ReviewCells2023
Transcriptome-Powered Pluripotent Stem Cell Differentiation for Regenerative Medicine.
Review in Cells, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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
11 citing papers in PubMed.
- Transcriptomic and functional comparison of adipose-and bone marrow-derived mesenchymal stem cells for tendon regeneration.Stem cell research & therapy · 2026Article
- Gene and Cell Therapy in Regenerative Medicine.Cells · 2026Article
- RNAa-Mediated Gene Activation in the Regulation of Stem Cell Fate.Biomolecules · 2025Review
- Neural crest-derived mesenchymal stem cells: Fates and perspectives.World journal of stem cells · 2025Review
- Transcriptomic Comparisons of Somatic and Cancer Stem Cells.Biomedicines · 2025Review
- Regenerating Locus Coeruleus-Norepinephrine (LC-NE) Function: A Novel Approach for Neurodegenerative Diseases.Cell proliferation · 2025Review
- Cell Seeding Strategy Influences Metabolism and Differentiation Potency of Human Induced Pluripotent Stem Cells Into Pancreatic Progenitors.Biotechnology journal · 2025Article
- Extracellular matrix proteins refine microenvironments for pancreatic organogenesis from induced pluripotent stem cell differentiation.Theranostics · 2025Article
- Isolation and tracing of matrix-producing notochordal and chondrocyte cells using ACAN-2A-mScarlet reporter human iPSC lines.Science advances · 2024Article
- Review
- Oxygenated Scaffolds for Pancreatic Endocrine Differentiation from Induced Pluripotent Stem Cells.Advanced healthcare materials · 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
2 authors.
Funding
Abstract
Pluripotent stem cells are endless sources for in vitro engineering human tissues for regenerative medicine. Extensive studies have demonstrated that transcription factors are the key to stem cell lineage commitment and differentiation efficacy. As the transcription factor profile varies depending on the cell type, global transcriptome analysis through RNA sequencing (RNAseq) has been a powerful tool for measuring and characterizing the success of stem cell differentiation. RNAseq has been utilized to comprehend how gene expression changes as cells differentiate and provide a guide to inducing cellular differentiation based on promoting the expression of specific genes. It has also been utilized to determine the specific cell type. This review highlights RNAseq techniques, tools for RNAseq data interpretation, RNAseq data analytic methods and their utilities, and transcriptomics-enabled human stem cell differentiation. In addition, the review outlines the potential benefits of the transcriptomics-aided discovery of intrinsic factors influencing stem cell lineage commitment, transcriptomics applied to disease physiology studies using patients' induced pluripotent stem cell (iPSC)-derived cells for regenerative medicine, and the future outlook on the technology and its implementation.
Indexed as
Identifiers
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.