Edgar Leon Udwin
Ontology highlight
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PROVIDER: S-EPMC1125007 | biostudies-literature | 2003 Jan
REPOSITORIES: biostudies-literature
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Project description:The preservation and understanding of cultural heritage depends increasingly on in-depth chemical studies. Rapid technological advances are forging connections between scientists and arts communities, enabling revolutionary new techniques for non-invasive technical study of culturally significant, highly prized artworks. We have applied a non-invasive, rapid, high definition X-ray fluorescence (XRF) elemental mapping technique to a French Impressionist painting using a synchrotron radiation source, and show how this technology can advance scholarly art interpretation and preservation. We have obtained detailed technical understanding of a painting which could not be resolved by conventional techniques. Here we show 31.6 megapixel scanning XRF derived elemental maps and report a novel image processing methodology utilising these maps to produce a false colour representation of a "hidden" portrait by Edgar Degas. This work provides a cohesive methodology for both imaging and understanding the chemical composition of artworks, and enables scholarly understandings of cultural heritage, many of which have eluded conventional technologies. We anticipate that the outcome from this work will encourage the reassessment of some of the world's great art treasures.
| S-EPMC4973632 | biostudies-literature
Project description:Sequence alignments are fundamental to a wide range of applications, including database searching, functional residue identification and structure prediction techniques. These applications predict or propagate structural/functional/evolutionary information based on a presumed homology between the aligned sequences. If the initial hypothesis of homology is wrong, no subsequent application, however sophisticated, can be expected to yield accurate results. Here we present a novel method, LEON, to predict homology between proteins based on a multiple alignment of complete sequences (MACS). In MACS, weak signals from distantly related proteins can be considered in the overall context of the family. Intermediate sequences and the combination of individual weak matches are used to increase the significance of low-scoring regions. Residue composition is also taken into account by incorporation of several existing methods for the detection of compositionally biased sequence segments. The accuracy and reliability of the predictions is demonstrated in large-scale comparisons with structural and sequence family databases, where the specificity was shown to be >99% and the sensitivity was estimated to be approximately 76%. LEON can thus be used to reliably identify the complex relationships between large multidomain proteins and should be useful for automatic high-throughput genome annotations, 2D/3D structure predictions, protein-protein interaction predictions etc.
| S-EPMC390283 | biostudies-literature
Project description: Not available
| S-EPMC4880622 | biostudies-literature
Project description:BackgroundTrough collections of plants and interviews with 110 individuals, an ethnobotanical study was conducted in order to determine the knowledge and use plant species in Rayones, Nuevo Leon, Mexico. The aim of this study was to record all useful plants and their uses, to know whether differences exist in the knowledge about the number of species and uses between women and men, and to know if there is a correlation between the age of individuals and knowledge of species and their uses.MethodsA total of 110 persons were interviewed (56 men, 56 women). Semistructured interviews were carried out. The data were analyzed by means of Student t test and the Pearson Correlation Coeficient.ResultsA total of 252 species, 228 genera and 91 families of vascular plants were recorded. Astraceae, Fabaceae and are the most important families with useful species and Agave and Opuntia are the genera with the highest number of useful species. One hundred and thirty six species are considered as medicinal. Agave, Acacia and Citrus are the genera with the highest number of medicinal species. Other uses includes edible, spiritual rituals, construction and ornamentals. There was a non-significant correlation between the person's age and number of species, but a significant very low negative correlation between the person's age and number of uses was found.ConclusionsKnowing their medicinal uses is an important issue for the people of Rayones. Boiling and preparing infusions are the main ways of using plants by residents. The leaves, the branches, and the fruits are the most commonly used parts. Almost 18% of the flora is used for wood and construction purposes. Several uses such as cosmetic, shampoo, firming skin tonics and health hair products recorded in Rayones has not been reported for other areas in the state of Nuevo León. In Rayones, women have a greater knowledge about plants and their uses than men, particularly, medicinal plants, but, men have a greater knowledge about wood and construction species.
| S-EPMC4237796 | biostudies-literature
Project description:The rapidly increasing availability of microbial genome sequences has led to a growing demand for bioinformatics software tools that support the functional analysis based on the comparison of closely related genomes. By utilizing comparative approaches on gene level it is possible to gain insights into the core genes which represent the set of shared features for a set of organisms under study. Vice versa singleton genes can be identified to elucidate the specific properties of an individual genome. Since initial publication, the EDGAR platform has become one of the most established software tools in the field of comparative genomics. Over the last years, the software has been continuously improved and a large number of new analysis features have been added. For the new version, EDGAR 2.0, the gene orthology estimation approach was newly designed and completely re-implemented. Among other new features, EDGAR 2.0 provides extended phylogenetic analysis features like AAI (Average Amino Acid Identity) and ANI (Average Nucleotide Identity) matrices, genome set size statistics and modernized visualizations like interactive synteny plots or Venn diagrams. Thereby, the software supports a quick and user-friendly survey of evolutionary relationships between microbial genomes and simplifies the process of obtaining new biological insights into their differential gene content. All features are offered to the scientific community via a web-based and therefore platform-independent user interface, which allows easy browsing of precomputed datasets. The web server is accessible at http://edgar.computational.bio.
| S-EPMC4987874 | biostudies-literature
Project description:BackgroundGenetic investigations, boosted by modern sequencing techniques, allow dissecting the genetic component of different phenotypic traits. These efforts result in the compilation of lists of genes related to diseases and show that an increasing number of diseases is associated with multiple genes. Investigating functional relations among genes associated with the same disease contributes to highlighting molecular mechanisms of the pathogenesis.ResultsWe present eDGAR, a database collecting and organizing the data on gene/disease associations as derived from OMIM, Humsavar and ClinVar. For each disease-associated gene, eDGAR collects information on its annotation. Specifically, for lists of genes, eDGAR provides information on: i) interactions retrieved from PDB, BIOGRID and STRING; ii) co-occurrence in stable and functional structural complexes; iii) shared Gene Ontology annotations; iv) shared KEGG and REACTOME pathways; v) enriched functional annotations computed with NET-GE; vi) regulatory interactions derived from TRRUST; vii) localization on chromosomes and/or co-localisation in neighboring loci. The present release of eDGAR includes 2672 diseases, related to 3658 different genes, for a total number of 5729 gene-disease associations. 71% of the genes are linked to 621 multigenic diseases and eDGAR highlights their common GO terms, KEGG/REACTOME pathways, physical and regulatory interactions. eDGAR includes a network based enrichment method for detecting statistically significant functional terms associated to groups of genes.ConclusionseDGAR offers a resource to analyze disease-gene associations. In multigenic diseases genes can share physical interactions and/or co-occurrence in the same functional processes. eDGAR is freely available at: edgar.biocomp.unibo.it.
| S-EPMC5558190 | biostudies-literature