Hierarchical Models for Mitochondrial DNA Sequence Data

Abstract: We introduce a Bayesian hierarchical model for mitochondrial DNA sequence data, which is fitted via acceptance-rejection algorithms. The model incorporates parametric models of population history explicitly as well as a mutational process allowing for a simultaneous parameter estimation whose importance has become increasingly clear in many recent studies. The model is applied to a sample of DNA sequences from the Italian population. Abstract: Wir stellen ein Bayes'sches hierarchisches Modell für mitochondrialen DNA Sequenzdaten vor, das mittels Acceptance-Rejection Algorithmen angepasst wird. Das Modell enthält explizit parametrische Modelle für die Entwicklung der Population wie auch einen Veränderungsprozess und erlauben eine simultane Parameterschätzung. Die Wichtigkeit dieser Vorgehensweise ist durch viele aktuelle Studien ganz deutlich nachgewiesen worden. Das Model wird auf eine Stichprobe von DNA Sequenzen der Italienischen Population angewandt

Local Temperature and Universal Heat Conduction in FPU chains

It is shown numerically that for Fermi Pasta Ulam (FPU) chains with alternating masses and heat baths at slightly different temperatures at the ends, the local temperature (LT) on small scales behaves paradoxically in steady state. This expands the long established problem of equilibration of FPU chains. A well-behaved LT appears to be achieved for equal mass chains; the thermal conductivity is shown to diverge with chain length N as N^(1/3), relevant for the much debated question of the universality of one dimensional heat conduction. The reason why earlier simulations have obtained systematically higher exponents is explained.Comment: 4 pages, 3 figures, revised published versio

Human Protein Cluster Analysis Using Amino Acid Frequencies

The paper focuses on the development of a software tool for protein clustering according to their amino acid content. All known human proteins were clustered according to the relative frequencies of their amino acids starting from the UniProtKB/Swiss-Prot reference database and making use of hierarchical cluster analysis. RESULTS were compared to those based on sequence similarities.Proteins display different clustering patterns according to type. Many extracellular proteins with highly specific and repetitive sequences (keratins, collagens etc.) cluster clearly confirming the accuracy of the clustering method. In our case clustering by sequence and amino acid content overlaps. Proteins with a more complex structure with multiple domains (catalytic, extracellular, transmembrane etc.), even if classified very similar according to sequence similarity and function (aquaporins, cadherins, steroid 5-alpha reductase etc.) showed different clustering according to amino acid content. Availability of essential amino acids according to local conditions (starvation, low or high oxygen, cell cycle phase etc.) may be a limiting factor in protein synthesis, whatever the mRNA level. This type of protein clustering may therefore prove a valuable tool in identifying so far unknown metabolic connections and constraints