{
  "abstract": "Perturbational and pharmacogenomic maps remain incomplete across cellular contexts, leaving a practical source-selection question before response prediction: which measured context should inform an unmeasured target? We tested whether baseline transcriptomic similarity ranks candidate sources for held-out targets, separating source ranking from aggregation and transfer-uncertainty decisions. Similarity tracked matched-response concordance in LINCS and GSE306429; selected-source utility exceeded random expectation in GSE306429 ({Delta}U = 0.034; P = 0.002) and in exact-time-matched MIX-Seq tasks ({Delta}U = 0.046). In the full GDSC2 analysis, the drug-balanced ranking effect was 0.359 (95% CI, 0.337-0.383). In a lineage-restricted analysis of the same eligible subset, within-tissue ranking remained positive at 0.130 (95% CI, 0.119-0.141), retaining 35.8% of the same-subset global effect (0.363; 95% CI, 0.342-0.386). Global transcriptomic top-1 selection exceeded tissue-matched random selection by 0.154 (95% CI, 0.143-0.164). Thus, baseline similarity adds source-ranking information after tissue matching in the evaluated setting, while ranking alone does not resolve whether to aggregate sources or how to quantify transfer uncertainty.",
  "abstract_shown": true,
  "affiliations": [
    "Institute of Clinical Medical Sciences, China-Japan Friendship Hospital"
  ],
  "article_type": "New results",
  "arxiv": null,
  "author_total": 6,
  "authors": [
    {
      "name": "L. Jiang"
    },
    {
      "name": "J. Pang"
    },
    {
      "name": "B. Luo"
    },
    {
      "name": "X. Wu"
    },
    {
      "name": "X. Li"
    },
    {
      "affs": [
        0
      ],
      "name": "H. Zhang"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/bzdersydn0jqn.bib",
  "cited_by": 0,
  "doi": "10.64898/2026.10.26.761823",
  "fulltext_url": "https://www.biorxiv.org/content/10.64898/2026.10.26.761823v1.full",
  "id": "bzdersydn0jqn",
  "issns": [],
  "landing_url": "https://www.biorxiv.org/content/10.64898/2026.10.26.761823v1",
  "language": null,
  "licence": "CC-BY-NC-ND",
  "licence_label": "CC BY-NC-ND",
  "licence_source": "article",
  "licence_url": "https://creativecommons.org/licenses/by-nc-nd/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "biorxiv",
      "bioinformatics"
    ]
  ],
  "openalex": null,
  "pdf_url": "https://www.biorxiv.org/content/10.64898/2026.10.26.761823v1.full.pdf",
  "pmcid": null,
  "pmid": null,
  "published": "2026-10-26",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/bzdersydn0jqn.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:30:27Z",
      "native_id": "10.64898/2026.10.26.761823",
      "source": "biorxiv",
      "url": "https://www.biorxiv.org/content/10.64898/2026.10.26.761823v1"
    }
  ],
  "subjects": [
    {
      "field": "biology",
      "origin": "biorxiv:bioinformatics",
      "subfield": "bioinformatics"
    }
  ],
  "title": "Transcriptomic similarity guides source selection beyond tissue lineage",
  "title_text": "Transcriptomic similarity guides source selection beyond tissue lineage",
  "type": "preprint",
  "updated_at": "2026-10-31T00:20:47Z",
  "url": "https://research.draconitic.com/paper/bzdersydn0jqn",
  "venue": "bioRxiv",
  "versions": []
}