Evidence map›Paper›PMID 41542086›Full record

ArticleComputational and structural biotechnology journal2025

KDASDB: A comprehensive and user-friendly database of alternative splicing dedicated to kidney diseases.

Yalan Kuang, Yilong Chen, Yongsan Yang, Zhiye Ying, Yonghong Gu, Lina Yang, Ruiye Bi, Xiaoxi Zeng, Haopeng Yu

Abstract read
In one paragraph

Article in Computational and structural biotechnology journal, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

9 authors.

Yalan KuangWest China Biomedical Big Data Center, West China Hospital, Sichuan University, Chengdu, Sichuan 610041, China.
Yilong ChenWest China Biomedical Big Data Center, West China Hospital, Sichuan University, Chengdu, Sichuan 610041, China.
Yongsan YangWest China Biomedical Big Data Center, West China Hospital, Sichuan University, Chengdu, Sichuan 610041, China.
Zhiye YingWest China Biomedical Big Data Center, West China Hospital, Sichuan University, Chengdu, Sichuan 610041, China.
Yonghong GuWest China Biomedical Big Data Center, West China Hospital, Sichuan University, Chengdu, Sichuan 610041, China.
Lina YangDepartment of Nephrology, Institute of Kidney Diseases, West China Hospital of Sichuan University, Chengdu 610041, China.
Ruiye BiState Key Laboratory of Oral Diseases, National Clinical Research Center for Oral Diseases, Department of Orthognathic and TMJ Surgery, West China Hospital of Stomatology, Sichuan University, Chengdu 610041, China.
Xiaoxi ZengWest China Biomedical Big Data Center, West China Hospital, Sichuan University, Chengdu, Sichuan 610041, China.
Haopeng YuWest China Biomedical Big Data Center, West China Hospital, Sichuan University, Chengdu, Sichuan 610041, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Kidney disease has long been a major public health concern, making it crucial to understand its causes, pathogenesis and progression for the development of effective prevention and treatment strategies. Alternative splicing (AS), an important post-transcriptional regulatory mechanism, has been increasingly recognized for its pivotal role in the pathogenesis and progression of kidney diseases. However, a dedicated database that systematically catalog AS events associated with kidney diseases is still lacking. In this study, we developed the Kidney Diseases Alternative Splicing Database (KDASDB, http://www.hxdsjzx.cn/KDASDB), which integrates 90,273 alternative splicing events (ASEs) derived from 2406 samples, encompassing 29 distinct kidney diseases and 126 projects across human and mouse. The database features 52,478 and 41,818 novel transcripts in human and mouse datasets, respectively, and identifies 3354 and 5638 novel ASEs. KDASDB offers intuitive query and visualization tools, enabling researchers to efficiently explore AS patterns and assess their biological significance. By providing comprehensive repository of ASEs and their associations with kidney diseases, KDASDB serves as a valuable platform for advancing our understanding of kidney disease pathogenesis and progression, and supporting the discovery of innovative therapeutic approaches.

Indexed as

Alternative splicingDatabaseKidney diseases

Identifiers

PMID41542086
PMCPMC12800380

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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.