CBFLivUni/AdenomyosisGeoMX: Publication

Johnson, Emily Jane
2025 · doi:10.5281/zenodo.15642732 · W6949811365
Other OA: green CC0
🔓 Open OA copy Full text JSON View on OpenAlex View at publisher
⚙ AI-generated summary by qwen3.7-flash, 2026-09-10 ⓘ

This publication details the code and figures for a study using spatially-resolved transcriptomics to uncover the hybrid molecular identity, ciliated phenotype, and immune signature of adenomyosis lesions.

One-sentence paraphrase of the abstract; not a substitute for reading it. No clinical advice. How this works

⚙ AI-generated deep summary by qwen3.7-flash, 2026-09-07 · read from full text ⓘ

This publication provides the computational code and data used to analyze spatially-resolved transcriptomics for adenomyosis lesions. The associated research investigates the hybrid molecular identity, ciliated phenotype, and immune signature within these specific uterine tissues. By making the analysis tools public, the authors support reproducibility in studying the complex cellular environment of adenomyotic tissue. This paper is centrally about adenomyosis — specifically focusing on the molecular and immune characterization of adenomyosis lesions using spatial transcriptomics.

Read from the paper's body, not the abstract. Not a substitute for reading the paper. No clinical advice. How this works

Abstract

Code used to perform the analysis and generate figures for the associated publication - Spatially-resolved transcriptomics uncovers the hybrid molecular identify, ciliated phenotype, and immune signature of adenomyosis lesions".
Full text 579 characters · extracted from oa-doi-fallback · click to expand
Published June 11, 2025 | Version v1 Software CBFLivUni/AdenomyosisGeoMX: Publication Authors/Creators - 1. Computational Biology Facility, Liverpool Shared Research Facilities, University of Liverpool, Liverpool L69 7ZB, United Kingdom Description Code and data used to perform the analysis and generate figures for the associated publication - Spatially-resolved transcriptomics uncovers the hybrid molecular identify, ciliated phenotype, and immune signature of adenomyosis lesions". Additional details Software - Repository URL - https://github.com/CBFLivUni/AdenomyosisGeoMX

Text is read by the "Ask this paper" AI Q&A widget below. Extraction quality varies by source — PMC NXML preserves structure cleanly, OA-HTML may include some navigation residue, and OA-PDF can have broken hyphenation. The publisher copy (via DOI) is the canonical version.

My notes (saved in your browser only)

⚙ Ask this paper AI returns verbatim quotes from the full text · source: oa-doi-fallback ⓘ

Answers must be backed by verbatim quotes from this paper's full text. Hallucinated quotes are dropped automatically; if no verbatim passage answers the question, we say so. How this works

Condition tags

adenomyosis

Citation neighborhood (no data yet)

We don't have any in-corpus citations linked to this paper yet. This is a recent paper (2025) — citers typically take a year or two to land, and the OpenAlex reference graph may still be filling in.

Source provenance

openalex
last seen: 2026-05-10T10:34:34.680553+00:00
License: CC0 · commercial use OK