have not indicated any specific feature that distinguishes iPSCs from ESCs. Therefore, in this study, we established a linear classification-based learning model to distinguish among ESCs, iPSCs, embryonal carcinoma cells (ECCs), and somatic cells on the basis of their DNA methylation profiles. The highest accuracy achieved by the learned models in identifying the cell type was 94.23%. In addition, the epigenetic signature of iPSCs, which is distinct from that of ESCs, was identified by component analysis of the learned models. The iPSC-specific regions with methylation fluctuations were abundant on chromosomes 7, 8, 12, and 22. The method developed in this study can be utilized with comprehensive data and widely applied to many aspects of molecular biology research.
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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.