ArticleAnnual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference2022
Identifying Transient Cells During Reprogramming via Persistent Homology.
Article in Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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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.
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Who cites it
1 citing paper in PubMed, 1 citations in OpenAlex.
- Topological data analysis in single cell biology.Frontiers in immunology · 2025Review
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Authors and funding
4 authors at 1 institution in 1 country.
Funding
Abstract
Single-cell RNA sequencing is a powerful method that helps delineate the regulatory mechanisms shaping the diverse cellular populations. Heterogeneous cell populations consist of individual cells, and the expression of distinct sets of genes can differentiate one sub-population of cells from another, as they are responsible for the emergence of distinct cellular phenotypes. Of particular importance are cells at transition states that bridge these different cellular phenotypes. In this study, we develop a method to identify the cells at transition states bridging different cellular phenotypes. Our approach is based on persistent homology, which enabled us to identify the group of cells located on the boundaries between different sub-populations of cells. We applied this method to study the reprogramming of human fibroblasts toward induced pluripotent stem cells using single-cell time-course data. Even though only the data that is representative of the early stages of the reprogramming process are analyzed, we are able to uncover transient cells bridging different cell sub-populations. The most prominent group of transient cells are found to be enriched for NANOG, which is a known stem cell transcription factor that takes part in the maintenance of pluripotency and other stem cell marker genes. Overall, our method can identify cells in transient states bridging major cellular phenotypes, even though they are only a small fraction of the overall cell population. We also discuss how this approach can link the topology of the surface of cellular transcripts and bring order to the transition between cellular states and how it automatically uncovers the underlying time process.
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