LitMiner: integration of library services within a bio-informatics application

CISTI Research, Canada Institute for Scientific and Technical Information, National Research Council of Canada, 1200 Montreal rd, Ottawa, Ontario, K1A 0R6, Canada.
Biomedical Digital Libraries 02/2006; 3:11. DOI: 10.1186/1742-5581-3-11
Source: PubMed

ABSTRACT This paper examines how the adoption of a subject-specific library service has changed the way in which its users interact with a digital library. The LitMiner text-analysis application was developed to enable biologists to explore gene relationships in the published literature. The application features a suite of interfaces that enable users to search PubMed as well as local databases, to view document abstracts, to filter terms, to select gene name aliases, and to visualize the co-occurrences of genes in the literature. At each of these stages, LitMiner offers the functionality of a digital library. Documents that are accessible online are identified by an icon. Users can also order documents from their institution's library collection from within the application. In so doing, LitMiner aims to integrate digital library services into the research process of its users.
Case study
This integration of digital library services into the research process of biologists results in increased access to the published literature.
In order to make better use of their collections, digital libraries should customize their services to suit the research needs of their patrons.

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Available from: Berry de Bruijn, Sep 29, 2015
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    • "EMPathIE pattern matching text EMP database enzymes [18] PASTA pattern matching text biological lexicons protein structure [19] BioIE pattern matching xml dictionary of terms biomedicine [20] BioRAT pattern matching, sub-language driven could be xml, html, text or asn.1, can do full-length pdf papers (converts to text) dictionary for protein and gene names, dictionary for interactions, and synonyms; text pattern template biomedicine [21] Chilibot shallow parsing not sure what was used in paper, but could be xml, html, text or asn.1 nomenclature dictionary biomedicine [22] Dragon Toolkit mixed syntactic semantic text domain ontologies genomics [23] EBIMed pattern matching xml dictionary of terms biomedicine [24] iProLINK shallow parsing text protein name dictionary, ontology, and annotated corpora proteins [25] LitMiner mixed syntactic semantic web documents Drosophila research [26] IE and other related research have acquired another, more general label " text data mining " (or simply " text mining " ). "
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    ABSTRACT: Centuries of biological knowledge are contained in the massive body of scientific literature, written for human-readability but too big for any one person to consume. Large-scale mining of information from the literature is necessary if biology is to transform into a data-driven science. A computer can handle the volume but cannot make sense of the language. This paper reviews and discusses the use of natural language processing (NLP) and machine-learning algorithms to extract information from systematic literature. NLP algorithms have been used for decades, but require special development for application in the biological realm due to the special nature of the language. Many tools exist for biological information extraction (cellular processes, taxonomic names, and morphological characters), but none have been applied life wide and most still require testing and development. Progress has been made in developing algorithms for automated annotation of taxonomic text, identification of taxonomic names in text, and extraction of morphological character information from taxonomic descriptions. This manuscript will briefly discuss the key steps in applying information extraction tools to enhance biodiversity science.
    Advances in Bioinformatics 05/2012; 2012:391574. DOI:10.1155/2012/391574
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    • "Εμπορικού χαρακτήρα λογισμικά τέτοιου είδους συνιστούν τα MetaLib, DigiTool, MuseGlobal (Donner & Curtis, 2004) κ.ά., που εστιάζουν στην ενοποίηση των δυνατοτήτων αναζήτησης ετερογενών πόρων (Gerrity, Lyman & Tallent, 2002). Αντίστοιχα, λογισμικά ανοικτού κώδικα (Demaine et al., 2006), όπως τα "
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    ABSTRACT: The paper regards to a proposition for coping with the problem of providing heterogeneous services through an integrated managerial system. The proposed system is being developed at the Panteion University Library and is complete at its main part as well as tested successfully. One of the main targets for the system is to demand minimum operational complexity on behalf of the librarians. Indeed, librarians are able to use an integrated management interface for entering data to different blocks, developing new services and (for example web forms or subject gateways), controlling logging facilities. Along with the other characteristics (such as scalability and interoperability) the system is innovative compared to other commercial or open source systems.
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    ABSTRACT: It is now almost 15 years since the publication of the first paper on text mining in the genomics domain, and decades since the first paper on text mining in the medical domain. Enormous progress has been made in the areas of information retrieval, evaluation methodologies and resource construction. Some problems, such as abbreviation-handling, can essentially be considered solved problems, and others, such as identification of gene mentions in text, seem likely to be solved soon. However, a number of problems at the frontiers of biomedical text mining continue to present interesting challenges and opportunities for great improvements and interesting research. In this article we review the current state of the art in biomedical text mining or ‘BioNLP’ in general, focusing primarily on papers published within the past year.
    Briefings in Bioinformatics 10/2007; 8(5):358-75. DOI:10.1093/bib/bbm045 · 9.62 Impact Factor
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