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Genomics Proteomics & BioinformaticsBioinformaticsPeer-reviewed journal article

MTB-KB: A Curated Knowledgebase of Mycobacterium tuberculosis Related Studies

Pan Li, Cuidan LiiD, Rongxi Zhu, Wenjing Sun, Hengyu ZhouiD, Zhuojing FaniD, Liya YueiD, Sijia ZhangiD, Xiaoyuan JiangiD, Quan LuoiD, Jinying HaniD, Hairong Huang, Adong SheniD, Bahetibieke TuohetaerbaikeiD, Jing WangiD, Wenbao ZhangiD, Hao WeniD, Haitao NiuiD, Congfan BuiD, Zhang ZhangiD, Jingfa XiaoiD, Renjun GaoiD, Fei CheniD

PDFDOIPreprint

Abstract

Tuberculosis (TB), caused by Mycobacterium tuberculosis (MTB), has regained its position as the worlds leading killer among infectious diseases. Despite extensive research progress across epidemiology, diagnosis, drug development, treatment regimens, vaccines, drug resistance, virulence factors, and immune mechanisms, MTB-related knowledge remains fragmented across thousands of publications, limiting its effective use. To address this gap, we present MTB-KB, a literature-curated knowledgebase that systematically integrates high-impact findings from eight major sections of TB research. The current release contains 75,170 associations from 1,246 publications, covering 18,439 entities standardized using authoritative databases and WHO-endorsed classifications. A central feature is the interactive knowledge graph, which links cross-section associations to reveal and infer MTB-host interactions, treatment strategies, and vaccine development opportunities. MTB-KB also provides a user-friendly interface with browsing, advanced search, and statistical visualization. Overall, by consolidating dispersed MTB knowledge into a structured and accessible platform, MTB-KB provides a valuable resource for researchers, clinicians, and policymakers, supporting both basic and clinical TB research, enabling evidence-based TB prevention, diagnosis, and treatment, and contributing to global elimination efforts. MTB-KB is accessible at https://ngdc.cncb.ac.cn/mtbkb/.

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