Improved Detection of Remote Homologues Using Cascade PSI-BLAST: Influence of Neighbouring Protein Families on Sequence Coverage

Background: Development of sensitive sequence search procedures for the detection of distant relationships between proteins at superfamily/fold level is still a big challenge. The intermediate sequence search approach is the most frequently employed manner of identifying remote homologues effectively. In this study, examination of serine proteases of prolyl oligopeptidase, rhomboid and subtilisin protein families were carried out using plant serine proteases as queries from two genomes including A. thaliana and O. sativa and 13 other families of unrelated folds to identify the distant homologues which could not be obtained using PSI-BLAST. Methodology/Principal Findings: We have proposed to start with multiple queries of classical serine protease members to identify remote homologues in families, using a rigorous approach like Cascade PSI-BLAST. We found that classical sequence based approaches, like PSI-BLAST, showed very low sequence coverage in identifying plant serine proteases. The algorithm was applied on enriched sequence database of homologous domains and we obtained overall average coverage of 88% at family, 77% at superfamily or fold level along with specificity of similar to 100% and Mathew's correlation coefficient of 0.91. Similar approach was also implemented on 13 other protein families representing every structural class in SCOP database. Further investigation with statistical tests, like jackknifing, helped us to better understand the influence of neighbouring protein families. Conclusions/Significance: Our study suggests that employment of multiple queries of a family for the Cascade PSI-BLAST searches is useful for predicting distant relationships effectively even at superfamily level. We have proposed a generalized strategy to cover all the distant members of a particular family using multiple query sequences. Our findings reveal that prior selection of sequences as query and the presence of neighbouring families can be important for covering the search space effectively in minimal computational time. This study also provides an understanding of the `bridging' role of related families.

Limit laws for coverage in backbone-sensor networks

We study coverage in sensor networks having two types of nodes, namely, sensor nodes and backbone nodes. Each sensor is capable of transmitting information over relatively small distances. The backbone nodes collect information from the sensors. This information is processed and communicated over an ad hoc network formed by the backbone nodes, which are capable of transmitting over much larger distances. We consider two models of deployment for the sensor and backbone nodes. One is a PoissonPoisson cluster model and the other a dependently thinned Poisson point process. We deduce limit laws for functionals of vacancy in both models using properties of association for random measures.

Enhancing Surface Coverage and Growth in Layer-by-Layer Assembly of Protein Nanoparticles

Thin films of bovine serum albumin (BSA) nanoparticles are fabricated via layer-by-layer assembly. The surface of BSA nanoparticles have two oppositely acting functional groups on the surface: amine (NH2) and carboxylate (COO-). The protonation and deprotonation of these functional groups at different pH vary the charge density on the particle surface, and entirely different growth can be observed by varying the nature of the complementary polymer and the pH of the particles. The complementary polymers used in this study are poly(dimethyldiallylammonium chloride) (PDDAC) and poly(acrylic acid) (PAA). The assembly of BSA nanoparticles based on electrostatic interaction with PDDAC suffers from the poor loading of the nanoparticles. The assembly with PAA aided by a hydrogen bonding interaction shows tremendous improvement in the growth of the assembly over PDDAC. Moreover, the pH of the BSA nanoparticles was observed to affect the loading of nanoparticles in the LbL assembly with PAA significantly.

Modifications in Trypsin Digestion Protocol for Increasing the Efficiency and Coverage

Standard trypsin digestion protocol of proteins followed by MALDI-MS analysis has been realized as an important tool for the identification and characterization of proteins. In this article, we proposed the elimination of the step of `staining/de-staining of gel pieces' in in-gel digestion protocol in order to improve the efficiency of trypsin digestion. Coomassie dye is known to interfere with digestion of proteins by trypsin and the procedure of staining-de-staining could result in loss of photoaffinity probe, post translational modifications and catalytic activities of enzymes. Further, we studied parameters like hydrophobicity and isoelectric point, and attempted to quantitatively relate it to the efficiency of trypsin digestion. We suggest that properties of proteins should be considered and trypsin digestion protocol should be appropriately modified as per sequence and other information.

Algorithm for Autonomous Reorganization of Mobile Wireless Camera Sensor Networks to Improve Coverage

In this paper, sensing coverage by wireless camera-embedded sensor networks (WCSNs), a class of directional sensors is studied. The proposed work facilitates the autonomous tuning of orientation parameters and displacement of camera-sensor nodes in the bounded field of interest (FoI), where the network coverage in terms of every point in the FoI is important. The proposed work is first of its kind to study the problem of maximizing coverage of randomly deployed mobile WCSNs which exploits their mobility. We propose an algorithm uncovered region exploration algorithm (UREA-CS) that can be executed in centralized and distributed modes. Further, the work is extended for two special scenarios: 1) to suit autonomous combing operations after initial random WCSN deployments and 2) to improve the network coverage with occlusions in the FoI. The extensive simulation results show that the performance of UREA-CS is consistent, robust, and versatile to achieve maximum coverage, both in centralized and distributed modes. The centralized and distributed modes are further analyzed with respect to the computational and communicational overheads.

Nationwide-US newspaper coverage of handling water contamination : a community structure approach

Resumen: Empleando la teoría de la “estructura comunitaria”, un muestreo de diarios principales en 28 ciudades grandes en Estados Unidos examina la cobertura del tema “El manejo de contaminación de agua y acceso a agua potable”. Mediante el análisis de todos los artículos de más de 250 palabras publicados a través de diez años entre 01/01/2001 y 01/01/2011 (339 artículos), se compararon sistemáticamente características comunitarias y el “Vector Mediático” de Pollock (combinando en un valor dos medidas de contenido: la “prominencia” de un artículo en un periódico con la orientación o tono). Cobertura “favorable”, que apoya la mayor ayuda gubernamental para mejorar el abastecimiento de agua potable, fue vinculada con medidas de “los interesados”, por ejemplo, con el porcentaje de hispanos (r de Pearson = .349, p = .04). El análisis de las medidas y su regresión reveló dos medidas significativas asociadas con apoyo para manejo gubernamental por agua potable: porcentaje de hispanos (12.2% de la varianza), y con porcentaje de ciudadanos de 18-24 años, 16.7%. Inesperadamente, la cobertura de manejo gubernamental para mejorar las existencias de agua potable no fue vinculado ni con medidas de “vulnerabilidad” (pobreza, desempleo) ni con medidas de “estabilidad” (educación, ingreso).

Roaming in the Mobile Internet: when coverage sharing agreements call for regulation

Revised: 2006-06

An update of the J48Consolidated WEKA’s class: CTC algorithm enhanced with the notion of coverage

This document aims to describe an update of the implementation of the J48Consolidated class within WEKA platform. The J48Consolidated class implements the CTC algorithm [2][3] which builds a unique decision tree based on a set of samples. The J48Consolidated class extends WEKA’s J48 class which implements the well-known C4.5 algorithm. This implementation was described in the technical report "J48Consolidated: An implementation of CTC algorithm for WEKA". The main, but not only, change in this update is the integration of the notion of coverage in order to determine the number of samples to be generated to build a consolidated tree. We define coverage as the percentage of examples of the training sample present in –or covered by– the set of generated subsamples. So, depending on the type of samples that we use, we will need more or less samples in order to achieve a specific value of coverage.