Sparse approximation for t-statistics

In the signal plus noise model, it is of interest to quantify the evidence that a signal is active given conditionally independent replicate observations $Y_j = X + \varepsilon_j$ on the signal $X$ at a particular site. We study the problem in which the signal distribution is sparse, and the error distribution has an unknown variance so that the null distribution of the standardized statistic is Student-$t$. The main contribution of this paper is a sparse-mixture approximation to the non-null marginal density of the $t$-ratio. This formula demonstrates the effect of low degrees of freedom on the Bayes factor, or the conditional probability that the site is active. We illustrate some differences on a HIV dataset for gene-expression data previously analyzed by Efron, 2012

DLSITE-1: lexical analysis for solving textual entailment recognition

This paper discusses the recognition of textual entailment in a text-hypothesis pair by applying a wide variety of lexical measures. We consider that the entailment phenomenon can be tackled from three general levels: lexical, syntactic and semantic. The main goals of this research are to deal with this phenomenon from a lexical point of view, and achieve high results considering only such kind of knowledge. To accomplish this, the information provided by the lexical measures is used as a set of features for a Support Vector Machine which will decide if the entailment relation is produced. A study of the most relevant features and a comparison with the best state-of-the-art textual entailment systems is exposed throughout the paper. Finally, the system has been evaluated using the Second PASCAL Recognising Textual Entailment Challenge data and evaluation methodology, obtaining an accuracy rate of 61.88%.QALL-ME consortium, 6º Programa Marco, Unión Europea, referencia del proyecto FP6-IST-033860. Gobierno de España, proyecto CICyT número TIN2006-1526-C06-01

A perspective-based approach for solving textual entailment recognition

The textual entailment recognition system that we discuss in this paper represents a perspective-based approach composed of two modules that analyze text-hypothesis pairs from a strictly lexical and syntactic perspectives, respectively. We attempt to prove that the textual entailment recognition task can be overcome by performing individual analysis that acknowledges us of the maximum amount of information that each single perspective can provide. We compare this approach with the system we presented in the previous edition of PASCAL Recognising Textual Entailment Challenge, obtaining an accuracy rate 17.98% higher.QALL-ME consortium, 6º Programa Marco, Unión Europea, referencia del proyecto FP6-IST-033860. Gobierno de España, proyecto CICyT número TIN2006-1526-C06-01. Generalitat Valenciana, proyecto ACOM06/90

Next-generation forward genetic screens: using simulated data to improve the design of mapping-by-sequencing experiments in Arabidopsis

Forward genetic screens have successfully identified many genes and continue to be powerful tools for dissecting biological processes in Arabidopsis and other model species. Next-generation sequencing technologies have revolutionized the time-consuming process of identifying the mutations that cause a phenotype of interest. However, due to the cost of such mapping-by-sequencing experiments, special attention should be paid to experimental design and technical decisions so that the read data allows to map the desired mutation. Here, we simulated different mapping-by-sequencing scenarios. We first evaluated which short-read technology was best suited for analyzing gene-rich genomic regions in Arabidopsis and determined the minimum sequencing depth required to confidently call single nucleotide variants. We also designed ways to discriminate mutagenesis-induced mutations from background Single Nucleotide Polymorphisms in mutants isolated in Arabidopsis non-reference lines. In addition, we simulated bulked segregant mapping populations for identifying point mutations and monitored how the size of the mapping population and the sequencing depth affect mapping precision. Finally, we provide the computational basis of a protocol that we already used to map T-DNA insertions with paired-end Illumina-like reads, using very low sequencing depths and pooling several mutants together; this approach can also be used with single-end reads as well as to map any other insertional mutagen. All these simulations proved useful for designing experiments that allowed us to map several mutations in Arabidopsis

Constraining quantum collapse inflationary models with current data: the semiclassical approach

The hypothesis of the self-induced collapse of the inflaton wave function was introduced as a candidate for the physical process responsible for the emergence of inhomogeneity and anisotropy at all scales. In particular, we consider different proposal for the precise form of the dynamics of the inflaton wave function: (i) the GRW-type collapse schemes proposals based on spontaneous individual collapses which generate nonvanishing expectation values of various physical quantities taken as ansatz modifications of the standard inflationary scenario; (ii) the proposal based on a Continuous Spontaneous Localization (CSL) type modification of the Schrödinger evolution of the inflaton wave function, based on a natural choice of collapse operator. We perform a systematic analysis within the semi-classical gravity approximation, of the standing of those models considering a full quasi-de Sitter expansion scenario. We note that the predictions for the Cosmic Microwave Background (CMB) temperature and polarization spectrum differ slightly from those of the standard cosmological model. We also analyze these proposals with a Bayesian model comparison using recent CMB and Baryonic Acoustic Oscillations (BAO) data. Our results show a moderate preference of the joint CMB and BAO data for one of the studied collapse schemes model over the ACDM one, while there is no preference when only CMB data are considered. Additionally, analysis using CMB data provide the same Bayesian evidence for both the CSL and Standard Models, i.e. the data have no preference between the simplicity of the LCDM model and the complexity of the collapse scenario.Facultad de Ciencias Astronómicas y Geofísica

Constraining quantum collapse inflationary models with current data: the semiclassical approach

The hypothesis of the self-induced collapse of the inflaton wave function was introduced as a candidate for the physical process responsible for the emergence of inhomogeneity and anisotropy at all scales. In particular, we consider different proposal for the precise form of the dynamics of the inflaton wave function: (i) the GRW-type collapse schemes proposals based on spontaneous individual collapses which generate nonvanishing expectation values of various physical quantities taken as ansatz modifications of the standard inflationary scenario; (ii) the proposal based on a Continuous Spontaneous Localization (CSL) type modification of the Schrödinger evolution of the inflaton wave function, based on a natural choice of collapse operator. We perform a systematic analysis within the semi-classical gravity approximation, of the standing of those models considering a full quasi-de Sitter expansion scenario. We note that the predictions for the Cosmic Microwave Background (CMB) temperature and polarization spectrum differ slightly from those of the standard cosmological model. We also analyze these proposals with a Bayesian model comparison using recent CMB and Baryonic Acoustic Oscillations (BAO) data. Our results show a moderate preference of the joint CMB and BAO data for one of the studied collapse schemes model over the ACDM one, while there is no preference when only CMB data are considered. Additionally, analysis using CMB data provide the same Bayesian evidence for both the CSL and Standard Models, i.e. the data have no preference between the simplicity of the LCDM model and the complexity of the collapse scenario.Facultad de Ciencias Astronómicas y Geofísica

Aplicación de Técnicas de Recuperación de Información a la Generación de Conjuntos Filtrados de Documentos para la Detección de Plagios Externos

En este artículo presentamos un método para la generación de conjuntos filtrados de documentos empleando técnicas de recuperación de información. Esto se presenta en el contexto de la detección de plagios externos, aunque las técnicas detalladas en este artículo son aplicables a cualquier tipo de documentos o consultas. La producción de conjuntos filtrados, y por ende la limitación del espacio de búsqueda del problema, puede resultar en una gran mejora de rendimiento y es utilizada hoy en día en gran cantidad de aplicaciones reales, como buscadores web. Respecto a la detección de plagios en documentos, la base de datos de textos con los que comparar el candidato sospechoso es potencialmente grande, y por lo tanto es muy recomendable aplicar técnicas de generación de conjuntos filtrados.In this paper we present an approach to generate document filtered sets using information retrieval techniques. This is presented in the context of external document plagiarism detection, although the techniques detailed in this paper are applicable to any sort of documents or queries. Producing filtered sets, and hence limiting the problem's search space, can be a tremendous performance improvement and is used today in many real world applications such as web search engines. With regards to document plagiarism detection, the database of documents to match the suspicious candidate against is potentially fairly large, and hence it becomes very recommendable to apply filtered set generation techniques.This research has been partially funded by the Spanish Ministry of Science and Innovation (grant TIN2009-13391-C04-01), the Conselleria d'Educació of the Spanish Generalitat Valenciana (grants PROMETEO/2009/119 and ACOMP/2010/286), and the University of Alicante post-doctoral fellowship program funded by Fundación CajaMurcia

Molecular characterization of the transcription termination factor from human mitochondria

The transcription termination factor (mTERF), which plays a central role in the control of mitochondrial rRNA and mRNA synthesis in mammalian mitochondria, has been previously identified and purified by DNA affinity chromatography from a human mitochondrial lysate (Kruse, B., Narasimhan, N., and Attardi, G. (1989) Cell 58, 391-397). In the present work, this factor has been characterized as to its protein composition and the activities of the protein components. Three polypeptides, two of approximately 34-kDa molecular mass and one of approximately 31 kDa, were shown to be associated with the specific DNA binding and footprinting activity of the factor, with the 31-kDa component having a much lower affinity for the recognition sequence than the 34-kDa components. On the other hand, the transcription termination activity, as assayed in an in vitro system, was found to be associated exclusively with the two 34-kDa polypeptides. Mass spectroscopic analysis of tryptic peptides derived from highly purified polypeptides indicated that all three polypeptides share regions with common sequences. The evidence obtained suggests that differential phosphorylation is not responsible for the difference in electrophoretic mobility of the three polypeptides