ArticleComputational and structural biotechnology journal2024
TCMM: A unified database for traditional Chinese medicine modernization and therapeutic innovations.
Article in Computational and structural biotechnology journal, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled 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.
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.
Who cites it
9 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Pooled it
- Advancing the modernization of traditional Chinese medicine through artificial intelligence and multimodal data integration.Chinese medicine · 2026Review
- Bicuculline fromComputational and structural biotechnology journal · 2026Article
- Decoding herbal combination models through systematic strategies: insights from target information and traditional Chinese medicine clinical theory.Briefings in bioinformatics · 2025Article
- Development and Validation of an HPLC-PDA Method for Quality Control of Jwagwieum, an Herbal Medicine Prescription: Simultaneous Analysis of Nine Marker Compounds.Pharmaceuticals (Basel, Switzerland) · 2025Article
- Computer-Aided Drug Design in Research on Chinese Materia Medica: Methods, Applications, Advantages, and Challenges.Pharmaceutics · 2025Review
- Addressing the obstacles in cultivating global advocates for traditional Chinese medicine: qualitative perspectives from stakeholder interview analysis.Frontiers in public health · 2025Article
- HerbComb: An integrated database for the discovery of novel combinational therapies from herbal medicines.Computational and structural biotechnology journal · 2025Article
- Modeling the therapeutic dynamics of acupuncture and moxibustion: a systems biology approach to treatment optimization.Computational and structural biotechnology journal · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Mining the potential of traditional Chinese medicine (TCM) in treating modern diseases requires a profound understanding of its action mechanism and a comprehensive knowledge system that seamlessly bridges modern medical insights with traditional theories. However, existing databases for modernizing TCM are plagued by varying degrees of information loss, which impede the multidimensional dissection of pharmacological effects. To address this challenge, we introduce traditional Chinese medicine modernization (TCMM), the currently largest modernized TCM database that integrates pioneering intelligent pipelines. By aligning high-quality TCM and modern medicine data, TCMM boasts the most extensive TCM modernization knowledge, including 20 types of modernized TCM concepts such as prescription, ingredient, target and 46 biological relations among them, totaling 3,447,023 records. We demonstrate the efficacy and reliability of TCMM with two features, prescription generation and knowledge discovery, the outcomes show consistency with biological experimental results. A publicly available web interface is at https://www.tcmm.net.cn/.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.