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  1. The World Wide Web has become a dissemination platform for scientific and non-scientific publications. However, most of the information remains locked up in discrete documents that are not always interconnecte...

    Authors: L Jael Garcia Castro, C McLaughlin and A Garcia
    Citation: Journal of Biomedical Semantics 2013 4(Suppl 1):S5

    This article is part of a Supplement: Volume 4 Supplement 1

  2. Document search on PubMed, the pre-eminent database for biomedical literature, relies on the annotation of its documents with relevant terms from the Medical Subject Headings ontology (MeSH) for improving reca...

    Authors: Daniel Eisinger, George Tsatsaronis, Markus Bundschus, Ulrich Wieneke and Michael Schroeder
    Citation: Journal of Biomedical Semantics 2013 4(Suppl 1):S3

    This article is part of a Supplement: Volume 4 Supplement 1

  3. Clinical Intelligence, as a research and engineering discipline, is dedicated to the development of tools for data analysis for the purposes of clinical research, surveillance, and effective health care manage...

    Authors: Alexandre Riazanov, Artjom Klein, Arash Shaban-Nejad, Gregory W Rose, Alan J Forster, David L Buckeridge and Christopher JO Baker
    Citation: Journal of Biomedical Semantics 2013 4:9
  4. There is a growing need for efficient and integrated access to databases provided by diverse institutions. Using a linked data design pattern allows the diverse data on the Internet to be linked effectively an...

    Authors: Yasunori Yamamoto, Atsuko Yamaguchi and Akinori Yonezawa
    Citation: Journal of Biomedical Semantics 2013 4:8
  5. U-Compare is a text mining platform that allows the construction, evaluation and comparison of text mining workflows. U-Compare contains a large library of components that are tuned to the biomedical domain. U...

    Authors: Georgios Kontonatsios, Ioannis Korkontzelos, BalaKrishna Kolluru, Paul Thompson and Sophia Ananiadou
    Citation: Journal of Biomedical Semantics 2013 4:7
  6. BioHackathon 2010 was the third in a series of meetings hosted by the Database Center for Life Sciences (DBCLS) in Tokyo, Japan. The overall goal of the BioHackathon series is to improve the quality and access...

    Authors: Toshiaki Katayama, Mark D Wilkinson, Gos Micklem, Shuichi Kawashima, Atsuko Yamaguchi, Mitsuteru Nakao, Yasunori Yamamoto, Shinobu Okamoto, Kenta Oouchida, Hong-Woo Chun, Jan Aerts, Hammad Afzal, Erick Antezana, Kazuharu Arakawa, Bruno Aranda, Francois Belleau…
    Citation: Journal of Biomedical Semantics 2013 4:6
  7. Out-of-date or incomplete drug product labeling information may increase the risk of otherwise preventable adverse drug events. In recognition of these concerns, the United States Federal Drug Administration (...

    Authors: Richard D Boyce, John R Horn, Oktie Hassanzadeh, Anita De Waard, Jodi Schneider, Joanne S Luciano, Majid Rastegar-Mojarad and Maria Liakata
    Citation: Journal of Biomedical Semantics 2013 4:5
  8. The availability of annotated corpora has facilitated the application of machine learning algorithms to concept extraction from clinical notes. However, high expenditure and labor are required for creating the...

    Authors: Kavishwar B Wagholikar, Manabu Torii, Siddhartha R Jonnalagadda and Hongfang Liu
    Citation: Journal of Biomedical Semantics 2013 4:3
  9. Biomedical ontologies are key elements for building up the Life Sciences Semantic Web. Reusing and building biomedical ontologies requires flexible and versatile tools to manipulate them efficiently, in partic...

    Authors: Mikel Egaña Aranguren, Jesualdo Tomás Fernández-Breis, Chris Mungall, Erick Antezana, Alejandro Rodríguez González and Mark D Wilkinson
    Citation: Journal of Biomedical Semantics 2013 4:2
  10. One challenge in reusing clinical data stored in electronic medical records is that these data are heterogenous. Clinical Natural Language Processing (NLP) plays an important role in transforming information i...

    Authors: Stephen T Wu, Vinod C Kaggal, Dmitriy Dligach, James J Masanz, Pei Chen, Lee Becker, Wendy W Chapman, Guergana K Savova, Hongfang Liu and Christopher G Chute
    Citation: Journal of Biomedical Semantics 2013 4:1
  11. Fever is one of the most common adverse events of vaccines. The detailed mechanisms of fever and vaccine-associated gene interaction networks are not fully understood. In the present study, we employed a genom...

    Authors: Junguk Hur, Arzucan Özgür, Zuoshuang Xiang and Yongqun He
    Citation: Journal of Biomedical Semantics 2012 3:18
  12. Structured Product Labeling (SPL) is a document markup standard approved by Health Level Seven (HL7) and adopted by United States Food and Drug Administration (FDA) as a mechanism for exchanging drug product i...

    Authors: Qian Zhu, Guoqian Jiang and Christopher G Chute
    Citation: Journal of Biomedical Semantics 2012 3:16
  13. The sheer amount of information about potential adverse drug events publishedin medical case reports pose major challenges for drug safety experts toperform timely monitoring. Efficient strategies for identifi...

    Authors: Harsha Gurulingappa, Abdul Mateen‐Rajpu and Luca Toldo
    Citation: Journal of Biomedical Semantics 2012 3:15
  14. Identification of drug-drug and drug-diseases interactions can pose a difficult problem to cope with, as the increasingly large number of available drugs coupled with the ongoing research activities in the pha...

    Authors: Charalampos Doulaverakis, George Nikolaidis, Athanasios Kleontas and Ioannis Kompatsiaris
    Citation: Journal of Biomedical Semantics 2012 3:14
  15. The U.S. FDA/CDC Vaccine Adverse Event Reporting System (VAERS) provides a valuable data source for post-vaccination adverse event analyses. The structured data in the system has been widely used, but the info...

    Authors: Cui Tao, Yongqun He, Hannah Yang, Gregory A Poland and Christopher G Chute
    Citation: Journal of Biomedical Semantics 2012 3:13
  16. Vaccines and drugs have contributed to dramatic improvements in public health worldwide. Over the last decade, there have been efforts in developing biomedical ontologies that represent various areas associate...

    Authors: Yongqun He, Luca Toldo, Gully Burns, Cui Tao and Darrell R Abernethy
    Citation: Journal of Biomedical Semantics 2012 3:12
  17. As the “omics” revolution unfolds, the growth in data quantity and diversity is bringing about the need for pioneering bioinformatics software, capable of significantly improving the research workflow. To cope...

    Authors: Pedro Lopes and José Luís Oliveira
    Citation: Journal of Biomedical Semantics 2012 3:11
  18. The ability to conduct genome-wide association studies (GWAS) has enabled new exploration of how genetic variations contribute to health and disease etiology. However, historically GWAS have been limited by in...

    Authors: Jyotishman Pathak, Richard C Kiefer, Suzette J Bielinski and Christopher G Chute
    Citation: Journal of Biomedical Semantics 2012 3:10
  19. The amount of data generated from genome-wide association studies (GWAS) has grown rapidly, but considerations for GWAS phenotype data reuse and interchange have not kept pace. This impacts on the work of GWAS...

    Authors: Tim Beck, Robert C Free, Gudmundur A Thorisson and Anthony J Brookes
    Citation: Journal of Biomedical Semantics 2012 3:9
  20. In this paper we demonstrate the usage of RIO; a framework for detecting syntactic regularities using cluster analysis of the entities in the signature of an ontology. Quality assurance in ontologies is vital ...

    Authors: Eleni Mikroyannidi, Robert Stevens, Luigi Iannone and Alan Rector
    Citation: Journal of Biomedical Semantics 2012 3:8
  21. Clustering textual contents is an important step in mining useful information on the web or other text-based resources. The common task in text clustering is to handle text in a multi-dimensional space, and to...

    Authors: Sun Kim and W John Wilbur
    Citation: Journal of Biomedical Semantics 2012 3(Suppl 3):S6

    This article is part of a Supplement: Volume 3 Supplement 3

  22. One of the key pieces of information which biomedical text mining systems are expected to extract from the literature are interactions among different types of biomedical entities (proteins, genes, diseases, d...

    Authors: Simon Clematide and Fabio Rinaldi
    Citation: Journal of Biomedical Semantics 2012 3(Suppl 3):S5

    This article is part of a Supplement: Volume 3 Supplement 3

  23. There are several humanly defined ontologies relevant to Medline. However, Medline is a fast growing collection of biomedical documents which creates difficulties in updating and expanding these humanly define...

    Authors: Lana Yeganova, Won Kim, Donald C Comeau and W John Wilbur
    Citation: Journal of Biomedical Semantics 2012 3(Suppl 3):S3

    This article is part of a Supplement: Volume 3 Supplement 3

  24. We propose a method for automatic extraction of protein-specific residue mentions from the biomedical literature. The method searches text for mentions of amino acids at specific sequence positions and attempt...

    Authors: KE Ravikumar, Haibin Liu, Judith D Cohn, Michael E Wall and Karin Verspoor
    Citation: Journal of Biomedical Semantics 2012 3(Suppl 3):S2

    This article is part of a Supplement: Volume 3 Supplement 3

  25. The concept of a mechanism has become a standard proposal for explanations in biology. It has been claimed that mechanistic explanations are appropriate for systems biology, because they occupy a middle ground...

    Authors: Johannes Röhl
    Citation: Journal of Biomedical Semantics 2012 3(Suppl 2):S9

    This article is part of a Supplement: Volume 3 Supplement 2

  26. Biomedical ontologies usually encode knowledge that applies always or at least most of the time, that is in normal circumstances. But for some applications like phenotype ontologies it is becoming increasingly...

    Authors: Niels Grewe
    Citation: Journal of Biomedical Semantics 2012 3(Suppl 2):S8

    This article is part of a Supplement: Volume 3 Supplement 2

  27. Despite the high coverage of biomedical ontologies, very few sound definitions of death can be found. Nevertheless, this concept has its relevance in epidemiology, such as for data integration within mortality...

    Authors: Filipe Santana, Fred Freitas, Roberta Fernandes, Zulma Medeiros and Daniel Schober
    Citation: Journal of Biomedical Semantics 2012 3(Suppl 2):S7

    This article is part of a Supplement: Volume 3 Supplement 2

  28. Ontologies are widely used in the biomedical community for annotation and integration of databases. Formal definitions can relate classes from different ontologies and thereby integrate data across different l...

    Authors: Georgios V Gkoutos and Robert Hoehndorf
    Citation: Journal of Biomedical Semantics 2012 3(Suppl 2):S6

    This article is part of a Supplement: Volume 3 Supplement 2

  29. Phenotype ontologies are used in species-specific databases for the annotation of mutagenesis experiments and to characterize human diseases. The Entity-Quality (EQ) formalism is a means to describe complex ph...

    Authors: Frank Loebe, Frank Stumpf, Robert Hoehndorf and Heinrich Herre
    Citation: Journal of Biomedical Semantics 2012 3(Suppl 2):S5

    This article is part of a Supplement: Volume 3 Supplement 2

  30. Although policy providers have outlined minimal metadata guidelines and naming conventions, ontologies of today still display inter- and intra-ontology heterogeneities in class labelling schemes and metadata c...

    Authors: Daniel Schober, Ilinca Tudose, Vojtech Svatek and Martin Boeker
    Citation: Journal of Biomedical Semantics 2012 3(Suppl 2):S4

    This article is part of a Supplement: Volume 3 Supplement 2

  31. We demonstrate a heterogeneity of representation types for breast cancer phenotypes and stress that the characterisation of a tumour phenotype often includes parameters that go beyond the representation of a c...

    Authors: Aleksandra Sojic and Oliver Kutz
    Citation: Journal of Biomedical Semantics 2012 3(Suppl 2):S3

    This article is part of a Supplement: Volume 3 Supplement 2

  32. Ontology Design Patterns (ODPs) are representational artifacts devised to offer solutions for recurring ontology design problems. They promise to enhance the ontology building process in terms of flexibility, ...

    Authors: Djamila Seddig-Raufie, Ludger Jansen, Daniel Schober, Martin Boeker, Niels Grewe and Stefan Schulz
    Citation: Journal of Biomedical Semantics 2012 3(Suppl 2):S2

    This article is part of a Supplement: Volume 3 Supplement 2

  33. Researchers use animal studies to better understand human diseases. In recent years, large-scale phenotype studies such as Phenoscape and EuroPhenome have been initiated to identify genetic causes of a species...

    Authors: Anika Oellrich, Georgios V Gkoutos, Robert Hoehndorf and Dietrich Rebholz-Schuhmann
    Citation: Journal of Biomedical Semantics 2012 3(Suppl 2):S1

    This article is part of a Supplement: Volume 3 Supplement 2

  34. With the development of high throughput methods of gene analyses, there is a growing need for mining tools to retrieve relevant articles in PubMed. As PubMed grows, literature searches become more complex and ...

    Authors: Charles Bettembourg, Christian Diot, Anita Burgun and Olivier Dameron
    Citation: Journal of Biomedical Semantics 2012 3:7
  35. Clinical phenotypes and disease-risk stratification are most often determined through the direct observations of clinicians in conjunction with published standards and guidelines, where the clinical expert is ...

    Authors: Soroush Samadian, Bruce McManus and Mark D Wilkinson
    Citation: Journal of Biomedical Semantics 2012 3:6
  36. Genome sequencing of many eukaryotic pathogens and the volume of data available on public resources have created a clear requirement for a consistent vocabulary to describe the range of developmental forms of ...

    Authors: Priti P Parikh, Jie Zheng, Flora Logan-Klumpler, Christian J Stoeckert Jr, Christos Louis, Pantelis Topalis, Anna V Protasio, Amit P Sheth, Mark Carrington, Matthew Berriman and Satya S Sahoo
    Citation: Journal of Biomedical Semantics 2012 3:5
  37. Transfusion and clinical laboratory services are high-volume activities involving complicated workflows across both ambulatory and inpatient environments. As a result, there are many opportunities for safety l...

    Authors: Julie M Whitehurst, John Schroder, Dave Leonard, Monica M Horvath, Heidi Cozart and Jeffrey Ferranti
    Citation: Journal of Biomedical Semantics 2012 3:4
  38. The OpenTox Framework, developed by the partners in the OpenTox project (http://​www.​opentox.​org), aims at providing a unified access to toxicity data, ...

    Authors: Olga Tcheremenskaia, Romualdo Benigni, Ivelina Nikolova, Nina Jeliazkova, Sylvia E Escher, Monika Batke, Thomas Baier, Vladimir Poroikov, Alexey Lagunin, Micha Rautenberg and Barry Hardy
    Citation: Journal of Biomedical Semantics 2012 3(Suppl 1):S7

    This article is part of a Supplement: Volume 3 Supplement 1

  39. A variety of topic-focused wikis are used in the biomedical sciences to enable the mass-collaborative synthesis and distribution of diverse bodies of knowledge. To address complex problems such as defining the...

    Authors: Benjamin M Good, Erik L Clarke, Salvatore Loguercio and Andrew I Su
    Citation: Journal of Biomedical Semantics 2012 3(Suppl 1):S6

    This article is part of a Supplement: Volume 3 Supplement 1

  40. The electronic surveillance for adverse drug events is largely based upon the analysis of coded data from reporting systems. Yet, the vast majority of electronic health data lies embedded within the free text ...

    Authors: Paea LePendu, Srinivasan V Iyer, Cédrick Fairon and Nigam H Shah
    Citation: Journal of Biomedical Semantics 2012 3(Suppl 1):S5

    This article is part of a Supplement: Volume 3 Supplement 1

  41. Identifying relationships between hitherto unrelated entities in different ontologies is the key task of ontology alignment. An alignment is either manually created by domain experts or automatically by an ali...

    Authors: Elena Beisswanger and Udo Hahn
    Citation: Journal of Biomedical Semantics 2012 3(Suppl 1):S4

    This article is part of a Supplement: Volume 3 Supplement 1

  42. Ontologies such as the Gene Ontology (GO) and their use in annotations make cross species comparisons of genes possible, along with a wide range of other analytical activities. The bio-ontologies community, in...

    Authors: Simon Jupp, Robert Stevens and Robert Hoehndorf
    Citation: Journal of Biomedical Semantics 2012 3(Suppl 1):S3

    This article is part of a Supplement: Volume 3 Supplement 1

  43. The increasing number of scientific literature on the Web and the absence of efficient tools used for classifying and searching the documents are the two most important factors that influence the speed of the ...

    Authors: George Tsatsaronis, Natalia Macari, Sunna Torge, Heiko Dietze and Michael Schroeder
    Citation: Journal of Biomedical Semantics 2012 3(Suppl 1):S2

    This article is part of a Supplement: Volume 3 Supplement 1

  44. Over the 14 years, the Bio-Ontologies SIG at ISMB has provided a forum for discussion of the latest and most innovative research in the bio-ontologies development, its applications to biomedicine and more gene...

    Authors: Larisa N Soldatova, Susanna-Assunta Sansone, Michel Dumontier and Nigam H Shah
    Citation: Journal of Biomedical Semantics 2012 3(Suppl 1):I1

    This article is part of a Supplement: Volume 3 Supplement 1

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