IMicAP: an intelligent microbial application platform for knowledge-driven microbiome research
4 affiliations
- 1Intelligence Medicine Institute, Fudan University , ,
- 2Shanghai Lishan Biotech Co., Ltd. , ,
- 3Center for Gut Microbiome, Metabolism and Immunity, Shanxi Bethune Hospital, Shanxi Academy of Medical Sciences, Tongji Shanxi Hospital, Third Hospital of Shanxi Medical University , ,
- 4Avon Old Farms School , , ,
Abstract
Background: Microorganisms play a pivotal role in health and disease, yet microbial research is hindered by fragmented data, heterogeneous knowledge representation, and a lack of integrated analytical tools. Existing databases and knowledge graphs often focus narrowly on genomic information, leaving critical metabolomic and literature-based associations underdeveloped.
Results: We developed the Intelligent Microbial Application Platform (IMicAP), an AI-driven, open-access web platform that integrates 12 microbial databases and over 35 million articles. IMicAP delivers 5 core modules: (1) Knowledge Query module for rapid data retrieval; (2) Knowledge Graph module for multi-hop reasoning and hypothesis generation; (3) Intelligent Question-Answering module for professional natural language dialogue in the field of microbiology; (4) Genome Browser module for genomic visualization; and (5) 16S rRNA Sequencing Analysis module for zero-code microbial bioinformatics analysis. Using curated microbe-disease and microbe-small molecule relations extracted with biomedical language models, IMicAP enables context-aware exploration of microbial relations.
Conclusion: IMicAP (available at: https://www.imicap.com:8443 ) is the first comprehensive, open-access, AI-powered microbial platform designed to bridge the gap between fragmented microbial data and actionable biological insights. It directly addresses 4 key limitations in existing resources: (1) Fragmented analysis without integrated workflows; (2) Narrow disease scope covering only one or two disease types; (3) Incomplete knowledge from restricted data sources; and (4) neglect of metabolomic information. IMicAP serves as a versatile resource for advancing microbiome research and translational discoveries. Future development focus on expanding microbial coverage, enhancing reasoning scalability, and evolving toward a dual knowledge-and-data-driven architecture to further support mechanistic discovery in microbial systems biology.
Related
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BibTeX
@article{zhu2026imicap,
title = {{IMicAP: an intelligent microbial application platform for knowledge-driven microbiome research}},
author = {Chaoyu Zhu and Xing Wang and Lihui Feng and Mingzhang Xu and Zhengkun Huang and Weijie Chen and Lei Liu},
journal = {Frontiers in microbiology},
year = {2026},
month = oct,
doi = {10.3389/fmicb.2026.1955928},
url = {https://europepmc.org/article/PMC/PMC13668525},
note = {CC BY},
}
RIS
TY - JOUR
TI - IMicAP: an intelligent microbial application platform for knowledge-driven microbiome research
AU - Chaoyu Zhu
AU - Xing Wang
AU - Lihui Feng
AU - Mingzhang Xu
AU - Zhengkun Huang
AU - Weijie Chen
AU - Lei Liu
PY - 2026
DA - 2026/10/01
JO - Frontiers in microbiology
DO - 10.3389/fmicb.2026.1955928
UR - https://europepmc.org/article/PMC/PMC13668525
AB - Background: Microorganisms play a pivotal role in health and disease, yet microbial research is hindered by fragmented data, heterogeneous knowledge representation, and a lack of integrated analytical tools. Existing databases and knowledge graphs often focus narrowly on genomic information, leaving critical metabolomic and literature-based associations underdeveloped. Results: We developed the Intelligent Microbial Application Platform (IMicAP), an AI-driven, open-access web platform that integrates 12 microbial databases and over 35 million articles. IMicAP delivers 5 core modules: (1) Knowledge Query module for rapid data retrieval; (2) Knowledge Graph module for multi-hop reasoning and hypothesis generation; (3) Intelligent Question-Answering module for professional natural language dialogue in the field of microbiology; (4) Genome Browser module for genomic visualization; and (5) 16S rRNA Sequencing Analysis module for zero-code microbial bioinformatics analysis. Using curated microbe-disease and microbe-small molecule relations extracted with biomedical language models, IMicAP enables context-aware exploration of microbial relations. Conclusion: IMicAP (available at: https://www.imicap.com:8443 ) is the first comprehensive, open-access, AI-powered microbial platform designed to bridge the gap between fragmented microbial data and actionable biological insights. It directly addresses 4 key limitations in existing resources: (1) Fragmented analysis without integrated workflows; (2) Narrow disease scope covering only one or two disease types; (3) Incomplete knowledge from restricted data sources; and (4) neglect of metabolomic information. IMicAP serves as a versatile resource for advancing microbiome research and translational discoveries. Future development focus on expanding microbial coverage, enhancing reasoning scalability, and evolving toward a dual knowledge-and-data-driven architecture to further support mechanistic discovery in microbial systems biology.
SN - 1664-302X
ER -