ReviewBiomolecules2025
Advances in Computational Drug Repurposing, Driver Genes, and Therapeutics in Lung Adenocarcinoma.
Review in Biomolecules, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
- AI-Driven Combination Therapy for Counteracting Dysregulated Genes in Lung Adenocarcinoma: Contribution-Aware Metaheuristic for Drug Repurposing.Pharmaceuticals (Basel, Switzerland) · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
This review catalogs candidate LUAD driver genes and their roles, recent discoveries, and therapeutic avenues. Beyond experimental repurposing, we evaluate modern computational methods and how they complement bench work. We conclude by appraising recent LUAD repurposing studies through a computational lens, emphasizing practical integration into translational research. Highlights: Overview of drug repurposing methods: We provide a list of six experimental and a brief taxonomy of eight computational drug repurposing method families. Recent insights into LUAD driver genes: We present a curated panel of LUAD drivers mapped to pathways, with alteration types, functions, and therapeutic implications. LUAD-focused computational repurposing studies: We provide a synthesis of recent LUAD studies presenting clear method families, highlighting exemplar pipelines, prioritized candidate drugs, and datasets.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.