We note that besides the multiple pathways considered above, Little and Wright [ 11], Little et al. [ 12] and Little [ 13] have also included mixture type of multiple pathways; however, because the mutation rates are very small, the chance of mixture type of pathways will be extremely small in which case the Little model is equivalent to the model in Section 3.
The functions fit and bootstrap estimate mixtures of evolutionary pathways from cross-sectional data, without and with bootstrap confidence intervals for model parameters, respectively.
The results also suggest that large effect sizes of SPINK1 N34S in small candidate gene studies in CP may be related to a mixture of multiple etiologic pathways leading to the same clinical endpoint.
While the subgroup analysis needs to be interpreted with caution, our results suggest that much of the variance in reported ORs between small studies of candidate genes in complex disorders may be attributed to a mixture of multiple etiologic pathways leading to a single clinical endpoint (e.g. organ fibrosis in CP).
The third pathway, present to all scientists independent of discipline, reflects a mixture of the first two pathways, whereby a scientist is embedded in an efficient medium-sized team environment and capitalizes on collaboration spillovers, thereby consistently producing highly-cited publications.
The mixture weight π, the percentage of pathways that are enriched, is generally assumed to be small.
Pathways in HER2+ are a mixture of TP53 (mutation rate 72%) related pathways and PIK3CA (mutation rate 40%) related pathways.
Thus, phylogenomic analysis indicates that these different organisms harbor pathways that display a mixture of features of the three canonical pathways from fungi, vertebrates, and land plants.
Several other host cell pathways contained a mixture of both up-regulated and down-regulated genes relative to the uninfected control; these pathways are clearly disrupted during T. hominis infection, but the overall effect on the host is difficult to predict from changes in transcript abundance.
The validation of our hypothesis through these biomarkers, would allow the estimation of the total personal exposure to complex mixture of toxic chemicals from different exposure pathways (lungs, skin, and GIT), and different sources (air, diet, lifestyle or occupation), whereas the traditional epidemiological studies don't.
