Abstract
We introduce the first meta-service for information extraction in molecular biology, the BioCreative MetaServer (BCMS; ). This prototype platform is a joint effort of 13 research groups and provides automatically generated annotations for PubMed/Medline abstracts. Annotation types cover gene names, gene IDs, species, and protein-protein interactions. The annotations are distributed by the meta-server in both human and machine readable formats (HTML/XML). This service is intended to be used by biomedical researchers and database annotators, and in biomedical language processing. The platform allows direct comparison, unified access, and result aggregation of the annotations.
Highlights
Information retrieval (IR), information extraction (IE), and text mining have become integral parts of computational biology over the past decade [1]
Biotec TU Dresden and Humboldt-Universität zu Berlin (JH, CP) [Hakenberg] The annotations we currently provide are gene mention normalization (32,795 human genes from EntrezGene), protein mention tagging, National Center for Biotechnology Information (NCBI) taxonomy IDs for species mentioned in texts, and classifications of whether the text discussed one or more protein-protein interactions
The platform provides an interface to explore and extract some of the annotation data created during the BioCreative II challenge [7], namely the four annotation types described in the Annotation systems section, for all of the official training and test set abstracts
Summary
Information retrieval (IR), information extraction (IE), and text mining have become integral parts of computational biology over the past decade [1]. These services are dispersed, integrated in specific packages, and include proprietary software. Progress in the field requires offering better access to the tools, methods, and their results [2] Other areas, such as sequence analysis, genome analysis, or protein structure prediction, have benefited greatly from enhanced access to services and tools for the community of biologists, bioinformaticians (through web servers and portals), and developers (by providing free, open source academic software) [3]. The gathered data are accessible to the user both as human-readable hypertext and as machine processable XML in the form of XML-RPC requests
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