ReviewHeliyon2023
Comprehensive survey of target prediction web servers for Traditional Chinese Medicine.
Review in Heliyon, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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
13 citing papers in PubMed.
- Article
- Jervine-induced suppression of triple-negative breast cancer (TNBC) cells growth through the regulation of Wnt signaling pathway- an in-silico and in-vitro approach.Journal of computer-aided molecular design · 2026Article
- Molecular Mechanism of Dihydroquercetin in Ameliorating Metabolic Dysfunction-Associated Steatotic Liver Disease: Insights Into the HIF-1α/VEGF Pathway.Food science & nutrition · 2026Article
- Advancing the modernization of traditional Chinese medicine through artificial intelligence and multimodal data integration.Chinese medicine · 2026Review
- The scientific basis of synergy in traditional Chinese medicine: physicochemical, pharmacokinetic, and pharmacodynamic perspectives.Chinese medicine · 2026Review
- Bushen Daozhuo Granules Alleviate Chronic Non-Bacterial Prostatitis in Rats through p38 MAPK and Akt Signaling Pathways Based on Tandem Mass Tag-Based Quantitative Proteomics and Network Pharmacology Analyses.Combinatorial chemistry & high throughput screening · 2026Article
- Molecular dynamics simulation in traditional Chinese medicine research: from molecular mechanisms to multiscale validation.Frontiers in chemistry · 2026Review
- Machine Learning for Multi-Target Drug Discovery: Challenges and Opportunities in Systems Pharmacology.Pharmaceutics · 2025Review
- Development of modern Chinese medicine guided by molecular compatibility theory.Journal of advanced research · 2025Review
- Dapagliflozin in Chronic Kidney Disease: Insights from Network Pharmacology and Molecular Docking Simulation.Life (Basel, Switzerland) · 2025Article
- Network pharmacology: Changes the treatment mode of "one disease-one target" in cancer treatment.World journal of gastrointestinal oncology · 2025Article
- Network pharmacology study andWorld journal of gastrointestinal oncology · 2024Article
- The Biology and Biochemistry of Kynurenic Acid, a Potential Nutraceutical with Multiple Biological Effects.International journal of molecular sciences · 2024Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Traditional Chinese medicine (TCM) is characterized by multi-components, multiple targets, and complex mechanisms of action and therefore has significant advantages in treating diseases. However, the clinical application of TCM prescriptions is limited due to the difficulty in elucidating the effective substances and the lack of current scientific evidence on the mechanisms of action. In recent years, the development of network pharmacology based on drug systems research has provided a new approach for understanding the complex systems represented by TCM. The determination of drug targets is the core of TCM network pharmacology research. Over the past years, many web tools for drug targets with various features have been developed to facilitate target prediction, significantly promoting drug discovery. Therefore, this review introduces the widely used web tools for compound-target interaction prediction databases and web resources in TCM pharmacology research, and it compares and analyzes each web tool based on their basic properties, including the underlying theory, algorithms, datasets, and search results. Finally, we present the remaining challenges for the promising future of compound-target interaction prediction in TCM pharmacology research. This work may guide researchers in choosing web tools for target prediction and may also help develop more TCM tools based on these existing resources.
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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.