{
  "abstract": "Aging alters transcriptional regulation in a tissue- and time-specific manner, reshaping gene regulatory networks and shifting regulatory influence dynamics. Traditional in silico influence maximization methods often rely on static gene expression snapshots and fail to capture gene-to-gene influence variations over time. To address this, we introduce the Age Index, a network-based metric that quantifies time-varying gene influence. We define the Maximal and Minimal Age Index Problems (MAP\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{upgreek} \\usepackage{mathrsfs} \\setlength{\\oddsidemargin}{-69pt} \\begin{document} $^{+}$\\end{document} and MAP\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{upgreek} \\usepackage{mathrsfs} \\setlength{\\oddsidemargin}{-69pt} \\begin{document} $^{-}$\\end{document}) as the tasks of identifying gene sets with the highest and lowest Age Index, and prove these problems are NP-hard. To solve them, we develop MAGE (Maximal Age-Index Algorithm), a stochastic method that iteratively constructs gene sets by prioritizing genes likely to optimize the Age Index. MAGE identifies statistically significant gene sets at the genome scale, with strong literature support, highlighting its potential to uncover age-sensitive regulatory mechanisms.",
  "abstract_shown": true,
  "affiliations": [
    "Electronics Technology Programme, Electronics and Automation Department, Technical Sciences Vocational School, Bursa Uludağ University, Görükle Campus, Görükle Mahallesi, Üniversite 1. Cadde, No. 711G, Nilüfer, Bursa 16059, Türkiye.",
    "Department of Computer Engineering, Bursa Technical University, Bursa 16310, Türkiye.",
    "Department of Computer Science, University of Florida, Gainesville, FL 32611, United States.",
    "Department of Medical and Surgical Sciences, University of Catanzaro, Viale Europa, I-88100 Catanzaro, Italy.",
    "Department of Computer Engineering, Modelling, Electronic and Systems, University of Calabria, Via P Bucci, I-87036 Rende (CS), Italy."
  ],
  "article_type": "research article",
  "arxiv": null,
  "author_total": 6,
  "authors": [
    {
      "affs": [
        0
      ],
      "name": "Murat Çalış",
      "orcid": "0009-0002-2652-223X"
    },
    {
      "affs": [
        1
      ],
      "name": "Volkan Altuntas",
      "orcid": "0000-0003-3144-8724"
    },
    {
      "affs": [
        2
      ],
      "name": "Omer Kahveci"
    },
    {
      "affs": [
        3
      ],
      "name": "Pietro Hiram Guzzi",
      "orcid": "0000-0001-5542-2997"
    },
    {
      "affs": [
        4
      ],
      "name": "Pierangelo Veltri",
      "orcid": "0000-0003-2494-0294"
    },
    {
      "affs": [
        2
      ],
      "name": "Tamer Kahveci",
      "orcid": "0000-0002-4403-8612"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/0vnm78semm7ym.bib",
  "cited_by": 0,
  "doi": "10.1093/bib/bbag613",
  "fulltext_url": "https://europepmc.org/articles/PMC13725925",
  "id": "0vnm78semm7ym",
  "issns": [
    "1467-5463",
    "1477-4054"
  ],
  "landing_url": "https://europepmc.org/article/MED/42969857",
  "language": "eng",
  "licence": "CC-BY",
  "licence_label": "CC BY",
  "licence_source": "article",
  "licence_url": "https://creativecommons.org/licenses/by/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "heading",
      "AcademicSubjects/SCI01060"
    ],
    [
      "heading",
      "Problem Solving Protocol"
    ],
    [
      "openalex",
      "1312|Bioinformatics and Genomic Networks"
    ]
  ],
  "openalex": "W7225119010",
  "pdf_url": "https://europepmc.org/articles/PMC13725925?pdf=render",
  "pmcid": "PMC13725925",
  "pmid": "42969857",
  "published": "2026-11-01",
  "publisher": "Oxford University Press",
  "ris": "https://research.draconitic.com/paper/0vnm78semm7ym.ris",
  "sources": [
    {
      "first_seen": "2026-11-03T15:20:53Z",
      "native_id": "MED:42969857",
      "source": "europepmc",
      "url": "https://europepmc.org/article/MED/42969857"
    },
    {
      "first_seen": "2026-11-05T12:22:22Z",
      "native_id": "PMC13725925",
      "source": "pmc",
      "url": "https://doi.org/10.1093/bib/bbag613"
    }
  ],
  "subjects": [
    {
      "field": "biochemistry",
      "origin": "openalex:1312|Bioinformatics and Genomic Networks",
      "subfield": "molecular-biology"
    }
  ],
  "title": "MAGE: an efficient algorithm for identifying Maximal Age-indexed GEne sets.",
  "title_text": "MAGE: an efficient algorithm for identifying Maximal Age-indexed GEne sets.",
  "type": "peer-reviewed",
  "updated_at": "2026-11-06T12:22:00Z",
  "url": "https://research.draconitic.com/paper/0vnm78semm7ym",
  "venue": "Briefings in bioinformatics",
  "versions": []
}