ReviewBioinformatics (Oxford, England)2025
Decoding cell fate: integrated experimental and computational analysis at the single-cell level.
Review in Bioinformatics (Oxford, England), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 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
2 citing papers in PubMed.
- Cardiac EndMT and EpiMT as a developmental continuum: integration of mechanical, metabolic, and epigenetic regulation.Frontiers in cell and developmental biology · 2026Review
- Mechanical forces orchestrate the epigenetic landscape of oral mesenchymal stem/progenitor cell fate in dental and periodontal tissues.Frontiers in cell and developmental biology · 2026Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
Abstract
motivationUnderstanding cell fate determination is crucial in developmental biology and regenerative medicine. Although theoretical frameworks such as epigenetic landscape and gene regulatory networks have been proposed for decades, traditional studies have often been limited by population-averaging and low-throughput techniques, which obscure the heterogeneity of individual cells and fail to provide a systematic view of cell fate control. Recent advances in single-cell technologies have provided unprecedented resolution, revealing the complexity of cell fate decisions and driving the need for more sophisticated computational methods.
resultsIn this review, we first emphasize experimental advances, such as single-cell multi-omics, lineage tracing, and perturbation techniques, which produce novel data modalities and enable dynamic tracking of cell fate transitions. We then discuss the modeling paradigms for cell fate studies and further assess the role of emerging AI tools in perturbation modeling and discuss the potential of single-cell and spatial foundation models. Additionally, we highlight several case studies on predicting and manipulating cell fates, and discuss key challenges and future directions of the field. AVAILABILITY AND IMPLEMENTATION: This work generates no new software.
Indexed as
Identifiers
What Socratic 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 Socratic graph.