Human Prolactinoma: A View of Protein-Protein Interaction Pattern.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:30464775", "kind": "science-record", "revision": 9, "content_hash": "sha256:e6f8cf2c875d6c01424274a80c51b35678242011093a3e7aaa790b54efda895b", "created_at": "2026-11-01T15:40:39Z", "updated_at": "2026-11-01T22:43:38Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Human Prolactinoma: A View of Protein-Protein Interaction Pattern.", "doi": "10.5812/ijem.67332", "pmid": "30464775", "authors": ["Mona Zamanian Azodi", "Majid Rezaei-Tavirani", "Mohammad Rostami Nejad", "Mostafa Rezaei-Tavirani"], "journal": "International journal of endocrinology and metabolism", "year": 2018, "abstract": "The aim of this study was to identify the highly expressed genes in terms of interaction concept in Prolactinoma. The study was conducted by additional analysis of the available data from the GEO database. The online tool, GEO2R, was used to analyze the gene expression profile of GSE36314 dataset using the GPL8300 platform. Consequently, a PPI network of up-regulated and down-regulated genes was constructed and examined to introduce the possible targets with possible therapeutic values. A number of 46 genes were dysregulated in Prolactinoma and their network indicated 15 essential genes via topological analysis. Moreover, the present study found that the highlighted genes of prolactinoma are involved in two major biological processes including growth regulation and metabolic function. Thus, the determined genes may be valuable for diagnosis, treatment, and patient follow-up. However, further studies are essential to validate this conclusion.", "claims": [{"id": "claim-method", "statement": "Similarly, the GEO2R provides a specific R formula for conducting the analysis in the R Studio environment using GEO query and limma R packages from the Bioconductor project (14).", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:30464775", "locator": "sections[2] \"2. 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