Evidence map›Paper›PMID 38040715›Full record

ArticleScientific data2023

HALD, a human aging and longevity knowledge graph for precision gerontology and geroscience analyses.

Zexu Wu, Cong Feng, Yanshi Hu, Yincong Zhou, Sida Li, Shilong Zhang, Yueming Hu, Yuhao Chen, Haoyu Chao, Qingyang Ni and 1 more

Open access · goldAbstract readDataset
In one paragraph

Article in Scientific data, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
2.2field-weighted citation impact, top 11% of its field
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed, 7 citations in OpenAlex.

  1. Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors at 3 institutions in 1 country.

Zexu Wu *Department of Bioinformatics, College of Life Sciences, Zhejiang University, Hangzhou, 310058, China.
Cong Feng *Department of Bioinformatics, College of Life Sciences, Zhejiang University, Hangzhou, 310058, China.
Yanshi HuDepartment of Bioinformatics, College of Life Sciences, Zhejiang University, Hangzhou, 310058, China.ORCID 0000-0003-3219-3778
Yincong ZhouDepartment of Bioinformatics, College of Life Sciences, Zhejiang University, Hangzhou, 310058, China.
Sida LiDepartment of Bioinformatics, College of Life Sciences, Zhejiang University, Hangzhou, 310058, China.
Shilong ZhangDepartment of Bioinformatics, College of Life Sciences, Zhejiang University, Hangzhou, 310058, China.
Yueming HuDepartment of Bioinformatics, College of Life Sciences, Zhejiang University, Hangzhou, 310058, China.
Yuhao ChenDepartment of Bioinformatics, College of Life Sciences, Zhejiang University, Hangzhou, 310058, China.
Haoyu ChaoDepartment of Bioinformatics, College of Life Sciences, Zhejiang University, Hangzhou, 310058, China.
Qingyang NiDepartment of Bioinformatics, College of Life Sciences, Zhejiang University, Hangzhou, 310058, China.
Ming ChenDepartment of Bioinformatics, College of Life Sciences, Zhejiang University, Hangzhou, 310058, China. mchen@zju.edu.cn.
Zhejiang University · CNZhejiang University-University of Edinburgh Institute · CNFirst Affiliated Hospital Zhejiang University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Human aging is a natural and inevitable biological process that leads to an increased risk of aging-related diseases. Developing anti-aging therapies for aging-related diseases requires a comprehensive understanding of the mechanisms and effects of aging and longevity from a multi-modal and multi-faceted perspective. However, most of the relevant knowledge is scattered in the biomedical literature, the volume of which reached 36 million in PubMed. Here, we presented HALD, a text mining-based human aging and longevity dataset of the biomedical knowledge graph from all published literature related to human aging and longevity in PubMed. HALD integrated multiple state-of-the-art natural language processing (NLP) techniques to improve the accuracy and coverage of the knowledge graph for precision gerontology and geroscience analyses. Up to September 2023, HALD had contained 12,227 entities in 10 types (gene, RNA, protein, carbohydrate, lipid, peptide, pharmaceutical preparations, toxin, mutation, and disease), 115,522 relations, 1,855 aging biomarkers, and 525 longevity biomarkers from 339,918 biomedical articles in PubMed. HALD is available at https://bis.zju.edu.cn/hald .

Indexed as

AgingGeriatricsLongevityBiomarkersGeroscienceHumansPattern Recognition, AutomatedBiomarkers

Identifiers

PMID38040715
PMCPMC10692171
OpenAlexW4389224442

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.