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ANGIOGENES : knowledge database for protein-coding and noncoding RNA genes in endothelial cells
(2016)
Increasing evidence indicates the presence of long noncoding RNAs (lncRNAs) is specific to various cell types. Although lncRNAs are speculated to be more numerous than protein-coding genes, the annotations of lncRNAs remain primitive due to the lack of well-structured schemes for their identification and description. Here, we introduce a new knowledge database “ANGIOGENES” (http://angiogenes.uni-frankfurt.de) to allow for in silico screening of protein-coding genes and lncRNAs expressed in various types of endothelial cells, which are present in all tissues. Using the latest annotations of protein-coding genes and lncRNAs, publicly-available RNA-seq data was analyzed to identify transcripts that are expressed in endothelial cells of human, mouse and zebrafish. The analyzed data were incorporated into ANGIOGENES to provide a one-stop-shop for transcriptomics data to facilitate further biological validation. ANGIOGENES is an intuitive and easy-to-use database to allow in silico screening of expressed, enriched and/or specific endothelial transcripts under various conditions. We anticipate that ANGIOGENES serves as a starting point for functional studies to elucidate the roles of protein-coding genes and lncRNAs in angiogenesis.
Interest to become a data scientist or related professions in data science domain is rapidly growing. To meet such a demand, we propose a novel educational service that aims to provide tailored learning paths for data science. Our target user is one who aims to be an expert in data science. Our approach is to analyze the background of the practitioner and match the learning units. A critical feature is that we use gamification to reinforce the practitioner engagement. We believe that our work provides a practical guideline for those who want to learn data science.
Video and image data are regularly used in the field of benthic ecology to document biodiversity. However, their use is subject to a number of challenges, principally the identification of taxa within the images without associated physical specimens. The challenge of applying traditional taxonomic keys to the identification of fauna from images has led to the development of personal, group, or institution level reference image catalogues of operational taxonomic units (OTUs) or morphospecies. Lack of standardisation among these reference catalogues has led to problems with observer bias and the inability to combine datasets across studies. In addition, lack of a common reference standard is stifling efforts in the application of artificial intelligence to taxon identification. Using the North Atlantic deep sea as a case study, we propose a database structure to facilitate standardisation of morphospecies image catalogues between research groups and support future use in multiple front-end applications. We also propose a framework for coordination of international efforts to develop reference guides for the identification of marine species from images. The proposed structure maps to the Darwin Core standard to allow integration with existing databases. We suggest a management framework where high-level taxonomic groups are curated by a regional team, consisting of both end users and taxonomic experts. We identify a mechanism by which overall quality of data within a common reference guide could be raised over the next decade. Finally, we discuss the role of a common reference standard in advancing marine ecology and supporting sustainable use of this ecosystem.
This paper describes the ongoing efforts of the authors to present ancient Greek and Roman numismatic data on the public internet, with an emphasis on efforts to integrate information from multiple sources using Linked Data and Semantic Web techniques. By way of very modern metaphor, it is useful to think of coins as intentionally created packages of 'named entities'. Each coin was struck by a particular authority, often at a known site, and coins often make reference to familiar concepts such as deities, historical events, or symbols that were widely recognized in the ancient world. The institutions represented among the authors have deployed search interfaces that allow users to take advantage of this aspect of numismatic databases. The American Numismatic Society's database provides faceted search to its collection of over 550,000 objects. The Portable Antiquities Scheme (PAS) in the UK presents individual finds (and hoards) recorded throughout the country. The Römisch-Germanische Kommission and the University of Frankfurt (DBIS) are developing a prototype metaportal (INTERFACE) that accesses national databases of coin finds held in in Frankfurt, Vienna and Utrecht. Each of these resources is beginning to explore Semantic Web/Linked data approaches so that the role of numismatic standards is immediately coming to the fore. DBIS and INTERFACE are developing a numismatic ontology. At the ANS and PAS, the public database already presents RDF serializations based on Dublin Core. Together, the authors have begun to explore standardization of conceptual names on the basis of the vocabulary presented at the site http://nomisma.org . Nomisma.org is a collaborative effort to provide stable digital representations of numismatic concepts and entities. It provides URIs for such basic concepts as 'coin', 'mint', 'axis'. All of these are defined within the scope of numismatics but are already being linked to other stable resources where available. This is particularly the case for mints. For example, the URI http://nomisma.org/id/corinth is intended to represent that ancient city in its role as a minter/issuer of coins. The URI is linked via the SKOS ontology to the Pleiades Gazetteer of ancient places. This allows Nomisma to be the basis for a common representation of the concept that an object is a coin minted at Corinth. The ANS has already deployed such relationships in its public database. The work of all these projects is very much in progress so that this paper hopes to generate discussion on how multiple large projects can move forward in their own work while encouraging sufficient commonality to support large scale research questions undertaken by diverse audiences.