Insularity and the evolution of melanism, sexual dichromatism and body size in the worldwide-distributed barn owl.

Abstract Island biogeography has provided fundamental hypotheses in population genetics, ecology and evolutionary biology. Insular populations usually face different feeding conditions, predation pressure, intraspecific and interspecific competition than continental populations. This so-called island syndrome can promote the evolution of specific phenotypes like a small (or large) body size and a light (or dark) colouration as well as influence the evolution of sexual dimorphism. To examine whether insularity leads to phenotypic differentiation in a consistent way in a worldwide-distributed nonmigratory species, we compared body size, body shape and colouration between insular and continental barn owl (Tyto alba) populations by controlling indirectly for phylogeny. This species is suitable because it varies in pheomelanin-based colouration from reddish-brown to white, and it displays eumelanic black spots for which the number and size vary between individuals, populations and species. Females are on average darker pheomelanic and display more and larger eumelanic spots than males. Our results show that on islands barn owls exhibited smaller and fewer eumelanic spots and lighter pheomelanic colouration, and shorter wings than on continents. Sexual dimorphism in pheomelanin-based colouration was less pronounced on islands than continents (i.e. on islands males tended to be as pheomelanic as females), and on small islands owls were redder pheomelanic and smaller in size than owls living on larger islands. Sexual dimorphism in the size of eumelanic spots was more pronounced (i.e. females displayed much larger spots than males) in barn owls living on islands located further away from a continent. Our study indicates that insular conditions drive the evolution towards a lower degree of eumelanism, smaller body size and affects the evolution of sexual dichromatism in melanin-based colour traits. The effect of insularity was more pronounced on body size and shape than on melanic traits.

ABS: a database of Annotated regulatory Binding Sites from orthologous promoters

Information about the genomic coordinates and the sequence of experimentally identified transcription factor binding sites is found scattered under a variety of diverse formats. The availability of standard collections of such high-quality data is important to design, evaluate and improve novel computational approaches to identify binding motifs on promoter sequences from related genes. ABS (http://genome.imim.es/datasets/abs2005/index.html) is a public database of known binding sites identified in promoters of orthologous vertebrate genes that have been manually curated from bibliography. We have annotated 650 experimental binding sites from 68 transcription factors and 100 orthologous target genes in human, mouse, rat or chicken genome sequences. Computational predictions and promoter alignment information are also provided for each entry. A simple and easy-to-use web interface facilitates data retrieval allowing different views of the information. In addition, the release 1.0 of ABS includes a customizable generator of artificial datasets based on the known sites contained in the collection and an evaluation tool to aid during the training and the assessment of motif-finding programs.

Automatic filtering and substantiation of drug safety signals

Drug safety issues pose serious health threats to the population and constitute a major cause of mortality worldwide. Due to the prominent implications to both public health and the pharmaceutical industry, it is of great importance to unravel the molecular mechanisms by which an adverse drug reaction can be potentially elicited. These mechanisms can be investigated by placing the pharmaco-epidemiologically detected adverse drug reaction in an information-rich context and by exploiting all currently available biomedical knowledge to substantiate it. We present a computational framework for the biological annotation of potential adverse drug reactions. First, the proposed framework investigates previous evidences on the drug-event association in the context of biomedical literature (signal filtering). Then, it seeks to provide a biological explanation (signal substantiation) by exploring mechanistic connections that might explain why a drug produces a specific adverse reaction. The mechanistic connections include the activity of the drug, related compounds and drug metabolites on protein targets, the association of protein targets to clinical events, and the annotation of proteins (both protein targets and proteins associated with clinical events) to biological pathways. Hence, the workflows for signal filtering and substantiation integrate modules for literature and database mining, in silico drug-target profiling, and analyses based on gene-disease networks and biological pathways. Application examples of these workflows carried out on selected cases of drug safety signals are discussed. The methodology and workflows presented offer a novel approach to explore the molecular mechanisms underlying adverse drug reactions

Gene-disease network analysis reveals functional modules in mendelian, complex and environmental diseases

AbstractBACKGROUND: Scientists have been trying to understand the molecular mechanisms of diseases to design preventive and therapeutic strategies for a long time. For some diseases, it has become evident that it is not enough to obtain a catalogue of the disease-related genes but to uncover how disruptions of molecular networks in the cell give rise to disease phenotypes. Moreover, with the unprecedented wealth of information available, even obtaining such catalogue is extremely difficult.PRINCIPAL FINDINGS: We developed a comprehensive gene-disease association database by integrating associations from several sources that cover different biomedical aspects of diseases. In particular, we focus on the current knowledge of human genetic diseases including mendelian, complex and environmental diseases. To assess the concept of modularity of human diseases, we performed a systematic study of the emergent properties of human gene-disease networks by means of network topology and functional annotation analysis. The results indicate a highly shared genetic origin of human diseases and show that for most diseases, including mendelian, complex and environmental diseases, functional modules exist. Moreover, a core set of biological pathways is found to be associated with most human diseases. We obtained similar results when studying clusters of diseases, suggesting that related diseases might arise due to dysfunction of common biological processes in the cell.CONCLUSIONS: For the first time, we include mendelian, complex and environmental diseases in an integrated gene-disease association database and show that the concept of modularity applies for all of them. We furthermore provide a functional analysis of disease-related modules providing important new biological insights, which might not be discovered when considering each of the gene-disease association repositories independently. Hence, we present a suitable framework for the study of how genetic and environmental factors, such as drugs, contribute to diseases.AVAILABILITY: The gene-disease networks used in this study and part of the analysis are available at http://ibi.imim.es/DisGeNET/DisGeNETweb.html#Download

Improvement of a fully distributed decision making protocol for CRN

Abstract¿La deteción del espectro libre para las comunicaciones inalámbricas en un momento puntual es una tarea compleja cuyo desarrollo se simplica al realizarse de forma distribuida por una red de radio cognitiva. Sin embargo existes dificultades y vulnerabilidades de seguridad que han de ser tenidas en cuenta y solventadas a la hora de autenticar y validar los nodos de la red. Este artículo presenta una propuesta de mejora del protocolo fully distributed decision making protocol for CRN con el fin de llevar a cabo esta tarea de detección del espectro de una manera eficiente y segura.

CleanEx: a database of heterogeneous gene expression data based on a consistent gene nomenclature.

The main goal of CleanEx is to provide access to public gene expression data via unique gene names. A second objective is to represent heterogeneous expression data produced by different technologies in a way that facilitates joint analysis and cross-data set comparisons. A consistent and up-to-date gene nomenclature is achieved by associating each single experiment with a permanent target identifier consisting of a physical description of the targeted RNA population or the hybridization reagent used. These targets are then mapped at regular intervals to the growing and evolving catalogues of human genes and genes from model organisms. The completely automatic mapping procedure relies partly on external genome information resources such as UniGene and RefSeq. The central part of CleanEx is a weekly built gene index containing cross-references to all public expression data already incorporated into the system. In addition, the expression target database of CleanEx provides gene mapping and quality control information for various types of experimental resource, such as cDNA clones or Affymetrix probe sets. The web-based query interfaces offer access to individual entries via text string searches or quantitative expression criteria. CleanEx is accessible at: http://www.cleanex.isb-sib.ch/.

Development of LRFD Procedures for Bridge Pile Foundations in Iowa, Volume I: An Electronic Database for PIle LOad Tests (PILOT), TR-573, 2011

For well over 100 years, the Working Stress Design (WSD) approach has been the traditional basis for geotechnical design with regard to settlements or failure conditions. However, considerable effort has been put forth over the past couple of decades in relation to the adoption of the Load and Resistance Factor Design (LRFD) approach into geotechnical design. With the goal of producing engineered designs with consistent levels of reliability, the Federal Highway Administration (FHWA) issued a policy memorandum on June 28, 2000, requiring all new bridges initiated after October 1, 2007, to be designed according to the LRFD approach. Likewise, regionally calibrated LRFD resistance factors were permitted by the American Association of State Highway and Transportation Officials (AASHTO) to improve the economy of bridge foundation elements. Thus, projects TR-573, TR-583 and TR-584 were undertaken by a research team at Iowa State University’s Bridge Engineering Center with the goal of developing resistance factors for pile design using available pile static load test data. To accomplish this goal, the available data were first analyzed for reliability and then placed in a newly designed relational database management system termed PIle LOad Tests (PILOT), to which this first volume of the final report for project TR-573 is dedicated. PILOT is an amalgamated, electronic source of information consisting of both static and dynamic data for pile load tests conducted in the State of Iowa. The database, which includes historical data on pile load tests dating back to 1966, is intended for use in the establishment of LRFD resistance factors for design and construction control of driven pile foundations in Iowa. Although a considerable amount of geotechnical and pile load test data is available in literature as well as in various State Department of Transportation files, PILOT is one of the first regional databases to be exclusively used in the development of LRFD resistance factors for the design and construction control of driven pile foundations. Currently providing an electronically organized assimilation of geotechnical and pile load test data for 274 piles of various types (e.g., steel H-shaped, timber, pipe, Monotube, and concrete), PILOT (http://srg.cce.iastate.edu/lrfd/) is on par with such familiar national databases used in the calibration of LRFD resistance factors for pile foundations as the FHWA’s Deep Foundation Load Test Database. By narrowing geographical boundaries while maintaining a high number of pile load tests, PILOT exemplifies a model for effective regional LRFD calibration procedures.

Improvement of a fully distributed decision making protocol for CRN

Este artículo presenta una propuesta de mejora del protocolo fully distributed decision making protocol for CRN con el fin de llevar a cabo la tarea de detección del espectro libre para las comunicaciones inalámbricas de una manera eficiente y segura.

A database to aid the identification of chemicals potentially posing a health risk through percutaneous exposure

In the context of recent attempts to redefine the 'skin notation' concept, a position paper summarizing an international workshop on the topic stated that the skin notation should be a hazard indicator related to the degree of toxicity and the potential for transdermal exposure of a chemical. Within the framework of developing a web-based tool integrating this concept, we constructed a database of 7101 agents for which a percutaneous permeation constant can be estimated (using molecular weight and octanol-water partition constant), and for which at least one of the following toxicity indices could be retrieved: Inhalation occupational exposure limit (n=644), Oral lethal dose 50 (LD50, n=6708), cutaneous LD50 (n=1801), Oral no observed adverse effect level (NOAEL, n=1600), and cutaneous NOAEL (n=187). Data sources included the Registry of toxic effects of chemical substances (RTECS, MDL information systems, Inc.), PHYSPROP (Syracuse Research Corp.) and safety cards from the International Programme on Chemical Safety (IPCS). A hazard index, which corresponds to the product of exposure duration and skin surface exposed that would yield an internal dose equal to a toxic reference dose was calculated. This presentation provides a descriptive summary of the database, correlations between toxicity indices, and an example of how the web tool will help industrial hygienist decide on the possibility of a dermal risk using the hazard index.

Functions for estimating stem diameter and tree age using tree height, crown width and existing stand database information

Abstract

The Quaternary Active Faults Database of Iberia (QAFI v.2.0)

The Quaternary Active Faults Database of Iberia (QAFI) is an initiative lead by the Institute of Geology and Mines of Spain (IGME) for building a public repository of scientific data regarding faults having documented activity during the last 2.59 Ma (Quaternary). QAFI also addresses a need to transfer geologic knowledge to practitioners of seismic hazard and risk in Iberia by identifying and characterizing seismogenic fault-sources. QAFI is populated by the information freely provided by more than 40 Earth science researchers, storing to date a total of 262 records. In this article we describe the development and evolution of the database, as well as its internal architecture. Aditionally, a first global analysis of the data is provided with a special focus on length and slip-rate fault parameters. Finally, the database completeness and the internal consistency of the data are discussed. Even though QAFI v.2.0 is the most current resource for calculating fault-related seismic hazard in Iberia, the database is still incomplete and requires further review.