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.
Original language | English (US) |
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Pages (from-to) | 42-48 |
Number of pages | 7 |
Journal | Forschende Komplementarmedizin |
Volume | 19 |
Issue number | SUPPL. 1 |
DOIs | |
State | Published - Jan 2012 |
Keywords
- Clinical trial design
- Complementary and alternative medicine
- Heterogeneity
- Parsimony
- Phylogenetics
- Synapomorphies
- Systems biology
ASJC Scopus subject areas
- Complementary and alternative medicine