Use of artificial genomes in assessing methods for atypical gene detection

Parametric methods for identifying laterally transferred genes exploit the directional mutational biases unique to each genome. Yet the development of new, more robust methods - as well as the evaluation and proper implementation of existing methods - relies on an arbitrary assessment of performance using real genomes, where the evolutionary histories of genes are not known. We have used the framework of a generalized hidden Markov model to create artificial genomes modeled after genuine genomes. To model a genome, "core" genes - those displaying patterns of mutational biases shared among large numbers of genes - are identified by a novel gene clustering approach based on the Akaike information criterion. Gene models derived from multiple "core" gene clusters are used to generate an artificial genome that models the properties of a genuine genome. Chimeric artificial genomes - representing those having experienced lateral gene transfer - were created by combining genes from multiple artificial genomes, and the performance of the parametric methods for identifying "atypical" genes was assessed directly. We found that a hidden Markov model that included multiple gene models, each trained on sets of genes representing the range of genotypic variability within a genome, could produce artificial genomes that mimicked the properties of genuine genomes. Moreover, different methods for detecting foreign genes performed differently - i.e., they had different sets of strengths and weaknesses - when identifying atypical genes within chimeric artificial genomes. © 2005 Azad and Lawrence

Thermodynamic analysis of the Quantum Critical behavior of Ce-lattice compounds

A systematic analysis of low temperature magnetic phase diagrams of Ce compounds is performed in order to recognize the thermodynamic conditions to be fulfilled by those systems to reach a quantum critical regime and, alternatively, to identify other kinds of low temperature behaviors. Based on specific heat ($C_m$) and entropy ($S_m$) results, three different types of phase diagrams are recognized: i) with the entropy involved into the ordered phase ($S_{MO}$) decreasing proportionally to the ordering temperature ($T_{MO}$), ii) those showing a transference of degrees of freedom from the ordered phase to a non-magnetic component, with their $C_m(T_{MO})$ jump ($\Delta C_m$) vanishing at finite temperature, and iii) those ending in a critical point at finite temperature because their $\Delta C_m$ do not decrease with $T_{MO}$ producing an entropy accumulation at low temperature. Only those systems belonging to the first case, i.e. with $S_{MO}\to 0$ as $T_{MO}\to 0$, can be regarded as candidates for quantum critical behavior. Their magnetic phase boundaries deviate from the classical negative curvature below $T\approx 2.5$\,K, denouncing frequent misleading extrapolations down to T=0. Different characteristic concentrations are recognized and analyzed for Ce-ligand alloyed systems. Particularly, a pre-critical region is identified, where the nature of the magnetic transition undergoes significant modifications, with its $\partial C_m/\partial T$ discontinuity strongly affected by magnetic field and showing an increasing remnant entropy at $T\to 0$. Physical constraints arising from the third law at $T\to 0$ are discussed and recognized from experimental results

Forecasting Player Behavioral Data and Simulating in-Game Events

Understanding player behavior is fundamental in game data science. Video games evolve as players interact with the game, so being able to foresee player experience would help to ensure a successful game development. In particular, game developers need to evaluate beforehand the impact of in-game events. Simulation optimization of these events is crucial to increase player engagement and maximize monetization. We present an experimental analysis of several methods to forecast game-related variables, with two main aims: to obtain accurate predictions of in-app purchases and playtime in an operational production environment, and to perform simulations of in-game events in order to maximize sales and playtime. Our ultimate purpose is to take a step towards the data-driven development of games. The results suggest that, even though the performance of traditional approaches such as ARIMA is still better, the outcomes of state-of-the-art techniques like deep learning are promising. Deep learning comes up as a well-suited general model that could be used to forecast a variety of time series with different dynamic behaviors

Infrared emission towards SN 1987A 11 years after outburst: Measurements with ISOCAM

We present measurements of the mid-infrared (MIR) emission from SN 1987A, made using the Infrared Space Observatory (ISO) 11 years after outburst. They are the only late epoch detections of this source in the thermal IR regime. The position of the source, determined from an offset to an IR-emitting star, suggests that the emission is associated with SN 1987A or its extended supernova remnant (SNR). A predominantly circumstellar origin is however suggested by the size and orientation of the IR-emitting region, which is comparable with the extension of the inner ring seen with the Hubble Space Telescope (HST). The emission is most probably from collisionally-heated circumstellar grains embedded in shocked gas downstream of the blast wave. The MIR extent is consistent with the hypothesis that the blast wave was propagating into material of moderate density interior to the thick inner ring at the epoch of the ISOCAM observations

Partial Homology Relations - Satisfiability in terms of Di-Cographs

Directed cographs (di-cographs) play a crucial role in the reconstruction of evolutionary histories of genes based on homology relations which are binary relations between genes. A variety of methods based on pairwise sequence comparisons can be used to infer such homology relations (e.g.\ orthology, paralogy, xenology). They are \emph{satisfiable} if the relations can be explained by an event-labeled gene tree, i.e., they can simultaneously co-exist in an evolutionary history of the underlying genes. Every gene tree is equivalently interpreted as a so-called cotree that entirely encodes the structure of a di-cograph. Thus, satisfiable homology relations must necessarily form a di-cograph. The inferred homology relations might not cover each pair of genes and thus, provide only partial knowledge on the full set of homology relations. Moreover, for particular pairs of genes, it might be known with a high degree of certainty that they are not orthologs (resp.\ paralogs, xenologs) which yields forbidden pairs of genes. Motivated by this observation, we characterize (partial) satisfiable homology relations with or without forbidden gene pairs, provide a quadratic-time algorithm for their recognition and for the computation of a cotree that explains the given relations

Genome landscapes and bacteriophage codon usage

Across all kingdoms of biological life, protein-coding genes exhibit unequal usage of synonmous codons. Although alternative theories abound, translational selection has been accepted as an important mechanism that shapes the patterns of codon usage in prokaryotes and simple eukaryotes. Here we analyze patterns of codon usage across 74 diverse bacteriophages that infect E. coli, P. aeruginosa and L. lactis as their primary host. We introduce the concept of a `genome landscape,' which helps reveal non-trivial, long-range patterns in codon usage across a genome. We develop a series of randomization tests that allow us to interrogate the significance of one aspect of codon usage, such a GC content, while controlling for another aspect, such as adaptation to host-preferred codons. We find that 33 phage genomes exhibit highly non-random patterns in their GC3-content, use of host-preferred codons, or both. We show that the head and tail proteins of these phages exhibit significant bias towards host-preferred codons, relative to the non-structural phage proteins. Our results support the hypothesis of translational selection on viral genes for host-preferred codons, over a broad range of bacteriophages.Comment: 9 Color Figures, 5 Tables, 53 Reference

"They think we're OK and we know we're not". A qualitative study of asylum seekers' access, knowledge and views to health care in the UK

<i>Background</i>: The provision of healthcare for asylum seekers is a global issue. Providing appropriate and culturally sensitive services requires us to understand the barriers facing asylum seekers and the facilitators that help them access health care. Here, we report on two linked studies exploring these issues, along with the health care needs and beliefs of asylum seekers living in the UK. <i>Methods</i>: Two qualitative methods were employed: focus groups facilitated by members of the asylum seeking community and interviews, either one-to-one or in a group, conducted through an interpreter. Analysis was facilitated using the Framework method. <i>Results</i>: Most asylum seekers were registered with a GP, facilitated for some by an Asylum Support nurse. Many experienced difficulty getting timely appointments with their doctor, especially for self-limiting symptoms that they felt could become more serious, especially in children. Most were positive about the health care they received, although some commented on the lack of continuity. However, there was surprise and disappointment at the length of waiting times both for hospital appointments and when attending accident and emergency departments. Most had attended a dentist, but usually only when there was a clinical need. The provision of interpreters in primary care was generally good, although there was a tension between interpreters translating verbatim and acting as patient advocates. Access to interpreters in other settings, e.g. in-patient hospital stays, was problematic. Barriers included the cost of over-the-counter medication, e.g. children's paracetamol; knowledge of out-of-hours medical care; and access to specialists in secondary care. Most respondents came from countries with no system of primary medical care, which impacted on their expectations of the UK system. <i>Conclusion</i>: Most asylum seekers were positive about their experiences of health care. However, we have identified issues regarding their understanding of how the UK system works, in particular the role of general practitioners and referral to hospital specialists. The provision of an Asylum Support nurse was clearly a facilitator to accessing primary medical care. Initiatives to increase their awareness and understanding of the UK system would be beneficial. Interpreting services also need to be developed, in particular their role in secondary care and the development of the role of interpreter as patient advocate

Universal scaling relation in high-temperature superconductors

Scaling laws express a systematic and universal simplicity among complex systems in nature. For example, such laws are of enormous significance in biology. Scaling relations are also important in the physical sciences. The seminal 1986 discovery of high transition-temperature (high-T_c) superconductivity in cuprate materials has sparked an intensive investigation of these and related complex oxides, yet the mechanism for superconductivity is still not agreed upon. In addition, no universal scaling law involving such fundamental properties as T_c and the superfluid density \rho_s, a quantity indicative of the number of charge carriers in the superconducting state, has been discovered. Here we demonstrate that the scaling relation \rho_s \propto \sigma_{dc} T_c, where the conductivity \sigma_{dc} characterizes the unidirectional, constant flow of electric charge carriers just above T_c, universally holds for a wide variety of materials and doping levels. This surprising unifying observation is likely to have important consequences for theories of high-T_c superconductivity.Comment: 11 pages, 2 figures, 2 table

Bayesian modeling of recombination events in bacterial populations

Background: We consider the discovery of recombinant segments jointly with their origins within multilocus DNA sequences from bacteria representing heterogeneous populations of fairly closely related species. The currently available methods for recombination detection capable of probabilistic characterization of uncertainty have a limited applicability in practice as the number of strains in a data set increases. Results: We introduce a Bayesian spatial structural model representing the continuum of origins over sites within the observed sequences, including a probabilistic characterization of uncertainty related to the origin of any particular site. To enable a statistically accurate and practically feasible approach to the analysis of large-scale data sets representing a single genus, we have developed a novel software tool (BRAT, Bayesian Recombination Tracker) implementing the model and the corresponding learning algorithm, which is capable of identifying the posterior optimal structure and to estimate the marginal posterior probabilities of putative origins over the sites. Conclusion: A multitude of challenging simulation scenarios and an analysis of real data from seven housekeeping genes of 120 strains of genus Burkholderia are used to illustrate the possibilities offered by our approach. The software is freely available for download at URL http://web.abo.fi/fak/ mnf//mate/jc/software/brat.html

Genome Trees from Conservation Profiles

The concept of the genome tree depends on the potential evolutionary significance in the clustering of species according to similarities in the gene content of their genomes. In this respect, genome trees have often been identified with species trees. With the rapid expansion of genome sequence data it becomes of increasing importance to develop accurate methods for grasping global trends for the phylogenetic signals that mutually link the various genomes. We therefore derive here the methodological concept of genome trees based on protein conservation profiles in multiple species. The basic idea in this derivation is that the multi-component “presence-absence” protein conservation profiles permit tracking of common evolutionary histories of genes across multiple genomes. We show that a significant reduction in informational redundancy is achieved by considering only the subset of distinct conservation profiles. Beyond these basic ideas, we point out various pitfalls and limitations associated with the data handling, paving the way for further improvements. As an illustration for the methods, we analyze a genome tree based on the above principles, along with a series of other trees derived from the same data and based on pair-wise comparisons (ancestral duplication-conservation and shared orthologs). In all trees we observe a sharp discrimination between the three primary domains of life: Bacteria, Archaea, and Eukarya. The new genome tree, based on conservation profiles, displays a significant correspondence with classically recognized taxonomical groupings, along with a series of departures from such conventional clusterings