Uppsala University

About: Uppsala University is a education organization based out in Uppsala, Sweden. It is known for research contribution in the topics: Population & Insulin. The organization has 36485 authors who have published 107509 publications receiving 4220668 citations. The organization is also known as: Uppsala universitet & uu.se.

Potential Applications and Pitfalls of Bayesian Inference of Phylogeny

Abstract: Only recently has Bayesian inference of phylogeny been proposed. The method is now a practical alternative to the other methods; indeed, the method appears to possess advantages over the other methods in terms of ability to use complex models of evolution, ease of interpretation of the results, and computational efeciency. However, the method should be used cautiously. The results of a Bayesian analysis should be examined with respect to the sensitivity of the results to the priors used and the reliability of the Markov chain Monte Carlo approximation of the probabilities of trees. (Bayesian inference; Markov chain Monte Carlo; phylogeny; posterior probability.)

cDNA sequence and chromosomal localization of human platelet-derived growth factor A-chain and its expression in tumour cell lines

Abstract: The amino-acid sequence of the precursor of the human tumour cell line-derived platelet-derived growth factor (PDGF) A-chain has been deduced from complementary DNA clones and the gene localized to chromosome 7. The protein shows extensive homology to the PDGF B-chain precursor. Expression of the PDGF A-chain gene is independent of that of the PDGF B-chain in a number of human tumour cell lines, and secretion of a PDGF-like growth factor of relative molecular mass 31,000 correlates with expression of A- but not B-chain messenger RNA.

GenX: an extensible X-ray reflectivity refinement program utilizing differential evolution

Abstract: GenX is a versatile program using the differential evolution algorithm for fitting X-ray and neutron reflectivity data. It utilizes the Parratt recursion formula for simulating specular reflectivity. The program is easily extensible, allowing users to incorporate their own models into the program. This can be useful for fitting data from other scattering experiments, or for any other minimization problem which has a large number of input parameters and/or contains many local minima, where the differential evolution algorithm is suitable. In addition, GenX manages to fit an arbitrary number of data sets simultaneously. The program is released under the GNU General Public License.