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. 2018 Jan 11;8:546. doi: 10.1038/s41598-017-18699-8

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© The Author(s) 2018

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

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Developing a bioinformatic and systematic literature review for defining proteomes. The entire body of Web of Science literature was searched. A series of terms were used to select a smaller population of publications of interest and the abstract text for each paper was then downloaded (a–d). A Perl algorithm was developed to search the downloaded abstract text for: at least one protein name as stated in Uniprot, “skin,” “Immunohistochem*”, and/or “Mass Spec*” (e) and created an Excel file with the list of DOIs with the contained terms (f). The papers in the Excel list were then manually reviewed for evidence (IHC, MS, ELISA, WB or zymography) of the protein in healthy human skin (g). Proteins were added to the database with captured data on: protein name, accession number, and gene name (from Uniprot) and; from target articles: skin sample information (age, sex, and anatomical site), localisation within the tissue and any associated pathologies.