Identification of plasmodium vivax proteins with potential role in invasion using sequence redundancy reduction and profile hidden markov models

Background: This study describes a bioinformatics approach designed to identify Plasmodium vivax proteins potentially involved in reticulocyte invasion. Specifically, different protein training sets were built and tuned based on different biological parameters, such as experimental evidence of secretion and/or involvement in invasion-related processes. A profile-based sequence method supported by hidden Markov models (HMMs) was then used to build classifiers to search for biologically-related proteins. The transcriptional profile of the P. vivax intra-erythrocyte developmental cycle was then screened using these classifiers. Results: A bioinformatics methodology for identifying potentially secreted P. vivax proteins was designed using sequence redundancy reduction and probabilistic profiles. This methodology led to identifying a set of 45 proteins that are potentially secreted during the P. vivax intra-erythrocyte development cycle and could be involved in cell invasion. Thirteen of the 45 proteins have already been described as vaccine candidates; there is experimental evidence of protein expression for 7 of the 32 remaining ones, while no previous studies of expression, function or immunology have been carried out for the additional 25. Conclusions: The results support the idea that probabilistic techniques like profile HMMs improve similarity searches. Also, different adjustments such as sequence redundancy reduction using Pisces or Cd-Hit allowed data clustering based on rational reproducible measurements. This kind of approach for selecting proteins with specific functions is highly important for supporting large-scale analyses that could aid in the identification of genes encoding potential new target antigens for vaccine development and drug design. The present study has led to targeting 32 proteins for further testing regarding their ability to induce protective immune responses against P. vivax malaria.

Hidden gold.

Diseñado para proporcionar un fácil apoyo para los alumnos que necesitan para ganar la confianza y la motivación en su lectura. La historia trata de un grupo de amigos que viven y asisten a la escuela en una zona llamada Wolf Hill. Además de las divertidas aventuras, la historia también se ocupa de cuestiones sobre la amistad, la escuela y la vida en un moderno entorno urbano. Diseñada en capítulos, para que parezca novela popular para niños mayores, y así aumentar la confianza y el interés de aquellos que pueden gustarles la lectura de historias destinadas a los niños más pequeños. Loz y sus amigos encuentran algunas monedas antiguas en un escondite secreto y quieren saber si tienen valor.

Helping immigrants identify as 'university-bound students' : unexpected difficulties in teaching the hidden curriculum. 'Ayudar a los inmigrantes a identificarse como 'estudiantes con destino a la universidad' : dificultades inesperadas en la enseñanza del currículo oculto'.

Monográfico con el título: 'Identidad y educación'. Resumen basado en el de la publicación

Sistema de reserves hoteleres on-line, basat en el protocol de comunicació OTA

L’origen d’aquest projecte neix en la necessitat de crear un sistema de reserves hoteleres on-line integral i amb connectivitat amb altres sistemes de reserves. S'ha optat pel protocol de comunicació OTA(Open Travel Alliance), es tracta d'un protocol de comunicació XML ideat per empreses del sector turístic dels Estats Units per la necessitat comuna d’unes especificacions tècniques que permetessin la comunicació electrònica de la informació

A covariate adjustment for zero-truncated approaches to estimating the size of hidden and elusive populations

In this paper we consider the estimation of population size from onesource capture–recapture data, that is, a list in which individuals can potentially be found repeatedly and where the question is how many individuals are missed by the list. As a typical example, we provide data from a drug user study in Bangkok from 2001 where the list consists of drug users who repeatedly contact treatment institutions. Drug users with 1, 2, 3, . . . contacts occur, but drug users with zero contacts are not present, requiring the size of this group to be estimated. Statistically, these data can be considered as stemming from a zero-truncated count distribution.We revisit an estimator for the population size suggested by Zelterman that is known to be robust under potential unobserved heterogeneity. We demonstrate that the Zelterman estimator can be viewed as a maximum likelihood estimator for a locally truncated Poisson likelihood which is equivalent to a binomial likelihood. This result allows the extension of the Zelterman estimator by means of logistic regression to include observed heterogeneity in the form of covariates. We also review an estimator proposed by Chao and explain why we are not able to obtain similar results for this estimator. The Zelterman estimator is applied in two case studies, the first a drug user study from Bangkok, the second an illegal immigrant study in the Netherlands. Our results suggest the new estimator should be used, in particular, if substantial unobserved heterogeneity is present.

Estimating the hidden number of scrapie affected holdings in great Britain using a simple, truncated count model allowing for heterogeneity.

None of the current surveillance streams monitoring the presence of scrapie in Great Britain provide a comprehensive and unbiased estimate of the prevalence of the disease at the holding level. Previous work to estimate the under-ascertainment adjusted prevalence of scrapie in Great Britain applied multiple-list capture–recapture methods. The enforcement of new control measures on scrapie-affected holdings in 2004 has stopped the overlapping between surveillance sources and, hence, the application of multiple-list capture–recapture models. Alternative methods, still under the capture–recapture methodology, relying on repeated entries in one single list have been suggested in these situations. In this article, we apply one-list capture–recapture approaches to data held on the Scrapie Notifications Database to estimate the undetected population of scrapie-affected holdings with clinical disease in Great Britain for the years 2002, 2003, and 2004. For doing so, we develop a new diagnostic tool for indication of heterogeneity as well as a new understanding of the Zelterman and Chao’s lower bound estimators to account for potential unobserved heterogeneity. We demonstrate that the Zelterman estimator can be viewed as a maximum likelihood estimator for a special, locally truncated Poisson likelihood equivalent to a binomial likelihood. This understanding allows the extension of the Zelterman approach by means of logistic regression to include observed heterogeneity in the form of covariates—in case studied here, the holding size and country of origin. Our results confirm the presence of substantial unobserved heterogeneity supporting the application of our two estimators. The total scrapie-affected holding population in Great Britain is around 300 holdings per year. None of the covariates appear to inform the model significantly.

Gold mining in Ghana's forest reserves: a report on the current debate

This paper examines the debate surrounding a recent decision made by the Ghanaian government to permit gold exploration - and potentially, mining - in 'protected' forest reserves. In 2001, four mining companies were awarded mineral exploration concessions in forested regions of the country, and have since put forward applications to mine for gold. Notwithstanding the sharp divide in opinion on the issue, the continued uncertainty surrounding the implications of the proposed activities makes further research on the ground imperative in the short term. Work aiming to elicit indigenous perspectives on the projects, as well as research that facilitates dialogue between and/or among stakeholder parties, should be prioritized.

Estimating the hidden number of scrapie affected holdings in great Britain using a simple, truncated count model allowing for heterogeneity

None of the current surveillance streams monitoring the presence of scrapie in Great Britain provide a comprehensive and unbiased estimate of the prevalence of the disease at the holding level. Previous work to estimate the under-ascertainment adjusted prevalence of scrapie in Great Britain applied multiple-list capture-recapture methods. The enforcement of new control measures on scrapie-affected holdings in 2004 has stopped the overlapping between surveillance sources and, hence, the application of multiple-list capture-recapture models. Alternative methods, still under the capture-recapture methodology, relying on repeated entries in one single list have been suggested in these situations. In this article, we apply one-list capture-recapture approaches to data held on the Scrapie Notifications Database to estimate the undetected population of scrapie-affected holdings with clinical disease in Great Britain for the years 2002, 2003, and 2004. For doing so, we develop a new diagnostic tool for indication of heterogeneity as well as a new understanding of the Zelterman and Chao's lower bound estimators to account for potential unobserved heterogeneity. We demonstrate that the Zelterman estimator can be viewed as a maximum likelihood estimator for a special, locally truncated Poisson likelihood equivalent to a binomial likelihood. This understanding allows the extension of the Zelterman approach by means of logistic regression to include observed heterogeneity in the form of covariates-in case studied here, the holding size and country of origin. Our results confirm the presence of substantial unobserved heterogeneity supporting the application of our two estimators. The total scrapie-affected holding population in Great Britain is around 300 holdings per year. None of the covariates appear to inform the model significantly.

Detecting recombination in 4-taxa DNA sequence alignments with Bayesian hidden Markov models and Markov chain Monte Carlo

This article presents a statistical method for detecting recombination in DNA sequence alignments, which is based on combining two probabilistic graphical models: (1) a taxon graph (phylogenetic tree) representing the relationship between the taxa, and (2) a site graph (hidden Markov model) representing interactions between different sites in the DNA sequence alignments. We adopt a Bayesian approach and sample the parameters of the model from the posterior distribution with Markov chain Monte Carlo, using a Metropolis-Hastings and Gibbs-within-Gibbs scheme. The proposed method is tested on various synthetic and real-world DNA sequence alignments, and we compare its performance with the established detection methods RECPARS, PLATO, and TOPAL, as well as with two alternative parameter estimation schemes.

Estimation of Hidden Markov Models parameters using differential evolution

Hidden Markov Models (HMMs) have been successfully applied to different modelling and classification problems from different areas over the recent years. An important step in using HMMs is the initialisation of the parameters of the model as the subsequent learning of HMM’s parameters will be dependent on these values. This initialisation should take into account the knowledge about the addressed problem and also optimisation techniques to estimate the best initial parameters given a cost function, and consequently, to estimate the best log-likelihood. This paper proposes the initialisation of Hidden Markov Models parameters using the optimisation algorithm Differential Evolution with the aim to obtain the best log-likelihood.

Assessing the date of the global oil peak: the need to use 2P reserves

Combining geological knowledge with proved plus probable ('2P') oil discovery data indicates that over 60 countries are now past their resource-limited peak of conventional oil production. The data show that the global peak of conventional oil production is close. Many analysts who rely only on proved ('1P') oil reserves data draw a very different conclusion. But proved oil reserves contain no information about the true size of discoveries, being variously under-reported, over-reported and not reported. Reliance on 1P data has led to a number of misconceptions, including the notion that past oil forecasts were incorrect, that oil reserves grow very significantly due to technology gain, and that the global supply of oil is ensured provided sufficient investment is forthcoming to 'turn resources into reserves'. These misconceptions have been widely held, including within academia, governments, some oil companies, and organisations such as the IEA. In addition to conventional oil, the world contains large quantities of non-conventional oil. Most current detailed models show that past the conventional oil peak the non-conventional oils are unlikely to come on-stream fast enough to offset conventional's decline. To determine the extent of future oil supply constraints calculations are required to determine fundamental rate limits for the production of non-conventional oils, as well as oil from gas, coal and biomass, and of oil substitution. Such assessments will need to examine technological readiness and lead-times, as well as rate constraints on investment, pollution, and net-energy return. (C) 2007 Elsevier Ltd. All rights reserved.