1. 2617-2640 of 2861 « 1 2 ... 107 108 109 110 111 112 113 ... 118 119 120 »
    1. Detection of Iupac and IUPAC-like chemical names.

      Related Articles Detection of IUPAC and IUPAC-like chemical names. Bioinformatics. 2008 Jul 1;24(13):i268-76 Authors: Klinger R, Kolárik C, Fluck J, Hofmann-Apitius M, Friedrich CM MOTIVATION: Chemical compounds like small signal molecules or other biological active chemical substances are an important entity class in life science publications and patents. Several representations and nomenclatures for chemicals like SMILES, InChI, IUPAC or trivial names exist. Only SMILES and InChI names allow a direct structure search, but in biomedical texts trivial names and Iupac like names are used more frequent. While trivial names can be found with a dictionary-based approach ...
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    2. Identifying gene-disease associations using centrality on a literature mined gene-interaction network.

      Related Articles Identifying gene-disease associations using centrality on a literature mined gene-interaction network. Bioinformatics. 2008 Jul 1;24(13):i277-85 Authors: Ozgür A, Vu T, Erkan G, Radev DR MOTIVATION: Understanding the role of genetics in diseases is one of the most important aims of the biological sciences. The completion of the Human Genome Project has led to a rapid increase in the number of publications in this area. However, the coverage of curated databases that provide information manually extracted from the literature is limited. Another challenge is that determining disease-related genes requires laborious experiments. Therefore, predicting good candidate ...
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    3. Seeking a new biology through text mining.

      Related Articles Seeking a new biology through text mining. Cell. 2008 Jul 11;134(1):9-13 Authors: Rzhetsky A, Seringhaus M, Gerstein M Tens of thousands of biomedical journals exist, and the deluge of new articles in the biomedical sciences is leading to information overload. Hence, there is much interest in text mining, the use of computational tools to enhance the human ability to parse and understand complex text. PMID: 18614002 [PubMed - indexed for MEDLINE]
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    4. Integrating high dimensional bi-directional parsing models for gene mention tagging.

      Related Articles Integrating high dimensional bi-directional parsing models for gene mention tagging. Bioinformatics. 2008 Jul 1;24(13):i286-94 Authors: Hsu CN, Chang YM, Kuo CJ, Lin YS, Huang HS, Chung IF MOTIVATION: Tagging gene and gene product mentions in scientific text is an important initial step of literature mining. In this article, we describe in detail our gene mention tagger participated in BioCreative 2 challenge and analyze what contributes to its good performance. Our tagger is based on the conditional random fields model (CRF), the most prevailing method for the gene mention tagging task in BioCreative 2. Our tagger ...
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    5. Nonnegative matrix factorization: an analytical and interpretive tool in computational biology.

      Related Articles Nonnegative matrix factorization: an analytical and interpretive tool in computational biology. PLoS Comput Biol. 2008 Jul;4(7):e1000029 Authors: Devarajan K In the last decade, advances in high-throughput technologies such as DNA microarrays have made it possible to simultaneously measure the expression levels of tens of thousands of genes and proteins. This has resulted in large amounts of biological data requiring analysis and interpretation. Nonnegative matrix factorization (NMF) was introduced as an unsupervised, parts-based learning paradigm involving the decomposition of a nonnegative matrix V into two nonnegative matrices, W and H, via a multiplicative updates algorithm. In ...
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    6. Extraction of recommendation features in radiology with natural language processing: exploratory study.

      Related Articles Extraction of recommendation features in radiology with natural language processing: exploratory study. AJR Am J Roentgenol. 2008 Aug;191(2):313-20 Authors: Dang PA, Kalra MK, Blake MA, Schultz TJ, Halpern EF, Dreyer KJ OBJECTIVE: The purposes of this study were to validate a natural language processing program for extraction of recommendation features, such as recommended time frames and imaging technique, from electronic radiology reports and to assess patterns of recommendation features in a large database of radiology reports. MATERIALS AND METHODS: This study was performed on a radiology reports database covering the years 1995-2004. From this database ...
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    7. Turning Informal Thesauri Into Formal Ontologies: A Feasibility Study on Biomedical Knowledge re-Use.

      Turning Informal Thesauri Into Formal Ontologies: A Feasibility Study on Biomedical Knowledge re-Use. Comp Funct Genomics. 2003;4(1):94-7 Authors: Hahn U This paper reports a large-scale knowledge conversion and curation experiment. Biomedical domain knowledge from a semantically weak and shallow terminological resource, the UMLS, is transformed into a rigorous description logics format. This way, the broad coverage of the UMLS is combined with inference mechanisms for consistency and cycle checking. They are the key to proper cleansing of the knowledge directly imported from the UMLS, as well as subsequent updating, maintenance and refinement of large knowledge repositories. The ...
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      Mentions: Germany Freiburg
    8. A web service for biomedical term look-up.

      A web service for biomedical term look-up. Comp Funct Genomics. 2005;6(1-2):86-93 Authors: Harkema H, Roberts I, Gaizauskas R, Hepple M Recent years have seen a huge increase in the amount of biomedical information that is available in electronic format. Consequently, for biomedical researchers wishing to relate their experimental results to relevant data lurking somewhere within this expanding universe of on-line information, the ability to access and navigate biomedical information sources in an efficient manner has become increasingly important. Natural language and text processing techniques can facilitate this task by making the information contained in textual resources such ...
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    9. Analysis of the Ijcnn 2007 agnostic learning vs. prior knowledge challenge.

      Related Articles Analysis of the IJCNN 2007 agnostic learning vs. prior knowledge challenge. Neural Netw. 2008 Mar-Apr;21(2-3):544-50 Authors: Guyon I, Saffari A, Dror G, Cawley G We organized a challenge for IJCNN 2007 to assess the added value of prior domain knowledge in machine learning. Most commercial data mining programs accept data pre-formatted in the form of a table, with each example being encoded as a linear feature vector. Is it worth spending time incorporating domain knowledge in feature construction or algorithm design, or can off-the-shelf programs working directly on simple low-level features do better than skilled ...
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    10. Identification of OBO nonalignments and its implications for OBO enrichment.

      Related Articles Identification of OBO nonalignments and its implications for OBO enrichment. Bioinformatics. 2008 Jun 15;24(12):1448-55 Authors: Bada M, Hunter L MOTIVATION: Existing projects that focus on the semiautomatic addition of links between existing terms in the Open Biomedical Ontologies can take advantage of reasoners that can make new inferences between terms that are based on the added formal definitions and that reflect nonalignments between the linked terms. However, these projects require that these definitions be necessary and sufficient, a strong requirement that often does not hold. If such definitions cannot be added, the reasoners cannot point ...
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    11. Universal and adapted vocabularies for generic visual categorization.

      Related Articles Universal and adapted vocabularies for generic visual categorization. IEEE Trans Pattern Anal Mach Intell. 2008 Jul;30(7):1243-56 Authors: Perronnin F Generic Visual Categorization (GVC) is the pattern classification problem which consists in assigning labels to an image based on its semantic content. This is a challenging task as one has to deal with inherent object/scene variations as well as changes in viewpoint, lighting and occlusion. Several state-of-the-art GVC systems use a vocabulary of visual terms to characterize images with a histogram of visual word counts. We propose a novel practical approach to GVC based on ...
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      Mentions: France Meylan
    12. Neurolinguistic approach to natural language processing with applications to medical text analysis.

      Neurolinguistic approach to natural language processing with applications to medical text analysis. Neural Netw. 2008 Jun 7; Authors: Duch W, Matykiewicz P, Pestian J Understanding written or spoken language presumably involves spreading neural activation in the brain. This process may be approximated by spreading activation in semantic networks, providing enhanced representations that involve concepts not found directly in the text. The approximation of this process is of great practical and theoretical interest. Although activations of neural circuits involved in representation of words rapidly change in time snapshots of these activations spreading through associative networks may be captured in a vector ...
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    13. PuReD-MCL: a graph-based PubMed document clustering methodology.

      PuReD-MCL: a graph-based PubMed document clustering methodology. Bioinformatics. 2008 Jul 1; Authors: Theodosiou T, Darzentas N, Angelis L, Ouzounis CA MOTIVATION: Biomedical literature is the principal repository of biomedical knowledge, with PubMed being the most complete database collecting, organising, and analysing such textual knowledge. There are numerous efforts that attempt to exploit this information by using text mining and machine learning techniques. We developed a novel approach, called PuReD-MCL (Pubmed Related Documents-MCL), which is based on the graph clustering algorithm MCL and relevant resources from PubMed. METHODS: PuReD-MCL avoids using natural language processing (NLP) techniques directly; instead, it takes advantage ...
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    14. GAPscreener: an automatic tool for screening human genetic association literature in PubMed using the support vector machine technique.

      Related Articles GAPscreener: an automatic tool for screening human genetic association literature in PubMed using the support vector machine technique. BMC Bioinformatics. 2008;9:205 Authors: Yu W, Clyne M, Dolan SM, Yesupriya A, Wulf A, Liu T, Khoury MJ, Gwinn M BACKGROUND: Synthesis of data from published human genetic association studies is a critical step in the translation of human genome discoveries into health applications. Although genetic association studies account for a substantial proportion of the abstracts in PubMed, identifying them with standard queries is not always accurate or efficient. Further automating the literature-screening process can reduce the burden ...
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    15. Auditory mismatch negativity for speech sound contrasts is modulated by language context.

      Auditory mismatch negativity for speech sound contrasts is modulated by language context. Neuroreport. 2008 Jul 2;19(10):1079-1083 Authors: Lipski SC, Mathiak K Auditory mismatch negativity is known to reflect language experience. This study wants to clarify whether this effect is dependent on language context. We compared German subjects' magnetic mismatch negativity in response to a non-native speech contrast presented with and without the context of a native contrast. The presence of the native contrast abolished the response to the nonnative sound at the left hemisphere and reduced the right-sided response. A significant context effect set in 170 ms ...
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    16. Use and misuse of the gene ontology annotations.

      Related Articles Use and misuse of the gene ontology annotations. Nat Rev Genet. 2008 Jul;9(7):509-15 Authors: Rhee SY, Wood V, Dolinski K, Draghici S The Gene Ontology (GO) project is a collaboration among model organism databases to describe gene products from all organisms using a consistent and computable language. GO produces sets of explicitly defined, structured vocabularies that describe biological processes, molecular functions and cellular components of gene products in both a computer- and human-readable manner. Here we describe key aspects of GO, which, when overlooked, can cause erroneous results, and address how these pitfalls can be ...
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      Mentions: California Stanford
    17. Genetic algorithms for data-driven web question answering.

      Related Articles Genetic algorithms for data-driven web question answering. Evol Comput. 2008;16(1):89-125 Authors: Figueroa AG, Neumann G We present an evolutionary approach for the computation of exact answers to natural languages (NL) questions. Answers are extracted directly from the N-best snippets, which have been identified by a standard Web search engine using NL questions. The core idea of our evolutionary approach to Web question answering is to search for those substrings in the snippets whose contexts are most similar to contexts of already known answers. This context model together with the words mentioned in the NL question ...
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    18. Relevance-based feature extraction for hyperspectral images.

      Related Articles Relevance-based feature extraction for hyperspectral images. IEEE Trans Neural Netw. 2008 Apr;19(4):658-72 Authors: Mendenhall MJ, Merenyi E Hyperspectral imagery affords researchers all discriminating details needed for fine delineation of many material classes. This delineation is essential for scientific research ranging from geologic to environmental impact studies. In a data mining scenario, one cannot blindly discard information because it can destroy discovery potential. In a supervised classification scenario, however, the preselection of classes presents one with an opportunity to extract a reduced set of meaningful features without degrading classification performance. Given the complex correlations found in ...
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    19. Semantic Role Labeling for Protein Transport Predicates.

      Semantic Role Labeling for Protein Transport Predicates. BMC Bioinformatics. 2008 Jun 11;9(1):277 Authors: Bethard S, Lu Z, Martin JH, Hunter L ABSTRACT: BACKGROUND: Automatic semantic role labeling (SRL) is a natural language processing (NLP) technique that maps sentences to semantic representations. This technique has been widely studied in the recent years, but mostly with data in newswire domains. Here, we report on a SRL model for identifying the semantic roles of biomedical predicates describing protein transport in GeneRIFs --- manually curated sentences focusing on gene functions. To avoid the computational cost of syntactic parsing, and because the boundaries ...
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    20. A de-identifier for medical discharge summaries.

      Related Articles A de-identifier for medical discharge summaries. Artif Intell Med. 2008 Jan;42(1):13-35 Authors: Uzuner O, Sibanda TC, Luo Y, Szolovits P OBJECTIVE: Clinical records contain significant medical information that can be useful to researchers in various disciplines. However, these records also contain personal health information (PHI) whose presence limits the use of the records outside of hospitals. The goal of de-identification is to remove all PHI from clinical records. This is a challenging task because many records contain foreign and misspelled PHI; they also contain PHI that are ambiguous with non-PHI. These complications are compounded by ...
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    21. MedEvi: retrieving textual evidence of relations between biomedical concepts from Medline.

      Related Articles MedEvi: retrieving textual evidence of relations between biomedical concepts from Medline. Bioinformatics. 2008 Jun 1;24(11):1410-2 Authors: Kim JJ, Pezik P, Rebholz-Schuhmann D Search engines running on MEDLINE abstracts have been widely used by biologists to find publications that are related to their research. The existing search engines such as PubMed, however, have limitations when applied for the task of seeking textual evidence of relations between given concepts. The limitations are mainly due to the problem that the search engines do not effectively deal with multi-term queries which may imply semantic relations between the terms. To ...
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    22. Use of Radcube for Extraction of Finding Trends in a Large Radiology Practice.

      Related Articles Use of Radcube for Extraction of Finding Trends in a Large Radiology Practice. J Digit Imaging. 2008 Jun 10; Authors: Dang PA, Kalra MK, Blake MA, Schultz TJ, Stout M, Halpern EF, Dreyer KJ The purpose of our study was to demonstrate the use of Natural Language Processing (Leximer), along with Online Analytic Processing, (NLP-OLAP), for extraction of finding trends in a large radiology practice. Prior studies have validated the Natural Language Processing (NLP) program, Leximer for classifying unstructured radiology reports based on the presence of positive radiology findings (F (POS)) and negative radiology findings (F (NEG)). The ...
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    23. Identification of transcription factor contexts in literature using machine learning approaches.

      Related Articles Identification of transcription factor contexts in literature using machine learning approaches. BMC Bioinformatics. 2008;9 Suppl 3:S11 Authors: Yang H, Nenadic G, Keane JA BACKGROUND: Availability of information about transcription factors (TFs) is crucial for genome biology, as TFs play a central role in the regulation of gene expression. While manual literature curation is expensive and labour intensive, the development of semi-automated text mining support is hindered by unavailability of training data. There have been no studies on how existing data sources (e.g. TF-related data from the MeSH thesaurus and GO ontology) or potentially noisy example ...
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