{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,20]],"date-time":"2025-11-20T17:22:20Z","timestamp":1763659340541,"version":"3.45.0"},"reference-count":10,"publisher":"Oxford University Press (OUP)","issue":"1","license":[{"start":{"date-parts":[[2025,10,31]],"date-time":"2025-10-31T00:00:00Z","timestamp":1761868800000},"content-version":"vor","delay-in-days":309,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Next Generation EU\u2014Italian NRRP"},{"name":"PNRR"},{"name":"FAIR\u2014Future AI Research","award":["PE00000013"],"award-info":[{"award-number":["PE00000013"]}]},{"DOI":"10.13039\/100031478","name":"NextGenerationEU","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100031478","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2024,12,26]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Motivation<\/jats:title>\n                    <jats:p>A comprehensive and in-depth deciphering of the dynamics concerning gene expressions is essential for understanding intricate biological mechanisms; for instance, the latter can be effectively addressed via network science, and Gene Co-expression Networks (GCNs), specifically. However, a typical GCN is based on a static model, which limits the ability to reflect changes that occur over time. To overcome this issue, we designed an open-source user-friendly web-service for constructing temporal networks from genotype-tissue expression data: COnstructing Real-world TEmporal networks (CoRTE).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>CoRTE bases the construction of a temporal network on the statistical analysis of the related gene co-expressions across successive age ranges, to define an ordered set of time points. In our experimentation we investigated gene co-expression dynamics across age groups in brain tissues associated with Alzheimer\u2019s Disease, processing curated aging-related data via the proposed web-service. The latter has effectively generated the temporal network consisting of a set of gene pairs that showed statistically significant co-expressions over time. Results demonstrated its capacity to capture time-dependent gene interactions relevant for aging-related disease progression. From a purely applicative point of view, CoRTE may be particularly suitable for exploring aging-related changes, disease development, and other time-dependent biological events.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Availability and implementation<\/jats:title>\n                    <jats:p>CoRTE is freely available at https:\/\/github.com\/pietrocinaglia\/corte-ws.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1093\/bioadv\/vbaf272","type":"journal-article","created":{"date-parts":[[2025,10,28]],"date-time":"2025-10-28T12:54:25Z","timestamp":1761656065000},"source":"Crossref","is-referenced-by-count":0,"title":["CoRTE: a web-service for constructing temporal networks from genotype-tissue expression data"],"prefix":"10.1093","volume":"5","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2237-6984","authenticated-orcid":false,"given":"Pietro","family":"Cinaglia","sequence":"first","affiliation":[{"name":"Department of Health Sciences, Magna Graecia University , Catanzaro, 88100,","place":["Italy"]},{"name":"Data Analytics Research Center, Magna Graecia University , Catanzaro, 88100,","place":["Italy"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1502-2387","authenticated-orcid":false,"given":"Mario","family":"Cannataro","sequence":"additional","affiliation":[{"name":"Data Analytics Research Center, Magna Graecia University , Catanzaro, 88100,","place":["Italy"]},{"name":"Department of Medical and Surgical Sciences, Magna Graecia University , Catanzaro, 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seedlings can reveal novel regulatory relationships","volume":"11","author":"Cortijo","year":"2020","journal-title":"Front Plant Sci"},{"key":"2025112012183009200_vbaf272-B4","doi-asserted-by":"crossref","first-page":"235","DOI":"10.1186\/s12864-025-11433-z","article-title":"Time-course transcriptome analysis reveals gene co-expression networks and transposable element responses to cold stress in cotton","volume":"26","author":"Dai","year":"2025","journal-title":"BMC Genomics"},{"key":"2025112012183009200_vbaf272-B5","doi-asserted-by":"crossref","first-page":"580","DOI":"10.1038\/ng.2653","article-title":"The Genotype-Tissue expression (GTEx) project","volume":"45","author":"GTEx Consortium","year":"2013","journal-title":"Nat Genet"},{"key":"2025112012183009200_vbaf272-B6","doi-asserted-by":"crossref","first-page":"81","DOI":"10.1186\/s12859-022-04609-x","article-title":"Distance correlation application to gene co-expression network analysis","volume":"23","author":"Hou","year":"2022","journal-title":"BMC Bioinformatics"},{"key":"2025112012183009200_vbaf272-B7","doi-asserted-by":"crossref","first-page":"1064","DOI":"10.1080\/02664763.2019.1667311","article-title":"TGCnA: temporal gene coexpression network analysis using a low-rank plus sparse framework","volume":"47","author":"Li","year":"2020","journal-title":"J Appl Stat"},{"key":"2025112012183009200_vbaf272-B8","doi-asserted-by":"crossref","first-page":"196","DOI":"10.14283\/jpad.2023.101","article-title":"Alzheimer\u2019s disease and aging association: identification and validation of related genes","volume":"11","author":"Liu","year":"2024","journal-title":"J Prev Alzheimers Dis"},{"key":"2025112012183009200_vbaf272-B9","doi-asserted-by":"crossref","first-page":"695399","DOI":"10.3389\/fgene.2021.695399","article-title":"Comparative analyses of gene co-expression networks: implementations and applications in the study of evolution","volume":"12","author":"Ovens","year":"2021","journal-title":"Front Genet"},{"key":"2025112012183009200_vbaf272-B10","doi-asserted-by":"crossref","first-page":"764","DOI":"10.1093\/bioinformatics\/btw729","article-title":"LEAP: constructing gene co-expression networks for single-cell RNA-sequencing data using pseudotime ordering","volume":"33","author":"Specht","year":"2017","journal-title":"Bioinformatics"}],"container-title":["Bioinformatics 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