![]() ; ; et al in PLoS Computational Biology (2010), 6 Detailed reference viewed: 90 (1 UL)![]() ; ; et al in PLoS Computational Biology (2010), 6(1), 1-2 Detailed reference viewed: 270 (1 UL)![]() ; ; et al in Journal of Web Semantics (2010), 8(2-3), 182-189 To date, adding semantic capabilities to web content usually requires considerable server-side re-engineering, thus only a tiny fraction of all web content currently has semantic annotations. Recently, we ... [more ▼] To date, adding semantic capabilities to web content usually requires considerable server-side re-engineering, thus only a tiny fraction of all web content currently has semantic annotations. Recently, we announced Reflect (http://reflect.ws), a free service that takes a more practical approach: Reflect uses augmented browsing to allow end-users to add systematic semantic annotations to any web-page in real-time, typically within seconds. In this paper we describe the tagging process in detail and show how further entity types can be added to Reflect; we also describe how publishers and content providers can access Reflect programmatically using SOAP, REST (HTTP post), and JavaScript. Usage of Reflect has grown rapidly within the life sciences, and while currently only genes, protein and small molecule names are tagged, we plan to soon expand the scope to include a much broader range of terms (e. g., Wikipedia entries). The popularity of Reflect demonstrates the use and feasibility of letting end-users decide how and when to add semantic annotations. Ultimately, 'semantics is in the eye of the end-user', hence we believe end-user approaches such as Reflect will become increasingly important in semantic web technologies. [less ▲] Detailed reference viewed: 179 (5 UL)![]() ; ; et al in Nature Biotechnology (2009), 27(6), 508-510 Detailed reference viewed: 142 (6 UL)![]() ; ; et al in Nucleic Acids Research (2008), 36(SI), 919-922 The molecular basis of drug action is often not well understood. This is partly because the very abundant and diverse information generated in the past decades on drugs is hidden in millions of medical ... [more ▼] The molecular basis of drug action is often not well understood. This is partly because the very abundant and diverse information generated in the past decades on drugs is hidden in millions of medical articles or textbooks. Therefore, we developed a one-stop data warehouse, SuperTarget that integrates drug-related information about medical indication areas, adverse drug effects, drug metabolization, pathways and Gene Ontology terms of the target proteins. An easy-to-use query interface enables the user to pose complex queries, for example to find drugs that target a certain pathway, interacting drugs that are metabolized by the same cytochrome P450 or drugs that target the same protein but are metabolized by different enzymes. Furthermore, we provide tools for 2D drug screening and sequence comparison of the targets. The database contains more than 2500 target proteins, which are annotated with about 7300 relations to 1500 drugs; the vast majority of entries have pointers to the respective literature source. A subset of these drugs has been annotated with additional binding information and indirect interactions and is available as a separate resource called Matador. SuperTarget and Matador are available at http://insilico.charite.de/supertarget and http://matador.embl.de. [less ▲] Detailed reference viewed: 197 (0 UL) |
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