Elsevier and LIPID MAPS Launch Lipid Structures App on SciVerse Applications
Application links lipid data within articles to contextual information
Amsterdam, December 9, 2011 – Elsevier, a world-leading provider of scientific, technical and medical information products and services, today announced the availability of the Lipid Structures (beta) app on SciVerse Applications. The app was developed in collaboration with LIPID MAPS, a multi-institutional consortium aimed at increasing understanding of lipid metabolism, and the SciVerse Developer Network.
Lipid Structures (beta) identifies and links lipid names or synonyms in articles on SciVerse ScienceDirect, providing the user with supporting information on each particular lipid in context, such as the structure and other key information for that molecule as represented on the LIPID MAPS™ website. Information includes common and systematic names, formula, exact mass, InChIKey, classification hierarchy and links to other public databases. A panel in the side-bar also provides a convenient listing of lipid molecules in the article along with the number of occurrences within the article text. The application draws on the LIPID MAPS Structure Database (LMSD), a relational database encompassing structures and annotations of biologically relevant lipids with over 30,000 unique lipid structures.
“The LIPID MAPS consortium is pleased to collaborate with Elsevier in using the Lipid Structures (beta) application to deliver online content for this important class of biomolecules,” said Eoin Fahy, LIPID MAPS Bioinformatics Project Coordinator. “We believe this application will provide a very convenient interactive source of information on lipid structure, classification and properties, and hopefully will serve as a useful reference and educational tool for the lipidomics community.”
“Elsevier’s application framework enables us to collaborate with organizations like LIPID MAPS to rapidly create deep interoperability between articles and databases via entity linking in the full text,” said Rafael Sidi, Vice President, Application Marketplace and Developer Network at Elsevier. “Applications which support these connections with key domain specific resources represent a new frontier in scientific search and discovery tools, and we hope this is the first of many to come.”
SciVerse Applications and the Developer Network provide opportunities for researchers and librarians to collaborate with developers in creating and promoting new applications that improve research workflows. The Developer Network features a growing community of application developers that gain potential recognition, prestige and revenue through their contributions to SciVerse Applications.
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About LIPID MAPS Structure Database (LMSD)
The LIPID MAPS Structure Database (LMSD) is a relational database encompassing structures and annotations of biologically relevant lipids. It contains over 30,000 unique lipid structures, making it the largest public lipid-only database in the world. Structures of lipids in the database come from several sources: (i) LIPID MAPS Consortium's core laboratories and partners; (ii) lipids identified by LIPID MAPS experiments; (iii) biologically relevant lipids manually curated from LIPID BANK, LIPIDAT, Lipid Library, Cyberlipids, ChEBI and other public sources; (iv) novel lipids submitted to peer-reviewed journals; (v) computationally generated structures for appropriate classes.
All the lipid structures in LMSD adhere to the structure drawing rules proposed by the LIPID MAPS consortium. Additionally, all lipids in the LMSD have been classified using the LIPID MAPS Lipid Classification System, and each lipid structure has been assigned a LIPID MAPS ID (LM_ID) which reflects its position in the classification hierarchy.
About LIPID MAPS
The LIPID MAPS (Lipid Metabolites and Pathways Strategy) consortium is a multi-institutional effort to further our understanding of lipid metabolism and the role lipids play in diseases such as diabetes, stroke, and cancer. The consortium takes a systems biology approach using the mouse macrophage as a model system, and provides tools and resources for the wider community. The ultimate goal of the LIPID MAPS effort is to better understand lipid metabolism and the active role lipids play in diabetes, stroke, cancer, arthritis, Alzheimer's and other lipid-based diseases in order to facilitate development of more effective treatments.
About the Elsevier SciVerse Suite
The SciVerse suite of search and discovery offerings provides the global research community access to a constantly expanding universe of content and solutions which can now be accessed in one platform. The suite currently includes SciVerse ScienceDirect, the world’s largest source of peer-reviewed content containing more than 10 million articles, and SciVerse Scopus, an abstract and citation database containing 41 million records, 70% with abstracts and nearly 19,500 titles from 5,000 publishers worldwide. The platform also includes SciVerse Hub beta, which enables researchers to perform a single search across all of the SciVerse content as well as targeted web content with results ranked by relevancy and without duplication. SciVerse Applications and Developer Network allow the scientific community to build, find and use applications that enhance the SciVerse research experience
Elsevier is a world-leading provider of information solutions that enhance the performance of science, health, and technology professionals, empowering them to make better decisions, deliver better care, and sometimes make groundbreaking discoveries that advance the boundaries of knowledge and human progress. Elsevier provides web-based, digital solutions — among them ScienceDirect, Scopus, Elsevier Research Intelligence and ClinicalKey— and publishes over 2,500 journals, including The Lancet and Cell, and more than 35,000 book titles, including a number of iconic reference works. Elsevier is part of RELX Group, a world-leading provider of information and analytics for professional and business customers across industries. www.elsevier.com
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