EVLncRNAs 4.0: an updated database of experimentally validated functional long non-coding RNAs with evidence-grounded AI access

Long non-coding RNAs (lncRNAs) have diverse biological functions, but experimentally validated evidence remains scattered across the literature and is often context dependent. EVLncRNAs 4.0 (https://www.sdklab-biophysics-dzu.net/EVLncRNAs4/) updates our manually curated database of functional lncRNAs supported by low-throughput experiments. For this release, 16 581 publications indexed between 15 May 2023 and 15 May 2026 were retrieved and manually screened. Compared with EVLncRNAs 3.0, EVLncRNAs 4.0 contains 7808 functional lncRNAs (+26%) from 199 species (+23%), 2313 diseases (+34%), 28 757 curated functional records (+21%), and 18 380 molecular interactions (+25%). EVLncRNAs 4.0 also introduces two AI-assisted functions built on the curated evidence base. AI Search uses an enhanced retrieval-augmented generation framework with adaptive selection across Quick, Expanded, and Exhaustive retrieval modes and generates answers from retrieved EVLncRNAs records with PMID-linked citations. Benchmark evaluation showed complete request execution, high retrieval coverage and full citation validity within the supplied evidence context. Functional Overview retrieves and aggregates lncRNA- and species-specific curated records before generating concise evidence-based summaries. In both functions, language models synthesize retrieved evidence rather than serve as independent sources of biological knowledge. EVLncRNAs 4.0 therefore provides an expanded, experimentally grounded resource for accessing and interpreting functional lncRNA evidence across species and biological contexts.

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Publication Details

Journal
Nucleic Acids Research
Published
2026-10-31
DOI
https://doi.org/10.1093/nar/gkag1111
Primary Topic
Cancer-related molecular mechanisms research
Type
article
Field-Weighted Citation Impact
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article

EVLncRNAs 4.0: an updated database of experimentally validated functional long non-coding RNAs with evidence-grounded AI access

Xianghua Dou, Yuedong Yang, Qiangcheng Zeng, Huiying Zhao et al.
Nucleic Acids Research
Cancer-related molecular mechanisms research
article

EVLncRNAs 4.0: an updated database of experimentally validated functional long non-coding RNAs with evidence-grounded AI access

Xianghua Dou, Yuedong Yang, Qiangcheng Zeng, Huiying Zhao, Yaoqi Zhou, 季葆华, Zhenghua LI, Bailing Zhou, Xue Yu, Chunjie Liu, Shuo Yang, Shicai Xu, Zanxia Cao, Li Kong, Jihua Wang, Pingping Huang, Xia Zhang, Zhiwei Li
article en

Abstract

Long non-coding RNAs (lncRNAs) have diverse biological functions, but experimentally validated evidence remains scattered across the literature and is often context dependent. EVLncRNAs 4.0 (https://www.sdklab-biophysics-dzu.net/EVLncRNAs4/) updates our manually curated database of functional lncRNAs supported by low-throughput experiments. For this release, 16 581 publications indexed between 15 May 2023 and 15 May 2026 were retrieved and manually screened. Compared with EVLncRNAs 3.0, EVLncRNAs 4.0 contains 7808 functional lncRNAs (+26%) from 199 species (+23%), 2313 diseases (+34%), 28 757 curated functional records (+21%), and 18 380 molecular interactions (+25%). EVLncRNAs 4.0 also introduces two AI-assisted functions built on the curated evidence base. AI Search uses an enhanced retrieval-augmented generation framework with adaptive selection across Quick, Expanded, and Exhaustive retrieval modes and generates answers from retrieved EVLncRNAs records with PMID-linked citations. Benchmark evaluation showed complete request execution, high retrieval coverage and full citation validity within the supplied evidence context. Functional Overview retrieves and aggregates lncRNA- and species-specific curated records before generating concise evidence-based summaries. In both functions, language models synthesize retrieved evidence rather than serve as independent sources of biological knowledge. EVLncRNAs 4.0 therefore provides an expanded, experimentally grounded resource for accessing and interpreting functional lncRNA evidence across species and biological contexts.

Nucleic Acids Research
Sun Yat-sen University (CN), State Intellectual Property Office (CN), Sun Yat-sen Memorial Hospital (CN), Shenzhen Bay Laboratory (CN), Dezhou University (CN)
Openalex Percentile: Top 16%
Cancer-related molecular mechanisms research
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