ArticleForschende Komplementarmedizin (2006)2012
Analyzing heterogeneous complexity in complementary and alternative medicine research: a systems biology solution via parsimony phylogenetics.
Article in Forschende Komplementarmedizin (2006), 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 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.
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Who cites it
5 citing papers in PubMed.
- A Systems Biology Interpretation of Array Comparative Genomic Hybridization (aCGH) Data through Phylogenetics.Omics : a journal of integrative biology · 2016Article
- Computational Tools for Parsimony Phylogenetic Analysis of Omics Data.Omics : a journal of integrative biology · 2015Article
- An integrative CGH, MSI and candidate genes methylation analysis of colorectal tumors.PloS one · 2014Article
- Potential self-regulatory mechanisms of yoga for psychological health.Frontiers in human neuroscience · 2014Article
- Testing the nanoparticle-allostatic cross-adaptation-sensitization model for homeopathic remedy effects.Homeopathy : the journal of the Faculty of Homeopathy · 2013Article
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
Abstract
Systems biology offers cutting-edge tools for the study of complementary and alternative medicine (CAM). The advent of 'omics' techniques and the resulting avalanche of scientific data have introduced an unprecedented level of complexity and heterogeneous data to biomedical research, leading to the development of novel research approaches. Statistical averaging has its limitations and is unsuitable for the analysis of heterogeneity, as it masks diversity by homogenizing otherwise heterogeneous populations. Unfortunately, most researchers are unaware of alternative methods of analysis capable of accounting for individual variability. This paper describes a systems biology solution to data complexity through the application of parsimony phylogenetic analysis. Maximum parsimony (MP) provides a data-based modeling paradigm that will permit a priori stratification of the study cohort(s), better assessment of early diagnosis, prognosis, and treatment efficacy within each stratum, and a method that could be used to explore, identify and describe complex human patterning.
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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.