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1. Wren JD, Wilkins D, Fuscoe JC, Bridges S, Winters-Hilt S, Gusev Y: Proceedings of the 2008 MidSouth Computational Biology and Bioinformatics Society (MCBIOS) Conference. BMC Bioinformatics; 2008;9 Suppl 9:S1
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  • [Source] The source of this record is MEDLINE®, a database of the U.S. National Library of Medicine.
  • [Title] Proceedings of the 2008 MidSouth Computational Biology and Bioinformatics Society (MCBIOS) Conference.
  • [MeSH-major] Computational Biology / trends. Gene Expression Profiling / trends. Genomics / trends. Microarray Analysis / trends

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  • (PMID = 18793454.001).
  • [ISSN] 1471-2105
  • [Journal-full-title] BMC bioinformatics
  • [ISO-abbreviation] BMC Bioinformatics
  • [Language] eng
  • [Grant] United States / NIAMS NIH HHS / AR / P30 AR053483
  • [Publication-type] Congresses
  • [Publication-country] England
  • [Other-IDs] NLM/ PMC2537572
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2. Bodenreider O: Biomedical ontologies in action: role in knowledge management, data integration and decision support. Yearb Med Inform; 2008;:67-79
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  • [Source] The source of this record is MEDLINE®, a database of the U.S. National Library of Medicine.
  • [Title] Biomedical ontologies in action: role in knowledge management, data integration and decision support.
  • OBJECTIVES: To provide typical examples of biomedical ontologies in action, emphasizing the role played by biomedical ontologies in knowledge management, data integration and decision support.
  • METHODS: Biomedical ontologies selected for their practical impact are examined from a functional perspective.
  • Examples of applications are taken from operational systems and the biomedical literature, with a bias towards recent journal articles.
  • RESULTS: The ontologies under investigation in this survey include SNOMED CT, the Logical Observation Identifiers, Names, and Codes (LOINC), the Foundational Model of Anatomy, the Gene Ontology, RxNorm, the National Cancer Institute Thesaurus, the International Classification of Diseases, the Medical Subject Headings (MeSH) and the Unified Medical Language System (UMLS).
  • The roles played by biomedical ontologies are classified into three major categories: knowledge management (indexing and retrieval of data and information, access to information, mapping among ontologies); data integration, exchange and semantic interoperability; and decision support and reasoning (data selection and aggregation, decision support, natural language processing applications, knowledge discovery).
  • CONCLUSIONS: Ontologies play an important role in biomedical research through a variety of applications.
  • While ontologies are used primarily as a source of vocabulary for standardization and integration purposes, many applications also use them as a source of computable knowledge.
  • Barriers to the use of ontologies in biomedical applications are discussed.
  • [MeSH-major] Decision Support Techniques. Information Management. Vocabulary, Controlled
  • [MeSH-minor] Bibliometrics. Natural Language Processing. PubMed / trends. Semantics. Terminology as Topic

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  • (PMID = 18660879.001).
  • [ISSN] 0943-4747
  • [Journal-full-title] Yearbook of medical informatics
  • [ISO-abbreviation] Yearb Med Inform
  • [Language] eng
  • [Grant] United States / Intramural NIH HHS / / Z99 LM999999
  • [Publication-type] Journal Article; Research Support, N.I.H., Intramural
  • [Publication-country] Germany
  • [Other-IDs] NLM/ NIHMS60158; NLM/ PMC2592252
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3. Tjioe E, Berry MW, Homayouni R: Discovering gene functional relationships using FAUN (Feature Annotation Using Nonnegative matrix factorization). BMC Bioinformatics; 2010 Oct 07;11 Suppl 6:S14
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  • [Source] The source of this record is MEDLINE®, a database of the U.S. National Library of Medicine.
  • [Title] Discovering gene functional relationships using FAUN (Feature Annotation Using Nonnegative matrix factorization).
  • BACKGROUND: Searching the enormous amount of information available in biomedical literature to extract novel functional relationships among genes remains a challenge in the field of bioinformatics.
  • While numerous (software) tools have been developed to extract and identify gene relationships from biological databases, few effectively deal with extracting new (or implied) gene relationships, a process which is useful in interpretation of discovery-oriented genome-wide experiments.
  • RESULTS: In this study, we develop a Web-based bioinformatics software environment called FAUN or Feature Annotation Using Nonnegative matrix factorization (NMF) to facilitate both the discovery and classification of functional relationships among genes.
  • Both the computational complexity and parameterization of NMF for processing gene sets are discussed.
  • FAUN is tested on three manually constructed gene document collections.
  • Its utility and performance as a knowledge discovery tool is demonstrated using a set of genes associated with Autism.
  • CONCLUSIONS: FAUN not only assists researchers to use biomedical literature efficiently, but also provides utilities for knowledge discovery.
  • This Web-based software environment may be useful for the validation and analysis of functional associations in gene subsets identified by high-throughput experiments.

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  • (PMID = 20946597.001).
  • [ISSN] 1471-2105
  • [Journal-full-title] BMC bioinformatics
  • [ISO-abbreviation] BMC Bioinformatics
  • [Language] ENG
  • [Grant] United States / NICHD NIH HHS / HD / HD052472
  • [Publication-type] Journal Article; Research Support, N.I.H., Extramural
  • [Publication-country] England
  • [Other-IDs] NLM/ PMC3026361
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4. Bui QC, Nualláin BO, Boucher CA, Sloot PM: Extracting causal relations on HIV drug resistance from literature. BMC Bioinformatics; 2010;11:101
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  • [Source] The source of this record is MEDLINE®, a database of the U.S. National Library of Medicine.
  • [Title] Extracting causal relations on HIV drug resistance from literature.
  • BACKGROUND: In HIV treatment it is critical to have up-to-date resistance data of applicable drugs since HIV has a very high rate of mutation.
  • These data are made available through scientific publications and must be extracted manually by experts in order to be used by virologists and medical doctors.
  • Therefore there is an urgent need for a tool that partially automates this process and is able to retrieve relations between drugs and virus mutations from literature.
  • RESULTS: In this work we present a novel method to extract and combine relationships between HIV drugs and mutations in viral genomes.
  • Our extraction method is based on natural language processing (NLP) which produces grammatical relations and applies a set of rules to these relations.
  • We applied our method to a relevant set of PubMed abstracts and obtained 2,434 extracted relations with an estimated performance of 84% for F-score.
  • We then combined the extracted relations using logistic regression to generate resistance values for each <drug, mutation> pair.
  • The results of this relation combination show more than 85% agreement with the Stanford HIVDB for the ten most frequently occurring mutations.
  • The system is used in 5 hospitals from the Virolab project http://www.virolab.org to preselect the most relevant novel resistance data from literature and present those to virologists and medical doctors for further evaluation.
  • CONCLUSIONS: The proposed relation extraction and combination method has a good performance on extracting HIV drug resistance data.
  • It can be used in large-scale relation extraction experiments.
  • The developed methods can also be applied to extract other type of relations such as gene-protein, gene-disease, and disease-mutation.
  • [MeSH-major] Abstracting and Indexing as Topic / methods. Drug Resistance, Viral / genetics. HIV Infections / drug therapy
  • [MeSH-minor] Anti-HIV Agents / therapeutic use. Databases, Genetic. Genome, Viral. Information Storage and Retrieval / methods. Internet. Mutation. PubMed

  • MedlinePlus Health Information. consumer health - HIV/AIDS.
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  • (PMID = 20178611.001).
  • [ISSN] 1471-2105
  • [Journal-full-title] BMC bioinformatics
  • [ISO-abbreviation] BMC Bioinformatics
  • [Language] eng
  • [Publication-type] Journal Article; Research Support, Non-U.S. Gov't
  • [Publication-country] England
  • [Chemical-registry-number] 0 / Anti-HIV Agents
  • [Other-IDs] NLM/ PMC2841207
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5. Smalheiser NR, Torvik VI, Zhou W: Arrowsmith two-node search interface: a tutorial on finding meaningful links between two disparate sets of articles in MEDLINE. Comput Methods Programs Biomed; 2009 May;94(2):190-7
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  • [Source] The source of this record is MEDLINE®, a database of the U.S. National Library of Medicine.
  • [Title] Arrowsmith two-node search interface: a tutorial on finding meaningful links between two disparate sets of articles in MEDLINE.
  • The Arrowsmith two-node search is a strategy that is designed to assist biomedical investigators in formulating and assessing scientific hypotheses.
  • More generally, it allows users to identify biologically meaningful links between any two sets of articles A and C in PubMed, even when these share no articles or authors in common and represent disparate topics or disciplines.
  • The key idea is to relate the two sets of articles via title words and phrases (B-terms) that they share.
  • We have created a free, public web-based version of the two-node search tool (http://arrowsmith.psych.uic.edu), have described its development and implementation, and have presented analyses of individual two-node searches.
  • In this paper, we provide an updated tutorial intended for end-users, that covers the use of the tool for a variety of potential scientific use case scenarios.
  • For example, one can assess a recent experimental, clinical or epidemiologic finding that connects two disparate fields of inquiry--identifying likely mechanisms to explain the finding, and choosing promising follow-up lines of investigation.
  • Alternatively, one can assess whether the existing scientific literature lends indirect support to a hypothesis posed by the user that has not yet been investigated.
  • One can also employ two-node searches to search for novel hypotheses.
  • Arrowsmith provides a service that cannot be carried out feasibly via standard PubMed searches or by other available text mining tools.

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  • (PMID = 19185946.001).
  • [ISSN] 1872-7565
  • [Journal-full-title] Computer methods and programs in biomedicine
  • [ISO-abbreviation] Comput Methods Programs Biomed
  • [Language] ENG
  • [Grant] United States / NLM NIH HHS / LM / R01 LM007292; United States / NLM NIH HHS / LM / LM008364; United States / NLM NIH HHS / LM / R21 LM008364; United States / NLM NIH HHS / LM / R01 LM007292-05; United States / NLM NIH HHS / LM / LM008364-02; United States / NLM NIH HHS / LM / R21 LM008364-02; United States / NLM NIH HHS / LM / LM007292
  • [Publication-type] Journal Article; Research Support, N.I.H., Extramural
  • [Publication-country] Ireland
  • [Other-IDs] NLM/ NIHMS105821; NLM/ PMC2693227
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6. Hull D, Pettifer SR, Kell DB: Defrosting the digital library: bibliographic tools for the next generation web. PLoS Comput Biol; 2008 Oct;4(10):e1000204
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  • [Source] The source of this record is MEDLINE®, a database of the U.S. National Library of Medicine.
  • [Title] Defrosting the digital library: bibliographic tools for the next generation web.
  • Many scientists now manage the bulk of their bibliographic information electronically, thereby organizing their publications and citation material from digital libraries.
  • However, a library has been described as "thought in cold storage," and unfortunately many digital libraries can be cold, impersonal, isolated, and inaccessible places.
  • In this Review, we discuss the current chilly state of digital libraries for the computational biologist, including PubMed, IEEE Xplore, the ACM digital library, ISI Web of Knowledge, Scopus, Citeseer, arXiv, DBLP, and Google Scholar.
  • We illustrate the current process of using these libraries with a typical workflow, and highlight problems with managing data and metadata using URIs.
  • We then examine a range of new applications such as Zotero, Mendeley, Mekentosj Papers, MyNCBI, CiteULike, Connotea, and HubMed that exploit the Web to make these digital libraries more personal, sociable, integrated, and accessible places.
  • We conclude with how these applications may begin to help achieve a digital defrost, and discuss some of the issues that will help or hinder this in terms of making libraries on the Web warmer places in the future, becoming resources that are considerably more useful to both humans and machines.
  • [MeSH-major] Database Management Systems / trends. Internet / organization & administration. Libraries, Digital / organization & administration
  • [MeSH-minor] Databases, Bibliographic. Humans. Library Automation / trends. Library Collection Development / trends

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  • (PMID = 18974831.001).
  • [ISSN] 1553-7358
  • [Journal-full-title] PLoS computational biology
  • [ISO-abbreviation] PLoS Comput. Biol.
  • [Language] eng
  • [Grant] United Kingdom / Biotechnology and Biological Sciences Research Council / / BB/E016065/1; United Kingdom / Biotechnology and Biological Sciences Research Council / / BB/E004431/1
  • [Publication-type] Journal Article; Research Support, Non-U.S. Gov't; Review
  • [Publication-country] United States
  • [Number-of-references] 210
  • [Other-IDs] NLM/ PMC2568856
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7. Smalheiser NR, Zhou W, Torvik VI: Anne O'Tate: A tool to support user-driven summarization, drill-down and browsing of PubMed search results. J Biomed Discov Collab; 2008 Feb 15;3:2
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  • [Source] The source of this record is MEDLINE®, a database of the U.S. National Library of Medicine.
  • [Title] Anne O'Tate: A tool to support user-driven summarization, drill-down and browsing of PubMed search results.
  • BACKGROUND: PubMed is designed to provide rapid, comprehensive retrieval of papers that discuss a given topic.
  • However, because PubMed does not organize the search output further, it is difficult for users to grasp an overview of the retrieved literature according to non-topical dimensions, to drill-down to find individual articles relevant to a particular individual's need, or to browse the collection.
  • RESULTS: In this paper, we present Anne O'Tate, a web-based tool that processes articles retrieved from PubMed and displays multiple aspects of the articles to the user, according to pre-defined categories such as the "most important" words found in titles or abstracts; topics; journals; authors; publication years; and affiliations.
  • Clicking on a given item opens a new window that displays all papers that contain that item.
  • One can navigate by drilling down through the categories progressively, e.g., one can first restrict the articles according to author name and then restrict that subset by affiliation.
  • Alternatively, one can expand small sets of articles to display the most closely related articles.
  • We also implemented a novel cluster-by-topic method that generates a concise set of topics covering most of the retrieved articles.
  • CONCLUSION: Anne O'Tate is an integrated, generic tool for summarization, drill-down and browsing of PubMed search results that accommodates a wide range of biomedical users and needs.
  • It can be accessed at 4.
  • Peer review and editorial matters for this article were handled by Aaron Cohen.

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  • (PMID = 18279519.001).
  • [ISSN] 1747-5333
  • [Journal-full-title] Journal of biomedical discovery and collaboration
  • [ISO-abbreviation] J Biomed Discov Collab
  • [Language] ENG
  • [Grant] United States / NLM NIH HHS / LM / R01 LM007292; United States / NLM NIH HHS / LM / R21 LM008364
  • [Publication-type] Journal Article
  • [Publication-country] United States
  • [Other-IDs] NLM/ PMC2276193
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