ArticleMedical & biological engineering & computing2008
Discovering active compounds from mixture of natural products by data mining approach.
Article in Medical & biological engineering & computing, 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 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
3 citing papers in PubMed.
- Machine Learning-Enabled Genome Mining and Bioactivity Prediction of Natural Products.ACS synthetic biology · 2023Review
- Extracting the Benefit of NexrutineCurrent pharmacology reports · 2015Article
- 21st century natural product research and drug development and traditional medicines.Natural product reports · 2013Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Traditionally, active compounds were discovered from natural products by repeated isolation and bioassays, which can be highly time consuming. Here, we have developed a data mining approach using the casual discovery algorithm to identify active compounds from mixtures by investigating the correlation between their chemical composition and bioactivity in the mixtures. The efficacy of our algorithm was validated by the cytotoxic effect of Panax ginseng extracts on MCF-7 cells and compared with previous reports. It was demonstrated that our method could successfully pick out active compounds from a mixture in the absence of separation processes. It is expected that the presented algorithm can possibly accelerate the process of discovering new drugs.
Indexed as
Identifiers
18320248What 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.