In recent years, collaborations often between mathematical and computational biologists and scientists in the World Health Organization (WHO) global influenza surveillance network, have resulted in a number of mathematical and computational advances including: increasing the resolution at which antigenic surveillance data can be analyzed, providing methods for genetic analysis and prediction, and an increased understanding of the determinants of repeated influenza vaccination. These advances increase the information extracted from influenza surveillance and increase the quantitative data available for the vaccine strain selection process. This mathematical and computational work is possible because of the wealth of information collected over many years by the WHO global influenza surveillance network, and further advances will be greatly facilitated by implementation of the proposed strengthening of virological and epidemiological surveillance in the WHO global agenda on influenza surveillance and control.

SUMMARY: The program MRBAYES performs Bayesian inference of phylogeny using a variant of Markov chain Monte Carlo. AVAILABILITY: MRBAYES, including the source code, documentation, sample data files, and an executable, is available at http://brahms.biology.rochester.edu/software.html.

A new method is presented for inferring evolutionary trees using nucleotide sequence data. The birth-death process is used as a model of speciation and extinction to specify the prior distribution of phylogenies and branching times. Nucleotide substitution is modeled by a continuous-time Markov process. Parameters of the branching model and the substitution model are estimated by maximum likelihood. The posterior probabilities of different phylogenies are calculated and the phylogeny with the highest posterior probability is chosen as the best estimate of the evolutionary relationship among species. We refer to this as the maximum posterior probability (MAP) tree. The posterior probability provides a natural measure of the reliability of the estimated phylogeny. Two example data sets are analyzed to infer the phylogenetic relationship of human, chimpanzee, gorilla, and orangutan. The best trees estimated by the new method are the same as those from the maximum likelihood analysis of separate topologies, but the posterior probabilities are quite different from the bootstrap proportions. The results of the method are found to be insensitive to changes in the rate parameter of the branching process.

GlyProt (http://www.glycosciences.de/glyprot/) is a web-based tool that enables meaningful N-glycan conformations to be attached to all the spatially accessible potential N-glycosylation sites of a known three-dimensional (3D) protein structure. The probabilities of physicochemical properties such as mass, accessible surface and radius of gyration are calculated. The purpose of this service is to provide rapid access to reliable 3D models of glycoproteins, which can subsequently be refined by using more elaborate simulations and validated by comparing the generated models with experimental data.