Estimating Discrete Markov Models From Various Incomplete Data Schemes

The parameters of a discrete stationary Markov model are transition probabilities between states. Traditionally, data consist in sequences of observed states for a given number of individuals over the whole observation period. In such a case, the estimation of transition probabilities is straightforwardly made by counting one-step moves from a given state to another. In many real-life problems, however, the inference is much more difficult as state sequences are not fully observed, namely the state of each individual is known only for some given values of the time variable. A review of the problem is given, focusing on Monte Carlo Markov Chain (MCMC) algorithms to perform Bayesian inference and evaluate posterior distributions of the transition probabilities in this missing-data framework. Leaning on the dependence between the rows of the transition matrix, an adaptive MCMC mechanism accelerating the classical Metropolis-Hastings algorithm is then proposed and empirically studied.Comment: 26 pages - preprint accepted in 20th February 2012 for publication in Computational Statistics and Data Analysis (please cite the journal's paper

Inferring transition probabilities from repeated cross sections: a cross-level inference approach to US presidential voting

This paper outlines a nonstationary, heterogeneous Markov model designed to estimate entry and exit transition probabilities at the micro-level from a time series of independent cross-sectional samples with a binary outcomevariable. The model has its origins in the work of Moffitt (1993) and shares features with standard statistical methods for ecological inference. We show how ML estimates of the parameters can be obtained by the method-of-scoring, how to estimate time-varying covariate effects, and how to include non-backcastable variables in the model. The latter extension of the basic model is an important one as it strongly increases its potential application in a wide array of research contexts. The example illustration uses survey data on American presidential vote intentions from a five-wavepanel study conducted by Patterson (1980) in 1976. We treat the panel data as independent cross sections and compare the estimates of the Markov model with the observations in the panel. Directions for future work are discussed.Markov model;transition probabilities

Selection for Replicases in Protocells

PMCID: PMC3649988This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited

The Statistical Analysis of Behavioural Latency Measures

This article concerns two important problems with the statistical analysis of behavioural latency measures: they typically have severely skewed distributions, and are often censored (truncated). These problems, however, were not generally recognised by animal behaviour researchers: most people either allot an arbitrary score to all censored values or simply ignore them. Yet, such treatments could easily lead to dubious conclusions because of reduction of power and spuriously significant p-values. Thus, one should always use specially devised survival analysis methods whenever the study involves the measurement of censored latencies. The present article provides a short catalogue of some appropriate references, concentrating on the methods which are not “standard” for the common biomedical applications of survival analysis, but may be crucial in many behavioural studies. The statistical analysis of uncensored latencies is also discussed, with a particular attention to the analysis of variance

MicroRNA regulation of bovine monocyte inflammatory and metabolic networks in an in vivo infection model.

peer-reviewedBovine mastitis is an inflammation-driven disease of the bovine mammary gland that costs the global dairy industry several billion dollars per annum. Because disease susceptibility is a multi-factorial complex phenotype, an integrative biology approach is required to dissect the molecular networks involved. Here, we report such an approach, using next generation sequencing combined with advanced network and pathway biology methods to simultaneously profile mRNA and miRNA expression at multiple time-points (0, 12, 24, 36 and 48h) in both milk and blood FACS-isolated CD14+ monocytes from animals infected in vivo with Streptococcus uberis. More than 3,700 differentially expressed (DE) genes were identified in milk-isolated monocytes (MIMs), a key immune cell recruited to the site of infection during mastitis. Up-regulated genes were significantly enriched for inflammatory pathways, while down-regulated genes were enriched for non-glycolytic metabolic pathways. Monocyte transcriptional changes in the blood, however, were more subtle but highlighted the impact of this infection systemically. Genes up-regulated in blood-isolated-monocytes (BIMs) showed a significant association with interferon and chemokine signalling. Furthermore, twenty-six miRNAs were differentially expressed in MIMs and three in BIMs. Pathway analysis revealed that predicted targets of down-regulated miRNAs were highly enriched for roles in innate immunity (FDR < 3.4E-8) in particular TLR signalling, while up-regulated miRNAs preferentially targeted genes involved in metabolism. We conclude that during S. uberis infection miRNAs are key amplifiers of monocyte inflammatory response networks and repressors of several metabolic pathways.This study was funded in part by Teagasc RMIS 6018 and United States Department of Agriculture ARS funding 3625-32000-102-00. NL is supported by a Teagasc Walsh Fellowship

Biologically produced volatile compounds: N2O emissions from soils

Tropospheric nitrous concentration has increased by 0.2 0.4% per year over the period 1975 to 1982, amounting to net addition to the atmosphere of 2.8 - 5.6 Tg N2O-N per year. This perturbation, if continued into the future, will affect stratospheric chemical cycles, and the thermal balance of the Earth. In turn it will have direct and indirect global effects on the biosphere. Though the budget and cycles of N2O on Earth are not yet fully resolved, accumulating information and recent modelling efforts permit a more complete evaluation and better definition of gaps in our knowledge

Influence of subunit structure on the oligomerization state of light harvesting complexes: a free energy calculation study

Light harvesting complexes 2 (LH2) from Rhodospirillum (Rs.) molischianum and Rhodopseudomonas (Rps.) acidophila form ring complexes out of eight or nine identical subunits, respectively. Here, we investigate computationally what factors govern the different ring sizes. Starting from the crystal structure geometries, we embed two subunits of each species into their native lipid-bilayer/water environment. Using molecular dynamics simulations with umbrella sampling and steered molecular dynamics, we probe the free energy profiles along two reaction coordinates, the angle and the distance between two subunits. We find that two subunits prefer to arrange at distinctly different angles, depending on the species, at about 42.5 deg for Rs. molischianum and at about 38.5 deg for Rps. acidophila, which is likely to be an important factor contributing to the assembly into different ring sizes. Our calculations suggest a key role of surface contacts within the transmembrane domain in constraining these angles, whereas the strongest interactions stabilizing the subunit dimers are found in the C-, and to a lesser extent, N-terminal domains. The presented computational approach provides a promising starting point to investigate the factors contributing to the assembly of protein complexes, in particular if combined with modeling of genetic variants.Comment: 28 pages, 7 figures, LaTeX2e - requires elsart.cls (included), submitted to Chemical Physic

The 1st Symposium on Chemical Evolution and the Origin and Evolution of Life

This symposium provided an opportunity for all NASA Exobiology principal investigators to present their most recent research in a scientific meeting forum. Papers were presented in the following exobiology areas: extraterrestrial chemistry primitive earth, information transfer, solar system exploration, planetary protection, geological record, and early biological evolution