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    1. Effects of speech- and text-based interaction modes in natural language human-computer dialogue.

      Related Articles Effects of speech- and text-based interaction modes in natural language human-computer dialogue. Hum Factors. 2007 Dec;49(6):1045-53 Authors: Le Bigot L, Rouet JF, Jamet E OBJECTIVE: This study examined the effects of user production (speaking and typing) and user reception (listening and reading) modes on natural language human-computer dialogue. BACKGROUND: Text-based dialogue is often more efficient than speech-based dialogue, but the latter is more dynamic and more suitable for mobile environments and hands-busy situations. The respective contributions of user production and reception modes have not previously been assessed. METHOD: Eighteen participants performed several information search tasks ...
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      Mentions: France
    2. Broadening the horizon--level 2.5 of the Hupo-psi format for molecular interactions.

      Related Articles Broadening the horizon--level 2.5 of the HUPO-PSI format for molecular interactions. BMC Biol. 2007;5:44 Authors: Kerrien S, Orchard S, Montecchi-Palazzi L, Aranda B, Quinn AF, Vinod N, Bader GD, Xenarios I, Wojcik J, Sherman D, Tyers M, Salama JJ, Moore S, Ceol A, Chatr-Aryamontri A, Oesterheld M, Stümpflen V, Salwinski L, Nerothin J, Cerami E, Cusick ME, Vidal M, Gilson M, Armstrong J, Woollard P, Hogue C, Eisenberg D, Cesareni G, Apweiler R, Hermjakob H BACKGROUND: Molecular interaction Information is a key resource in modern biomedical research. Publicly available data have previously been provided ...
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    3. Frontiers of biomedical text mining: current progress.

      Related Articles Frontiers of biomedical text mining: current progress. Brief Bioinform. 2007 Sep;8(5):358-75 Authors: Zweigenbaum P, Demner-Fushman D, Yu H, Cohen KB 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 ...
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      Mentions: France Orsay Cedex
    4. Kernel approaches for genic interaction extraction.

      Related Articles Kernel approaches for genic interaction extraction. Bioinformatics. 2008 Jan 1;24(1):118-26 Authors: Kim S, Yoon J, Yang J MOTIVATION: Automatic knowledge discovery and efficient information access such as named entity recognition and relation extraction between entities have recently become critical issues in the biomedical literature. However, the inherent difficulty of the relation extraction task, mainly caused by the diversity of natural language, is further compounded in the biomedical domain because biomedical sentences are commonly long and complex. In addition, relation extraction often involves modeling long range dependencies, discontiguous word patterns and semantic relations for which the ...
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    5. Biomedical ontologies: a functional perspective.

      Related Articles Biomedical ontologies: a functional perspective. Brief Bioinform. 2008 Jan;9(1):75-90 Authors: Rubin DL, Shah NH, Noy NF The information explosion in biology makes it difficult for researchers to stay abreast of current biomedical knowledge and to make sense of the massive amounts of online information. Ontologies--specifications of the entities, their attributes and relationships among the entities in a domain of discourse--are increasingly enabling biomedical researchers to accomplish these tasks. In fact, bio-ontologies are beginning to proliferate in step with accruing biological data. The myriad of ontologies being created enables researchers not only to solve some of ...
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    6. Corpus annotation for mining biomedical events from literature.

      Related Articles Corpus annotation for mining biomedical events from literature. BMC Bioinformatics. 2008 Jan 8;9(1):10 Authors: Kim JD, Ohta T, Tsujii J ABSTRACT: BACKGROUND: Advanced text-mining (TM) such as semantic enrichment of papers, event or relation extraction, and intelligent question answering have increasingly attracted attention in the bio-medical domain. For such attempts to succeed, text annotation from the biological point of view is indispensable. However, due to the complexity of the task, semantic annotation has never been tried on a large scale, apart from relatively simple term annotation. RESULTS: We have completed a new type of semantic ...
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    7. BioCAD: an information fusion platform for bio-network inference and analysis.

      Related Articles BioCAD: an information fusion platform for bio-network inference and analysis. BMC Bioinformatics. 2007;8 Suppl 9:S2 Authors: Lee D, Kim S, Kim Y BACKGROUND: As systems biology has begun to draw growing attention, bio-network inference and analysis have become more and more important. Though there have been many efforts for bio-network inference, they are still far from practical applications due to too many false inferences and lack of comprehensible interpretation in the biological viewpoints. In order for applying to real problems, they should provide effective inference, reliable validation, rational elucidation, and sufficient extensibility to incorporate various relevant ...
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    8. GO for gene documents.

      Related Articles GO for gene documents. BMC Bioinformatics. 2007;8 Suppl 9:S3 Authors: Srinivasan P, Qiu XY BACKGROUND: Annotating genes and their products with Gene Ontology codes is an important area of research. One approach is to use the information available about these genes in the biomedical literature. The goal in this paper, based on this approach, is to develop automatic annotation methods that can supplement the expensive manual annotation processes currently in place. RESULTS: Using a set of Support Vector Machines (SVM) classifiers we were able to achieve Fscores of 0.49, 0.41 and 0.33 for ...
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    9. A comparison study on algorithms of detecting long forms for short forms in biomedical text.

      Related Articles A comparison study on algorithms of detecting long forms for short forms in biomedical text. BMC Bioinformatics. 2007;8 Suppl 9:S5 Authors: Torii M, Hu ZZ, Song M, Wu CH, Liu H MOTIVATION: With more and more research dedicated to literature mining in the biomedical domain, more and more systems are available for people to choose from when building literature mining applications. In this study, we focus on one specific kind of literature mining task, i.e., detecting definitions of acronyms, abbreviations, and symbols in biomedical text. We denote acronyms, abbreviations, and symbols as short forms (SFs ...
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    10. A coherent graph-based semantic clustering and summarization approach for biomedical literature and a new summarization evaluation method.

      Related Articles A coherent graph-based semantic clustering and summarization approach for biomedical literature and a new summarization evaluation method. BMC Bioinformatics. 2007;8 Suppl 9:S4 Authors: Yoo I, Hu X, Song IY BACKGROUND: A huge amount of biomedical textual information has been produced and collected in MEDLINE for decades. In order to easily utilize biomedical information in the free text, document clustering and text summarization together are used as a solution for text information overload problem. In this paper, we introduce a coherent graph-based semantic clustering and summarization approach for biomedical literature. RESULTS: Our extensive experimental results show the ...
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    11. Extracting unrecognized gene relationships from the biomedical literature via matrix factorizations.

      Related Articles Extracting unrecognized gene relationships from the biomedical literature via matrix factorizations. BMC Bioinformatics. 2007;8 Suppl 9:S6 Authors: Kim H, Park H, Drake BL BACKGROUND: The construction of literature-based networks of gene-gene interactions is one of the most important applications of text mining in bioinformatics. Extracting potential gene relationships from the biomedical literature may be helpful in building biological hypotheses that can be explored further experimentally. Recently, latent semantic indexing based on the singular value decomposition (LSI/SVD) has been applied to gene retrieval. However, the determination of the number of factors k used in the reduced ...
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    12. Collection of cancer stage data by classifying free-text medical reports.

      Related Articles Collection of cancer stage data by classifying free-text medical reports. J Am Med Inform Assoc. 2007 Nov-Dec;14(6):736-45 Authors: McCowan IA, Moore DC, Nguyen AN, Bowman RV, Clarke BE, Duhig EE, Fry MJ Cancer staging provides a basis for planning clinical management, but also allows for meaningful analysis of cancer outcomes and evaluation of cancer care services. Despite this, stage data in cancer registries is often incomplete, inaccurate, or simply not collected. This article describes a prototype software system (Cancer Stage Interpretation System, CSIS) that automatically extracts cancer staging information from medical reports. The system uses ...
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      Mentions: Australia Brisbane
    13. Mining and analysing scale-free protein-protein interaction network.

      Related Articles Mining and analysing scale-free protein-protein interaction network. Int J Bioinform Res Appl. 2005;1(1):81-101 Authors: Hu X Protein-protein interaction network is essential to understand the fundamental processes that govern cell biology. In this paper, we integrate information extraction and data mining techniques to extract and mine the scale-free protein-protein interaction network from biomedical literature. The experiments on around 1,600 chromatin proteins indicate that our system is very promising for mining and analysing protein-protein interaction network. PMID: 18048123 [PubMed - indexed for MEDLINE]
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    14. A workflow for mutation extraction and structure annotation.

      Related Articles A workflow for mutation extraction and structure annotation. J Bioinform Comput Biol. 2007 Dec;5(6):1319-37 Authors: Kanagasabai R, Choo KH, Ranganathan S, Baker CJ Rich information on point mutation studies is scattered across heterogeneous data sources. This paper presents an automated workflow for mining mutation annotations from full-text biomedical literature using natural language processing (NLP) techniques as well as for their subsequent reuse in protein structure annotation and visualization. This system, called mSTRAP (Mutation extraction and STRucture Annotation Pipeline), is designed for both information aggregation and subsequent brokerage of the mutation annotations. It facilitates the coordination ...
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    15. Rapid pattern development for concept recognition systems: application to point mutations.

      Related Articles Rapid pattern development for concept recognition systems: application to point mutations. J Bioinform Comput Biol. 2007 Dec;5(6):1233-59 Authors: Caporaso JG, Baumgartner WA, Randolph DA, Cohen KB, Hunter L The primary biomedical literature is being generated at an unprecedented rate, and researchers cannot keep abreast of new developments in their fields. Biomedical natural language processing is being developed to address this issue, but building reliable systems often requires many expert-hours. We present an approach for automatically developing collections of regular expressions to drive high-performance concept recognition systems with minimal human interaction. We applied our approach to ...
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    16. GE-Miner: integration of cluster ensemble and text mining for comprehensive gene expression analysis.

      Related Articles GE-Miner: integration of cluster ensemble and text mining for comprehensive gene expression analysis. Int J Bioinform Res Appl. 2006;2(3):325-38 Authors: Hu X Generating high quality gene clusters and identifying the underlying biological mechanism of the gene clusters are the important goals of clustering gene expression analysis. Based on this consideration, we design and develop a unified system Gene Expression Miner (GE-Miner) by integrating cluster ensemble, text clustering and multidocument summarisation and provide an environment for comprehensive gene expression data analysis. Experimental results demonstrate that our systems can obtain high quality clusters and provide concise and ...
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    17. A thousand words in a scene.

      Related Articles A thousand words in a scene. IEEE Trans Pattern Anal Mach Intell. 2007 Sep;29(9):1575-89 Authors: Quelhas P, Monay F, Odobez JM, Gatica-Perez D, Tuytelaars T This paper presents a novel approach for visual scene modeling and classification, investigating the combined use of text modeling methods and local invariant features. Our work attempts to elucidate (1) whether a text-like bag-of-visterms representation (histogram of quantized local visual features) is suitable for scene (rather than object) classification, (2) whether some analogies between discrete scene representations and text documents exist, and (3) whether unsupervised, latent space models can be ...
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    18. Functional profiling of microarray experiments using text-mining derived bioentities.

      Related Articles Functional profiling of microarray experiments using text-mining derived bioentities. Bioinformatics. 2007 Nov 15;23(22):3098-9 Authors: Minguez P, Al-Shahrour F, Montaner D, Dopazo J MOTIVATION: The increasing use of microarray technologies brought about a parallel demand in methods for the functional interpretation of the results. Beyond the conventional functional annotations for genes, such as gene ontology, pathways, etc. other sources of information are still to be exploited. Text-mining methods allow extracting informative terms (bioentities) with different functional, chemical, clinical, etc. meanings, that can be associated to genes. We show how to use these associations within an appropriate ...
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      Mentions: Spain Valencia
    19. A semantic web approach applied to integrative bioinformatics experimentation: a biological use case with genomics data.

      Related Articles A semantic web approach applied to integrative bioinformatics experimentation: a biological use case with genomics data. Bioinformatics. 2007 Nov 15;23(22):3080-7 Authors: Post LJ, Roos M, Marshall MS, van Driel R, Breit TM MOTIVATION: The numerous public data resources make integrative bioinformatics experimentation increasingly important in life sciences research. However, it is severely hampered by the way the data and information are made available. The semantic web approach enhances data exchange and integration by providing standardized formats such as RDF, RDF Schema (RDFS) and OWL, to achieve a formalized computational environment. Our semantic web-enabled data integration ...
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    20. Mining experimental evidence of molecular function claims from the literature.

      Related Articles Mining experimental evidence of molecular function claims from the literature. Bioinformatics. 2007 Dec 1;23(23):3232-40 Authors: Crangle CE, Cherry JM, Hong EL, Zbyslaw A MOTIVATION: The rate at which gene-related findings appear in the scientific literature makes it difficult if not impossible for biomedical scientists to keep fully informed and up to date. The importance of these findings argues for the development of automated methods that can find, extract and summarize this information. This article reports on methods for determining the molecular function claims that are being made in a scientific article, specifically those that are ...
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    21. Leveraging the structure of the Semantic Web to enhance information retrieval for proteomics.

      Related Articles Leveraging the structure of the Semantic Web to enhance information retrieval for proteomics. Bioinformatics. 2007 Nov 15;23(22):3073-9 Authors: Smith A, Cheung K, Krauthammer M, Schultz M, Gerstein M MOTIVATION: Proteomics researchers need to be able to quickly retrieve relevant information from the web and the biomedical literature. To improve information retrieval, we leverage the structure of the semantic web, developing an approach for joining it with the largely opposing paradigm of unsupervised web search. RESULTS: Our approach uses a Resource-Description-Framework (RDF) graph that inter-relates documents through their associated biological identifiers (e.g., protein ID). A ...
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    22. Automatic Classification of Foot Examination Findings using Statistical Natural Language Processing and Machine Learning.

      Automatic Classification of Foot Examination Findings using Statistical Natural Language Processing and Machine Learning. J Am Med Inform Assoc. 2007 Dec 20; Authors: Pakhomov SV, Hanson PL, Bjornsen SS, Smith SA We examine the feasibility of a machine learning approach to identification of foot examination (FE) findings from the unstructured text of clinical reports. A Support Vector Machine (SVM) based system was constructed to process the text of physical examination sections of in- and out-patient clinical notes to identify if the findings of structural, neurological, and vascular components of a FE revealed normal or abnormal findings or were not assessed ...
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