Analysis of residuals from enzyme kinetic and protein folding experiments in the presence of correlated experimental noise

Experimental data from continuous enzyme assays or protein folding experiments often contain hundreds, or even thousands, of densely spaced data points. When the sampling interval is extremely short, the experimental data points might not be statistically independent. The resulting neighborhood correlation invalidates important theoretical assumptions of nonlinear regression analysis. As a consequence, certain goodness-of-fit criteria, such as the runs-of-signs test and the autocorrelation function, might indicate a systematic lack of fit even if the experiment does agree very well with the underlying theoretical model. A solution to this problem is to analyze only a subset of the residuals of fit, such that any excessive neighborhood correlation is eliminated. Substrate kinetics of the HIV protease and the unfolding kinetics of UMP/CMP kinase, a globular protein from Dictyostelium discoideum, serve as two illustrative examples. A suitable data-reduction algorithm has been incorporated into software DYNAFIT [P. Kuzmi?, Anal. Biochem. 237 (1996) 260-273], freely available to all academic researchers from http://www.biokin.com.     

Simultaneous Statistical Inference for Epigenetic Data

Epigenetic research leads to complex data structures. Since parametric model assumptions for the distribution of epigenetic data are hard to verify we introduce in the present work a nonparametric statistical framework for two-group comparisons. Furthermore, epigenetic analyses are often performed at various genetic loci simultaneously. Hence, in order to be able to draw valid conclusions for specific loci, an appropriate multiple testing correction is necessary. Finally, with technologies available for the simultaneous assessment of many interrelated biological parameters (such as gene arrays), statistical approaches also need to deal with a possibly unknown dependency structure in the data. Our statistical approach to the nonparametric comparison of two samples with independent multivariate observables is based on recently developed multivariate multiple permutation tests. We adapt their theory in order to cope with families of hypotheses regarding relative effects. Our results indicate that the multivariate multiple permutation test keeps the pre-assigned type I error level for the global null hypothesis. In combination with the closure principle, the family-wise error rate for the simultaneous test of the corresponding locus/parameter-specific null hypotheses can be controlled. In applications we demonstrate that group differences in epigenetic data can be detected reliably with our methodology.     

A Proposed Timescale for the Evolution of Armophorean Ciliates: Clevelandellids Diversify More Rapidly Than Metopids

Members of the class Armophorea occur in microaerophilic and anaerobic habitats, including the digestive tract of invertebrates and vertebrates. Phylogenetic kinships of metopid and clevelandellid armophoreans conflict with traditional morphology‐based classifications. To reconcile their relationships and understand their morphological evolution and diversification, we utilized the molecular clock theory as well as information contained in the estimated time trees and morphology of extant taxa. The radiation of the last common ancestor of metopids and clevelandellids very likely occurred during the Paleozoic and crown diversification of the endosymbiotic clevelandellids dates back to the Mesozoic. According to diversification analyses, endosymbiotic clevelandellids have higher net diversification rates than predominantly free‐living metopids. Their cladogenic success was very likely associated with sharply isolated ecological niches constituted by their hosts. Conflicts between traditional classifications and molecular phylogenies of metopids and clevelandellids very likely come from processes, leading to further diversification without extinction of ancestral lineages as well as from morphological plesiomorphies incorrectly classified as apomorphies. Our study thus suggests that diversification processes and reconstruction of ancestral morphologies improve the understanding of paraphyly which occurs in groups of organisms with an apparently long evolutionary history and when speciation prevails over extinction.