2008 IntroducingMetaServicesForBioMedExtraction

• (Leitner et al., 2008) ⇒ Florian Leitner, Martin Krallinger, Carlos Rodriguez-Penagos, Jörg Hakenberg, Conrad Plake, Cheng-Ju Kuo, Chun-Nan Hsu, Richard Tzong-Han Tsai, Hsi-Chuan Hung William W Lau, Calvin A Johnson, Rune Sætre, Kazuhiro Yoshida, Yan Hua Chen, Sun Kim, Soo-Yong Shin, Byoung-Tak Zhang, William A. Baumgartner Jr, Lawrence Hunter, Barry Haddow, Michael Matthews, Xinglong Wang, Patrick Ruch, Frédéric Ehrler, Arzucan Özgür, Güneş Erkan, Dragomir Radev, Michael Krauthammer, ThaiBinh Luong, Robert Hoffmann, Chris Sander, Alfonso Valencia. (2008). “Introducing Meta-Services for Biomedical Information Extraction.” In: Genome Biology, 9(Suppl 2):S6 doi:10.1186/gb-2008-9-s2-s6

Subject Headings: Gene Mention Recognition System, Gene Mention Normalization System, PubMed, Uniprot, BMCS, BioCreate Meta-Services, Entity Mention Normalization Task.

Notes

• http://bcms.bioinfo.cnio.es/

Cited By

• ~40 http://scholar.google.com/scholar?q=%22Introducing+Meta-Services+for+Biomedical+Information+Extraction.%22+2008

Quotes

Abstract

We introduce the first meta-service for information extraction in molecular biology, the BioCreative MetaServer (BCMS; http://bcms.bioinfo.cnio.es/ webcite). 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.

Background

Information retrieval (IR), information extraction (IE), and text mining have become integral parts of computational biology over the past decade [1]. However, these services are dispersed, integrated in specific packages, and include proprietary software. Therefore, 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].

Web services, widely used throughout the internet to provide the functionality for distributed systems, are becoming a common part of bioinformatics tools; For example, one of the most used text mining applications, namely iHOP (Information Hyperlinked Over Proteins), provides such an infrastructure to access its data [4]. Meta-services, too, are a ubiquitous component of the world wide web, found as meta-search engines, in business-to-buisness and business-to-consumer transactions (for example, for flight booking systems), and are used in scientific research (for example, for protein structure prediction) [5]. Another example of a distributed meta-service is BioDAS (Distributed Annotation System), a platform to exchange biologic sequence annotations between independent resources [6].

This publication describes the development of the BioCreative MetaServer (BCMS) prototype. The Results section (below) provides an overview of the system design and introduces the basic components, followed by short descriptions of the IE systems currently available through the platform prototype. The Discussion section (below) reviews what problems are solved and what issues need further investigation. The Conclusions section (below) closes with current and future utilities of this platform for the biomedical community. Technical details on the platform and implementation aspects can be found in the Materials and methods section (below).

Results

The fundamental aim of the BCMS platform is to provide users with annotations on biomedical texts from different systems. At the current prototype level, the dataset is restricted to a fixed number of approximately 22,800 PubMed/Medline abstracts. The available annotations consist of marking passages that are detected as gene or protein name mentions, annotating the articles with the gene/protein and taxonomic IDs (providing hyperlinks to the corresponding database entries), and a confidence score for whether the text contains protein-protein interaction information. Expanding on stand alone IE systems, this platform gathers the results of several systems developed by various research groups, unifies them, and allows the user to access abstracts and annotations in a combined view. It is conceivable that collating classification results will often enhance performance, simply because multiple equal classifications for a given annotation are more likely to be correct. 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.

Annotation Systems

Gene/protein normalization (GN): detect which genes or proteins are mentioned, assigning sequence database identifiers to the text.

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)

Entity mention normalization is based on large lexicon of known names and synonyms, which are kept in main memory at all times for efficiency. Once a potential named entity has been found, we further identify it using context profiles in case multiple entities share the same name [15];

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	Author	volume	Date Value	title	type	journal	titleUrl	doi	note	year
2008 IntroducingMetaServicesForBioMedExtraction	Kazuhiro Yoshida Patrick Ruch Dragomir Radev Alfonso Valencia Tzong-han Tsai Barry Haddow Michael Matthews Xinglong Wang William A. Baumgartner Jr Florian Leitner Lawrence Hunter Michael Krauthammer Chun-Nan Hsu Martin Krallinger Carlos Rodriguez-Penagos Cheng-Ju Kuo Hsi-Chuan Hung William W Lau Calvin A Johnson Rune Sætre Yan Hua Chen Sun Kim Soo-Yong Shin Byoung-Tak Zhang Frédéric Ehrler Arzucan Özgür Güneş Erkan ThaiBinh Luong Robert Hoffmann Chris Sander			Introducing Meta-Services for Biomedical Information Extraction			http://dx.doi.org/10.1186/gb-2008-9-s2-s6	10.1186/gb-2008-9-s2-s6