{"entity": "publication", "iuid": "9a97e601ca394ffbbd87361ddaadab5f", "timestamp": "2026-09-01T08:31:28.794Z", "links": {"self": {"href": "https://publications-affiliated.scilifelab.se/publication/9a97e601ca394ffbbd87361ddaadab5f.json"}, "display": {"href": "https://publications-affiliated.scilifelab.se/publication/9a97e601ca394ffbbd87361ddaadab5f"}}, "title": "Spage2vec: Unsupervised representation of localized spatial gene expression signatures.", "authors": [{"family": "Partel", "given": "Gabriele", "initials": "G", "orcid": "0000-0002-4482-3119", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/d2d38e59d5c840a0a53a4b90690fdc7a.json"}}, {"family": "W\u00e4hlby", "given": "Carolina", "initials": "C", "orcid": "0000-0002-4139-7003", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/833afe3444d84c24be12ea1468563bea.json"}}], "type": "journal article", "published": "2021-03-00", "journal": {"title": "FEBS J.", "issn": "1742-4658", "volume": "288", "issue": "6", "pages": "1859-1870", "issn-l": "1742-464X"}, "abstract": "Investigations of spatial cellular composition of tissue architectures revealed by multiplexed in situ RNA detection often rely on inaccurate cell segmentation or prior biological knowledge from complementary single-cell sequencing experiments. Here, we present spage2vec, an unsupervised segmentation-free approach for decrypting the spatial transcriptomic heterogeneity of complex tissues at subcellular resolution. Spage2vec represents the spatial transcriptomic landscape of tissue samples as a graph and leverages a powerful machine learning graph representation technique to create a lower dimensional representation of local spatial gene expression. We apply spage2vec to mouse brain data from three different in situ transcriptomic assays and to a spatial gene expression dataset consisting of hundreds of individual cells. We show that learned representations encode meaningful biological spatial information of re-occurring localized gene expression signatures involved in cellular and subcellular processes. DATABASE: Spatial gene expression data are available in Zenodo database at https://doi.org/10.5281/zenodo.3897401. Source code for reproducing analysis results and figures is available in Zenodo database at http://www.doi.org/10.5281/zenodo.4030404.", "doi": "10.1111/febs.15572", "pmid": "32976679", "labels": [], "xrefs": [{"db": "pmc", "key": "PMC7983892"}], "notes": [], "created": "2026-08-20T11:18:03.786Z", "modified": "2026-08-20T11:18:03.816Z"}