On calculating the probability of a set of orthologous sequences

Probabilistic DNA sequence models have been intensively applied to genome research. Within the evolutionary biology framework, this article investigates the feasibility for rigorously estimating the probability of a set of orthologous DNA sequences which evolve from a common progenitor. We propose Monte Carlo integration algorithms to sample the unknown ancestral and/or root sequences a posteriori conditional on a reference sequence and apply pairwise Needleman–Wunsch alignment between the sampled and nonreference species sequences to estimate the probability. We test our algorithms on both simulated and real sequences and compare calculated probabilities from Monte Carlo integration to those induced by single multiple alignment

Statistical design and analysis of clinical trials : principles and methods

xix, 226 pages ; 24 c

Is SubcellularLocalization Informative for Modeling Protein-protein Interaction Signal?

Statistical methods have been intensively applied in genomic signal processing (Dougherty et al. 2005). For budding yeast Saccharomyces cerevisiae with around 6000 proteins, genome-wide protein-protein-interaction (PPI) (Fromont-Racine et al. 2000, Ito et al. 2001, Newman et al. 2000, and Uetz et al. 2000 among others) and protein subcellular localization (PSL) (Huh et al. 2003) data recently became available and for the latter the presence of 4152 proteins is experimentally tested in each of the 22 subcellular compartments. Recent work shows that multiple biological sources are helpful for both PSL and PPI predictions, and this paper studies statistical feasibility of modeling PPI from PSL since PSLs may play different marginal or joint roles in the complex regulatory network. However, our results indicate that PSL may be controversial for this purpose as an independent source

Inhibition of Intestinal Tumorigenesis in Apcmin/+ Mice by (-)-Epigallocatechin-3-Gallate, the Major Catechin in Green Tea

The present study was designed to investigate the effects of two main constituents of green tea, (-)-epigallocatechin-3-gallate (EGCG) and caffeine, on intestinal tumorigenesis in Apcmin/+ mice, a recognized mouse model for human intestinal cancer, and to elucidate possible mechanisms involved in the inhibitory action of the active constituent. We found that p.o. administration of EGCG at doses of 0.08% or 0.16% in drinking fluid significantly decreased small intestinal tumor formation by 37% or 47%, respectively, whereas caffeine at a dose of 0.044% in drinking fluid had no inhibitory activity against intestinal tumorigenesis. In another experiment, small intestinal tumorigenesis was inhibited in a dose-dependent manner by p.o. administration of EGCG in a dose range of 0.02% to 0.32%. P.O. administration of EGCG resulted in increased levels of E-cadherin and decreased levels of nuclear β-catenin, c-Myc, phospho-Akt, and phospho-extracellular signal-regulated kinase 1/2 (ERK1/2) in small intestinal tumors. Treatment of HT29 human colon cancer cells with EGCG (12.5 or 20 μmol/L at different times) also increased protein levels of E-cadherin by 27% to 58%, induced the translocation of β-catenin from nucleus to cytoplasm and plasma membrane, and decreased c-Myc and cyclin D1 (20 μmol/L EGCG for 24 hours). These results indicate that EGCG effectively inhibited intestinal tumorigenesis in Apcmin/+ mice, possibly through the attenuation of the carcinogenic events, which include aberrant nuclear β-catenin and activated Akt and ERK signaling