OnTheFly: a tool for automated document-based text annotation, data linking and network generation

OnTheFly is a web-based application that applies biological named entity recognition to enrich Microsoft Office, PDF and plain text documents. The input files are converted into the HTML format and then sent to the Reflect tagging server, which highlights biological entity names like genes, proteins and chemicals, and attaches to them JavaScript code to invoke a summary pop-up window. The window provides an overview of relevant information about the entity, such as a protein description, the domain composition, a link to the 3D structure and links to other relevant online resources. OnTheFly is also able to extract the bioentities mentioned in a set of files and to produce a graphical representation of the networks of the known and predicted associations of these entities by retrieving the information from the STITCH database

Evaluación de Líneas de Sorgo por su Resistencia a la Mosquita, Stenodiplosis sorghicola (Coq.) en Nicaragua

Con el objetivo de evaluar líneas de sorgo por su resistencia a la mosquita, Stenodiplosis sorghicola (Coq.), se introdujo procedente de la Universidad de Texas A amp; M, en el año 2004 un vivero de 64 líneas de sorgo con resistencia a mosquita. Se seleccionaron las mejores 35 por aspecto de planta para sembrarlas nuevamente en 2005. Además en 2005 se introdujo otro vivero de 50 líneas. Los tres viveros se sembraron en surcos de 5 m de largo distribuidos en bloques completos al azar con 3 repeticiones en la época de postrera (Agosto – Diciembre) de 2004 en Santa Rosa y 2005 en CNIA, ambas estaciones experimentales del Instituto Nicaragüense de Tecnología Agropecuaria (INTA). El daño de mosquita se evaluó usando la escala visual para daño elaborada por Frederiksen et al (1981). También las líneas se evaluaron para rendimiento de grano y se tomó datos de días a floración y altura de planta. Los resultados indican que en 2004 Las líneas de mayor rendimiento de grano fueron 02CM1137-BK/LM, 03CM15085-BK, 03CM15038-BK y 03CM15033-BK con 6002, 5194, 5144 y 5066 kg/ha respectivamente y que el daño de mosquita fue muy bajo. En 2005, en la evaluación de 35 líneas seleccionadas en 2004, las de mayor rendimiento fueron 03CM15038-BK, 03CM15033-BK, 03CM15131 y 01LI9278 con 6406, 6396, 6255 y 6215 kg/ha y daño de mosquita de 1.3, 1.0, 1.3 y 1.0 respectivamente. El daño de mosquita fue severo y algunas líneas no produjeron grano. El menor rendimiento se encontró en la línea 01LI9275 con 280 kg/ha y daño de 8.3. En el vivero nuevo introducido en 2005 las líneas de mayor rendimiento fueron 05:03CM15087-BK, 05:04LI4366, 05:00LI1324 y 05LI4042,43 con 7915, 7238, 6625 y 5088 kg/ha respectivamente y daño de mosquita de 1.0 en las primeras tres líneas y 2.0 en la cuarta. En este vivero, la línea 05:04LI4015,16 no produjo grano y el daño fue de 9.0

Losses in pendular suspensions due to centrifugal coupling

We present an analysis of the centrifugal coupling of a simple pendulum to a dissipative support. We show that such a coupling leads to an amplitude dependent quality factor. For amplitudes which could be present in laser interferometer gravitational wave detector suspensions, this mechanism could limit the quality factor of the test mass suspension significantly to 1010 and should be considered in the design of advanced LIGO type detectors

Functional classification of proteins based on projection of amino acid sequences: application for prediction of protein kinase substrates

<p>Abstract</p> <p>Background</p> <p>The knowledge about proteins with specific interaction capacity to the protein partners is very important for the modeling of cell signaling networks. However, the experimentally-derived data are sufficiently not complete for the reconstruction of signaling pathways. This problem can be solved by the network enrichment with predicted protein interactions. The previously published <it>in silico </it>method PAAS was applied for prediction of interactions between protein kinases and their substrates.</p> <p>Results</p> <p>We used the method for recognition of the protein classes defined by the interaction with the same protein partners. 1021 protein kinase substrates classified by 45 kinases were extracted from the Phospho.ELM database and used as a training set. The reasonable accuracy of prediction calculated by leave-one-out cross validation procedure was observed in the majority of kinase-specificity classes. The random multiple splitting of the studied set onto the test and training set had also led to satisfactory results. The kinase substrate specificity for 186 proteins extracted from TRANSPATH^®database was predicted by PAAS method. Several kinase-substrate interactions described in this database were correctly predicted. Using the previously developed ExPlain™ system for the reconstruction of signal transduction pathways, we showed that addition of the newly predicted interactions enabled us to find the possible path between signal trigger, TNF-alpha, and its target genes in the cell.</p> <p>Conclusions</p> <p>It was shown that the predictions of protein kinase substrates by PAAS were suitable for the enrichment of signaling pathway networks and identification of the novel signaling pathways. The on-line version of PAAS for prediction of protein kinase substrates is freely available at <url>http://www.ibmc.msk.ru/PAAS/</url>.</p

Fitness Tradeoffs of Antibiotic Resistance in Extraintestinal Pathogenic Escherichia coli

Evolutionary trade-offs occur when selection on one trait has detrimental effects on other traits. In pathogenic microbes, it has been hypothesized that antibiotic resistance trades off with fitness in the absence of antibiotic. Although studies of single resistance mutations support this hypothesis, it is unclear whether trade-offs are maintained over time, due to compensatory evolution and broader effects of genetic background. Here, we leverage natural variation in 39 extraintestinal clinical isolates of Escherichia coli to assess trade-offs between growth rates and resistance to fluoroquinolone and cephalosporin antibiotics. Whole-genome sequencing identifies a broad range of clinically relevant resistance determinants in these strains. We find evidence for a negative correlation between growth rate and antibiotic resistance, consistent with a persistent trade-off bet

Geometric De-noising of Protein-Protein Interaction Networks

Understanding complex networks of protein-protein interactions (PPIs) is one of the foremost challenges of the post-genomic era. Due to the recent advances in experimental bio-technology, including yeast-2-hybrid (Y2H), tandem affinity purification (TAP) and other high-throughput methods for protein-protein interaction (PPI) detection, huge amounts of PPI network data are becoming available. Of major concern, however, are the levels of noise and incompleteness. For example, for Y2H screens, it is thought that the false positive rate could be as high as 64%, and the false negative rate may range from 43% to 71%. TAP experiments are believed to have comparable levels of noise