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Rodriguez-Esteban, Raul. "Semantic persistence of ambiguous biomedical names in the citation network." Bioinformatics 36, no. 7 (December 12, 2019): 2224–28. http://dx.doi.org/10.1093/bioinformatics/btz923.
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Abstract Motivation Name ambiguity has long been a central problem in biomedical text mining. To tackle it, it has been usually assumed that names present only one meaning within a given text. It is not known whether this assumption applies beyond the scope of single documents. Results Using a new method that leverages large numbers of biomedical annotations and normalized citations, this study shows that ambiguous biomedical names mentioned in scientific articles tend to present the same meaning in articles that cite them or that they cite, and, to a lesser extent, two steps away in the citation network. Citations, therefore, can be regarded as semantic connections between articles and the citation network should be considered for tasks such as automatic name disambiguation, entity linking and biomedical database annotation. A simple experiment shows the applicability of these findings to name disambiguation. Availability and implementation The code used for this analysis is available at: https://github.com/raroes/one-sense-per-citation-network.
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JHA, RAHUL, AMJAD-ABU JBARA, VAHED QAZVINIAN, and DRAGOMIR R. RADEV. "NLP-driven citation analysis for scientometrics." Natural Language Engineering 23, no. 1 (January 25, 2016): 93–130. http://dx.doi.org/10.1017/s1351324915000443.
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AbstractThis paper summarizes ongoing research in Natural-Language-Processing-driven citation analysis and describes experiments and motivating examples of how this work can be used to enhance traditional scientometrics analysis that is based on simply treating citations as a ‘vote’ from the citing paper to cited paper. In particular, we describe our dataset for citation polarity and citation purpose, present experimental results on the automatic detection of these indicators, and demonstrate the use of such annotations for studying research dynamics and scientific summarization. We also look at two complementary problems that show up in Natural-Language-Processing-driven citation analysis for a specific target paper. The first problem is extracting citation context, the implicit citation sentences that do not contain explicit anchors to the target paper. The second problem is extracting reference scope, the target relevant segment of a complicated citing sentence that cites multiple papers. We show how these tasks can be helpful in improving sentiment analysis and citation-based summarization.
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McIntosh, John L. "Survivors of Suicide: A Comprehensive Bibliography." OMEGA - Journal of Death and Dying 16, no. 4 (June 1986): 355–70. http://dx.doi.org/10.2190/9njv-l843-xw6d-7mpv.
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A bibliography of the literature on survivors of suicide is presented. Journal articles, books, book chapters, abstracts in proceedings of professional meetings, and pamphlets on the topic of survivor-victims are listed. Brief annotations are provided for some citations.
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De, Soumya, R. Joe Stanley, Beibei Cheng, Sameer Antani, Rodney Long, and George Thoma. "Automated Text Detection and Recognition in Annotated Biomedical Publication Images." International Journal of Healthcare Information Systems and Informatics 9, no. 2 (April 2014): 34–63. http://dx.doi.org/10.4018/ijhisi.2014040103.
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Images in biomedical publications often convey important information related to an article's content. When referenced properly, these images aid in clinical decision support. Annotations such as text labels and symbols, as provided by medical experts, are used to highlight regions of interest within the images. These annotations, if extracted automatically, could be used in conjunction with either the image caption text or the image citations (mentions) in the articles to improve biomedical information retrieval. In the current study, automatic detection and recognition of text labels in biomedical publication images was investigated. This paper presents both image analysis and feature-based approaches to extract and recognize specific regions of interest (text labels) within images in biomedical publications. Experiments were performed on 6515 characters extracted from text labels present in 200 biomedical publication images. These images are part of the data set from ImageCLEF 2010. Automated character recognition experiments were conducted using geometry-, region-, exemplar-, and profile-based correlation features and Fourier descriptors extracted from the characters. Correct recognition as high as 92.67% was obtained with a support vector machine classifier, compared to a 75.90% correct recognition rate with a benchmark Optical Character Recognition technique.
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MacMullen, W. John. "Quantifying literature citations, index terms, and Gene Ontology annotations in the Saccharomyces Genome Database to assess results-set clustering utility." Proceedings of the American Society for Information Science and Technology 43, no. 1 (October 10, 2007): 1–17. http://dx.doi.org/10.1002/meet.14504301191.
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Cheng, Beibei, R. Joe Stanley, Soumya De, Sameer Antani, and George R. Thoma. "Automatic Detection of Arrow Annotation Overlays in Biomedical Images." International Journal of Healthcare Information Systems and Informatics 6, no. 4 (October 2011): 23–41. http://dx.doi.org/10.4018/jhisi.2011100102.
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Images in biomedical articles are often referenced for clinical decision support, educational purposes, and medical research. Authors-marked annotations such as text labels and symbols overlaid on these images are used to highlight regions of interest which are then referenced in the caption text or figure citations in the articles. Detecting and recognizing such symbols is valuable for improving biomedical information retrieval. In this research, image processing and computational intelligence methods are integrated for object segmentation and discrimination and applied to the problem of detecting arrows on these images. Evolving Artificial Neural Networks (EANNs) and Evolving Artificial Neural Network Ensembles (EANNEs) computational intelligence-based algorithms are developed to recognize overlays, specifically arrows, in medical images. For these discrimination techniques, EANNs use particle swarm optimization and genetic algorithm for artificial neural network (ANN) training, and EANNEs utilize the number of ANNs generated in an ensemble and negative correlation learning for neural network training based on averaging and Linear Vector Quantization (LVQ) winner-take-all approaches. Experiments performed on medical images from the imageCLEFmed’08 data set, yielded area under the receiver operating characteristic curve and precision/recall results as high as 0.988 and 0.928/0.973, respectively, using the EANNEs method with the winner-take-all approach.
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Dass, Gaurhari, Manh-Tu Vu, Pan Xu, Enrique Audain, Marc-Phillip Hitz, Björn A. Grüning, Henning Hermjakob, and Yasset Perez-Riverol. "The omics discovery REST interface." Nucleic Acids Research 48, W1 (May 6, 2020): W380—W384. http://dx.doi.org/10.1093/nar/gkaa326.
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Abstract The Omics Discovery Index is an open source platform that can be used to access, discover and disseminate omics datasets. OmicsDI integrates proteomics, genomics, metabolomics, models and transcriptomics datasets. Using an efficient indexing system, OmicsDI integrates different biological entities including genes, transcripts, proteins, metabolites and the corresponding publications from PubMed. In addition, it implements a group of pipelines to estimate the impact of each dataset by tracing the number of citations, reanalysis and biological entities reported by each dataset. Here, we present the OmicsDI REST interface (www.omicsdi.org/ws/) to enable programmatic access to any dataset in OmicsDI or all the datasets for a specific provider (database). Clients can perform queries on the API using different metadata information such as sample details (species, tissues, etc), instrumentation (mass spectrometer, sequencer), keywords and other provided annotations. In addition, we present two different libraries in R and Python to facilitate the development of tools that can programmatically interact with the OmicsDI REST interface.
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Segal, Lester A. "Azariah de' Rossi. The Light of the Eyes. Translated with introduction and annotations by Joanna Weinberg. Yale Judaica Series. New Haven: Yale University Press, 2001. xlix, 802 pp." AJS Review 29, no. 1 (April 2005): 200–203. http://dx.doi.org/10.1017/s0364009405430093.
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The central dimension of Azariah de' Rossi's complex and diverse treatise, Meءor עeinayim, is undoubtedly what Joanna Weinberg describes as “his real contribution to critical scholarship” (p. xxix), and this is especially evident in his innovative chapters on Philo, rabbinic aggadah and Jewish chronology. De' Rossi's studies are compounded by ponderous Hebrew prose replete with citations, proof-texts, references, and allusions. Nevertheless, Weinberg skillfully makes this classic manageable in English. Her abundant notes clarify the classical Jewish texts he addressed and the innumerable Jewish and non-Jewish sources from antiquity to the sixteenth century integral to his scholarly endeavor. The translation is also complemented by a comprehensive index of sources.
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Segal, Lester A. "Azariah de' Rossi. The Light of the Eyes. Translated with introduction and annotations by Joanna Weinberg. Yale Judaica Series. New Haven: Yale University Press, 2001. xlix, 802 pp." AJS Review 29, no. 1 (April 2005): 200–203. http://dx.doi.org/10.1017/s036400940544009x.
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The central dimension of Azariah de' Rossi's complex and diverse treatise, Meءor עeinayim, is undoubtedly what Joanna Weinberg describes as “his real contribution to critical scholarship” (p. xxix), and this is especially evident in his innovative chapters on Philo, rabbinic aggadah and Jewish chronology. De' Rossi's studies are compounded by ponderous Hebrew prose replete with citations, proof-texts, references, and allusions. Nevertheless, Weinberg skillfully makes this classic manageable in English. Her abundant notes clarify the classical Jewish texts he addressed and the innumerable Jewish and non-Jewish sources from antiquity to the sixteenth century integral to his scholarly endeavor. The translation is also complemented by a comprehensive index of sources.
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Cooling, Michael T., and Peter Hunter. "The CellML Metadata Framework 2.0 Specification." Journal of Integrative Bioinformatics 12, no. 2 (June 1, 2015): 86–103. http://dx.doi.org/10.1515/jib-2015-260.
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Summary The CellML Metadata Framework 2.0 is a modular framework that describes how semantic annotations should be made about mathematical models encoded in the CellML (www.cellml.org) format, and their elements. In addition to the Core specification, there are several satellite specifications, each designed to cater for model annotation in a different context. Basic Model Information, Citation, License and Biological Annotation specifications are presented.
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Mount, Sigrid Docken. "Evolutions in exhibition catalogues of African art." Art Libraries Journal 13, no. 3 (1988): 14–19. http://dx.doi.org/10.1017/s0307472200005769.
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Since their appearance in the early 20th century, catalogues prepared for exhibitions of African art have undergone a gradual transformation. Beginning as mere checklists many of these publications have, in the 1970s and 80s, evolved into major scholarly works whose significance transcends their original purpose as guides to the exhibitions. Changes occurring over the years are traced through examination of the form and content of representative catalogues and by review of the reception by art historians of many of these works into the corpus of literature of African art. The growing importance of exhibition catalogues as important art historical documents is also demonstrated by a chronological analysis of bibliographic citations in the major scholarly journal of African art in the United States. Finally, scrutiny of sources and annotations included in an important bibliographic guide to the literature of African art indicates how firmly established the exhibition catalogue has become as one of the most important publication forms for the dissemination of scholarly writing on African art.[This paper won the ARLIS/NA Gerd Muehsam Award for 1986. We hope to publish a sequel in a future issue, on exhibitions of African art in Africa and the development of catalogues written by Africans. Editor].
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Fontaine, Jean Fred, and Miguel A. Andrade-Navarro. "Gene Set to Diseases (GS2D): disease enrichment analysis on human gene sets with literature data." Genomics and Computational Biology 2, no. 1 (October 30, 2016): 33. http://dx.doi.org/10.18547/gcb.2016.vol2.iss1.e33.
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Large sets of candidate genes derived from high-throughput biological experiments can be characterized by functional enrichment analysis. The analysis consists of comparing the functions of one gene set against that of a background gene set. Then, functions related to a significant number of genes in the gene set are expected to be relevant. Web tools offering disease enrichment analysis on gene sets are often based on gene-disease associations from manually curated or experimental data that is accurate but does not cover all diseases discussed in the literature. Using associations automatically derived from literature data could be a cost effective method to improve the coverage of diseases for enrichment analysis at comparable levels of accuracy.
We have implemented a method named Gene set to Diseases, GS2D, as a web tool performing disease enrichment analysis on human protein coding gene sets. It uses an automatically built dataset of more than 63 thousand gene-disease associations defined as statistically significant co-occurrences of genes and diseases in annotations of biomedical citations from PubMed. The dataset covers more diseases for enrichment analysis than the largest comparable curated database, Comparative Toxicogenomics Database, and its performance compared favourably to similar approaches based on manually curated or experimental data. Graphical and programmatic interfaces are available at http://cbdm.uni-mainz.de/geneset2diseases.
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MATSUMORI, Hideyuki. "Citations of the Shi buer men (The Ten Aspects of Non-duality) in the Fahua wenju ji (The Annotations on "The Words and Phases of the Lotus Sutra") of Zhanran." Journal of Indian and Buddhist Studies (Indogaku Bukkyogaku Kenkyu) 57, no. 1 (2008): 39–42. http://dx.doi.org/10.4259/ibk.57.1_39.
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Wu, Bing, and Chen Yan Zhang. "Knowledge Sharing Research on Web 2.0." Applied Mechanics and Materials 631-632 (September 2014): 1136–39. http://dx.doi.org/10.4028/www.scientific.net/amm.631-632.1136.
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As Web 2.0 services emphasize the integration of distributed information and applications on a network, we gleaned from science citation index expanded (SCI-EXPANED) and Social Sciences Citation Index (SSCI) database on web of science, concerning advances in collaboration research in Web 2.0. The result indicates that the number of publication literatures on this topic mainly distributes in recent 7 years, and citations reach climax of 22 in 2013. The main research territory is USA, accounting for 40%. And from the analysis of research area, Engineering accounts for 40%. Overall, the related research topics can be classified in four areas: annotation system for knowledge sharing, determinants of knowledge sharing using Web 2.0, adoption of Web 2.0 for knowledge sharing and knowledge sharing successes in Web 2.0.
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Yasunaga, Michihiro, Jungo Kasai, Rui Zhang, Alexander R. Fabbri, Irene Li, Dan Friedman, and Dragomir R. Radev. "ScisummNet: A Large Annotated Corpus and Content-Impact Models for Scientific Paper Summarization with Citation Networks." Proceedings of the AAAI Conference on Artificial Intelligence 33 (July 17, 2019): 7386–93. http://dx.doi.org/10.1609/aaai.v33i01.33017386.
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Scientific article summarization is challenging: large, annotated corpora are not available, and the summary should ideally include the article’s impacts on research community. This paper provides novel solutions to these two challenges. We 1) develop and release the first large-scale manually-annotated corpus for scientific papers (on computational linguistics) by enabling faster annotation, and 2) propose summarization methods that integrate the authors’ original highlights (abstract) and the article’s actual impacts on the community (citations), to create comprehensive, hybrid summaries. We conduct experiments to demonstrate the efficacy of our corpus in training data-driven models for scientific paper summarization and the advantage of our hybrid summaries over abstracts and traditional citation-based summaries. Our large annotated corpus and hybrid methods provide a new framework for scientific paper summarization research.
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Yaniasih, Yaniasih, and Indra Budi. "Systematic Design and Evaluation of a Citation Function Classification Scheme in Indonesian Journals." Publications 9, no. 3 (June 28, 2021): 27. http://dx.doi.org/10.3390/publications9030027.
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Classifying citations according to function has many benefits when it comes to information retrieval tasks, scholarly communication studies, and ranking metric developments. Many citation function classification schemes have been proposed, but most of them have not been systematically designed for an extensive literature-based compilation process. Many schemes were also not evaluated properly before being used for classification experiments utilizing large datasets. This paper aimed to build and evaluate new citation function categories based upon sufficient scientific evidence. A total of 2153 citation sentences were collected from Indonesian journal articles for our dataset. To identify the new categories, a literature survey was conducted, analyses and groupings of category meanings were carried out, and then categories were selected based on the dataset’s characteristics and the purpose of the classification. The evaluation used five criteria: coherence, ease, utility, balance, and coverage. Fleiss’ kappa and automatic classification metrics using machine learning and deep learning algorithms were used to assess the criteria. These methods resulted in five citation function categories. The scheme’s coherence and ease of use were quite good, as indicated by an inter-annotator agreement value of 0.659 and a Long Short-Term Memory (LSTM) F1-score of 0.93. According to the balance and coverage criteria, the scheme still needs to be improved. This research data was limited to journals in food science published in Indonesia. Future research will involve classifying the citation function using a massive dataset collected from various scientific fields and published from some representative countries, as well as applying improved annotation schemes and deep learning methods.
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Urbanic, Allan. "Literaturnaia kritika i literaturovedenie na stranitsakh zarubezhnoi periodiki na russkom iazyke, 1980–1995: Sbornik referatov i annotatsii[Literary criticism and literary research on the pages of Russian-language émigré periodicals, 1980–1995: collection of citations and annotations], by G. Gezen and L. Khotin." Slavic & East European Information Resources 11, no. 4 (November 30, 2010): 389–90. http://dx.doi.org/10.1080/15228886.2010.523864.
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Lantz, Catherine, Glenda Maria Insua, Annie R. Armstrong, and Annie Pho. "Student bibliographies: charting research skills over time." Reference Services Review 44, no. 3 (August 8, 2016): 253–65. http://dx.doi.org/10.1108/rsr-12-2015-0053.
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Purpose The purpose of this study is to compare two bibliography assignments completed after one-shot library instruction to determine which research skills first-year students retain over the course of a semester. Design/methodology/approach A rubric was developed for citation analysis of student-annotated bibliographies and final bibliographies. Each assignment was scored on a three-point scale, and four criteria were assessed: the quality of sources used, variety of sources used, quality of annotations (for first assignment only) and citation accuracy. Findings Students scored highest on the quality of sources used in both assignments, although there was a statistically significant decline in overall scores from the first assignment to the second. Students had the most difficulty with writing annotations, followed closely by citation accuracy. Students primarily cited journal articles in their annotated bibliographies and reference sources in their final bibliographies. Website use increased notably from one assignment to the other. Originality/value This research is unique in its analysis of two separate bibliography assignments completed by first-year students over the course of a semester. It is of interest to librarians teaching one-shot library instruction or any librarian interested in assessing the research skills of first-year students.
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Девисилов and Vladimir Devisilov. "Bases of Scientific Data, Citation Index, and How to Increase It." Safety in Technosphere 5, no. 6 (December 25, 2016): 3–15. http://dx.doi.org/10.12737/24720.
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Scientometrical indicators for scientist activity, scientific magazines, citation indexes, methods of their definition and work with them have been considered. Main bases for scientific data – Scopus, Web of Science, Russian index of scientific citation (Russian science citation index) have been presented, rules of their use and work with them. Merits and demerits of the main scientometrical indicators are analyzed and recommendations for increase of scientist citation index are given. Scientific article’s structure, as well as requirements to its basic elements influencing a paper’s citation level, have been explained, recommendations for preparation of
such paper’s basic elements as its heading, abstract, keywords, citable sources’ bibliography have been given. The structure for the paper’s main text has been considered and recommendations on its writing have been given. A conclusion is drawn that one of the reasons related to low level citation of Russian scientists, and references to publications in Russian magazines is a lack of culture in writing of scientific papers and not observance of their preparation rules that complicates their annotation in bases of scientific data.
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Sang-Keum, Ou. "A Research on the Citation of the Classic Books in Lishan’s Annotations of Wenxuan." Chinese Studies 75 (June 30, 2021): 391–413. http://dx.doi.org/10.14378/kacs.2021.75.75.20.
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Michel, Franck, and The Bioschemas Community. "Bioschemas & Schema.org: a Lightweight Semantic Layer for Life Sciences Websites." Biodiversity Information Science and Standards 2 (May 22, 2018): e25836. http://dx.doi.org/10.3897/biss.2.25836.
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Web portals are commonly used to expose and share scientific data. They enable end users to find, organize and obtain data relevant to their interests. With the continuous growth of data across all science domains, researchers commonly find themselves overwhelmed as finding, retrieving and making sense of data becomes increasingly difficult. Search engines can help find relevant websites, but the short summarizations they provide in results lists are often little informative on how relevant a website is with respect to research interests. To yield better results, a strategy adopted by Google, Yahoo, Yandex and Bing involves consuming structured content that they extract from websites. Towards this end, the schema.org collaborative community defines vocabularies covering common entities and relationships (e.g., events, organizations, creative works) (Guha et al. 2016). Websites can leverage these vocabularies to embed semantic annotations within web pages, in the form of markup using standard formats. Search engines, in turn, exploit semantic markup to enhance the ranking of most relevant resources while providing more informative and accurate summarization. Additionally, adding such rich metadata is a step forward to make data FAIR, i.e. Findable, Accessible, Interoperable and Reusable. Although schema.org encompasses terms related to data repositories, datasets, citations, events, etc., it lacks specialized terms for modeling research entities. The Bioschemas community (Garcia et al. 2017) aims to extend schema.org to support markup for Life Sciences websites. A major pillar lies in reusing types from schema.org as well as well-adopted domain ontologies, while only proposing a limited set of new types. The goal is to enable semantic cross-linking between knowledge graphs extracted from marked-up websites. An overview of the main types is presented in Fig. 1. Bioschemas also provides profiles that specify how to describe an entity of some type. For instance, the protein profile requires a unique identifier, recommends to list transcribed genes and associated diseases, and points to recommended terms from the Protein Ontology and Semantic Science Integrated Ontology. The success of schema.org lies in its simplicity and the support by major search engines. By extending schema.org, Bioschemas enables life sciences research communities to benefit from a lightweight semantic layer on websites and thus facilitates discoverability and interoperability across them. From an initial pilot including just a few bio-types such as proteins and samples, the Bioschemas community has grown and is now opening up towards other disciplines. The biodiversity domain is a promising candidate for such further extensions. We can think of additional profiles to account for biodiversity-related information. For instance, since taxonomic registers are the backbone of many web portals and databases, new profiles could describe taxa and scientific names while reusing well-adopted vocabularies such as Darwin Core terms (Baskauf et al. 2016) or TDWG ontologies (TDWG Vocabulary Management Task Group 2013). Fostering the use of such markup by web portals reporting traits, observations or museum collections could not only improve information discovery using search engines, but could also be a key to spur large-scale biodiversity data integration scenarios.
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Wallace, Byron C., Anna Noel-Storr, Iain J. Marshall, Aaron M. Cohen, Neil R. Smalheiser, and James Thomas. "Identifying reports of randomized controlled trials (RCTs) via a hybrid machine learning and crowdsourcing approach." Journal of the American Medical Informatics Association 24, no. 6 (May 25, 2017): 1165–68. http://dx.doi.org/10.1093/jamia/ocx053.
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Abstract Objectives Identifying all published reports of randomized controlled trials (RCTs) is an important aim, but it requires extensive manual effort to separate RCTs from non-RCTs, even using current machine learning (ML) approaches. We aimed to make this process more efficient via a hybrid approach using both crowdsourcing and ML. Methods We trained a classifier to discriminate between citations that describe RCTs and those that do not. We then adopted a simple strategy of automatically excluding citations deemed very unlikely to be RCTs by the classifier and deferring to crowdworkers otherwise. Results Combining ML and crowdsourcing provides a highly sensitive RCT identification strategy (our estimates suggest 95%–99% recall) with substantially less effort (we observed a reduction of around 60%–80%) than relying on manual screening alone. Conclusions Hybrid crowd-ML strategies warrant further exploration for biomedical curation/annotation tasks.
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Schulte Nordholt, Larissa, and Dirk Alkemade. "Voetnootpraktijken." Tijdschrift voor geschiedenis 133, no. 1 (June 1, 2020): 77–87. http://dx.doi.org/10.5117/tvgesch2020.1.005.schu.
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Abstract On footnotesFootnotes are a crucial part of the historian’s craft. Yet, they are often construed as no more than tools, used by historians, and scientists, to refer to sources and relevant literature. By looking at several student handbooks on history writing and recent studies on annotation practices, we argue in this discussion article that footnotes are more than simple references to other people’s work and that historians would do well to reflect on this. Footnotes can help historians construct historiographical and scientific discussions, and are therefore inextricably linked to politics of representation, inclusion and exclusion. Footnotes, we argue, fulfill a social and political function as knowledge brokers. With the rise of citation indexes problems of self-citation and gender misattribution have recently received more attention. Research into the uses and misuses of footnotes can shine a light on citation practices that reflect inequalities within academia. Therefore, it is worth considering more closely what happens in the literal margins of history writing.
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Herzberg, Laura, and Harald Lüngen. "Types and annotation of reply relations in computer-mediated communication." European Journal of Applied Linguistics 7, no. 2 (September 2, 2019): 305–32. http://dx.doi.org/10.1515/eujal-2019-0006.
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AbstractThis paper presents types and annotation layers of reply relations in computer- mediated communication (CMC). Reply relations hold between post units in CMC interactions and describe references from one given post to a previous post. We classify three types of reply relations in CMC interactions: first, technical replies, i. e. the possibility to reply directly to a previous post by clicking a ‘reply’ button; second, indentations, e. g. in wiki talk pages in which users insert their contributions in the existing talk page by indenting them and third, interpretative reply relations, i. e. the reply action is not realised formally but signalled by other structural or linguistics means such as address markers ‘@’, greetings, citations and/or Q-A structures. We take a look at existing practices in the description and representation of such relations in corpora and examples of chat, Wikipedia talk pages, Twitter and blogs. We then provide an annotation proposal that combines the different levels of description and representation of reply relations and which adheres to the schemas and practices for encoding CMC corpus documents within the TEI framework as defined by the TEI CMC SIG. It constitutes a prerequisite for correctly identifying higher levels of interactional relations such as dialogue acts or discussion trees.
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Connors, Robert J. "The rhetoric of citation systems—Part I: The development of annotation structures from the renaissance to 1900*." Rhetoric Review 17, no. 1 (September 1998): 6–48. http://dx.doi.org/10.1080/07350199809359230.
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Faisal, Muhammad, Auliffi Ermian Challen, and Imelda Sari. "BUILDING MASTERY OF ACCOUNTING LITERATURE THROUGH REFERENCE MANAGEMENT SOFTWARE." Indonesian Journal of Engagement, Community Services, Empowerment and Development 1, no. 1 (April 19, 2021): 23–30. http://dx.doi.org/10.53067/ijecsed.v1i1.4.
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The rapid growth of accounting literature in the digital age is a challenge in studying accounting literature. Mastery of scientific literature is an ability that every student wants to have. Responding to the rapid development of accounting literacy, optimizing the use of reference management software should become a habit for students to answer the challenges of the rapid growth of the accounting literature. This article describes a combination method of utilizing a reference management program Mendeley into student lecture courses to help students master the rapidly evolving accounting literature using digital resources. The use of Mendeley software also helps students form annotation skills in compiling citation entries that are comprehensive and effective
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Sayers, Eric W., Jeff Beck, J. Rodney Brister, Evan E. Bolton, Kathi Canese, Donald C. Comeau, Kathryn Funk, et al. "Database resources of the National Center for Biotechnology Information." Nucleic Acids Research 48, no. D1 (October 11, 2019): D9—D16. http://dx.doi.org/10.1093/nar/gkz899.
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Abstract The National Center for Biotechnology Information (NCBI) provides a large suite of online resources for biological information and data, including the GenBank® nucleic acid sequence database and the PubMed database of citations and abstracts published in life science journals. The Entrez system provides search and retrieval operations for most of these data from 35 distinct databases. The E-utilities serve as the programming interface for the Entrez system. Custom implementations of the BLAST program provide sequence-based searching of many specialized datasets. New resources released in the past year include a new PubMed interface, a sequence database search and a gene orthologs page. Additional resources that were updated in the past year include PMC, Bookshelf, My Bibliography, Assembly, RefSeq, viral genomes, the prokaryotic genome annotation pipeline, Genome Workbench, dbSNP, BLAST, Primer-BLAST, IgBLAST and PubChem. All of these resources can be accessed through the NCBI home page at www.ncbi.nlm.nih.gov.
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Ma, Juncai, Linhuan Wu, and İpek Kurtböke. "Skerman and beyond: 2019 status of the Global Catalogue of Microorganisms." Microbiology Australia 40, no. 3 (2019): 121. http://dx.doi.org/10.1071/ma19033.
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The World Federation for Culture Collections (WFCC)-MIRCEN World Data Centre for Microorganisms (WDCM) was set up as a data centre of WFCC and UNESCO World Network of Microbiological Resources Centres (MIRCEN). The WDCM is a vehicle for networking microbial resource centres of various types of microorganisms. It also serves as an information resource for the customers of the microbial resource centres (http://www.wdcm.org/). The WDCM was established in 1966 by the late Professor V.B.D. Skerman in Australia, later moved to Japan in 1986 and since 2010 is based in China under the Directorship of Dr Juncai Ma. Current databases at the WDCM are the Culture Collections Information Worldwide (CCINFO), Global Catalogue of Microorganisms (GCM) and the WDCM Reference Strain Catalogue. In addition, Analyzer of Bio-resource citations (ABC) and Statistics on Patented Microorganisms are available (http://www.wdcm.org/databases.html). In this article the status of the GCM and its associated 10K type strain sequencing project that currently provides services to taxonomists for standard genome sequencing and annotation will be communicated.
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Xun, Guangxu, Kishlay Jha, Ye Yuan, Yaqing Wang, and Aidong Zhang. "MeSHProbeNet: a self-attentive probe net for MeSH indexing." Bioinformatics 35, no. 19 (March 9, 2019): 3794–802. http://dx.doi.org/10.1093/bioinformatics/btz142.
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Abstract Motivation MEDLINE is the primary bibliographic database maintained by National Library of Medicine (NLM). MEDLINE citations are indexed with Medical Subject Headings (MeSH), which is a controlled vocabulary curated by the NLM experts. This greatly facilitates the applications of biomedical research and knowledge discovery. Currently, MeSH indexing is manually performed by human experts. To reduce the time and monetary cost associated with manual annotation, many automatic MeSH indexing systems have been proposed to assist manual annotation, including DeepMeSH and NLM’s official model Medical Text Indexer (MTI). However, the existing models usually rely on the intermediate results of other models and suffer from efficiency issues. We propose an end-to-end framework, MeSHProbeNet (formerly named as xgx), which utilizes deep learning and self-attentive MeSH probes to index MeSH terms. Each MeSH probe enables the model to extract one specific aspect of biomedical knowledge from an input article, thus comprehensive biomedical information can be extracted with different MeSH probes and interpretability can be achieved at word level. MeSH terms are finally recommended with a unified classifier, making MeSHProbeNet both time efficient and space efficient. Results MeSHProbeNet won the first place in the latest batch of Task A in the 2018 BioASQ challenge. The result on the last test set of the challenge is reported in this paper. Compared with other state-of-the-art models, such as MTI and DeepMeSH, MeSHProbeNet achieves the highest scores in all the F-measures, including Example Based F-Measure, Macro F-Measure, Micro F-Measure, Hierarchical F-Measure and Lowest Common Ancestor F-measure. We also intuitively show how MeSHProbeNet is able to extract comprehensive biomedical knowledge from an input article.
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Tang, Jiaxin, Yang Chen, Guozhen She, Yang Xu, Kewei Sha, Xin Wang, Yi Wang, Zhenhua Zhang, and Pan Hui. "Identifying Mis-Configured Author Profiles on Google Scholar Using Deep Learning." Applied Sciences 11, no. 15 (July 27, 2021): 6912. http://dx.doi.org/10.3390/app11156912.
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Google Scholar has been a widely used platform for academic performance evaluation and citation analysis. The issue about the mis-configuration of author profiles may seriously damage the reliability of the data, and thus affect the accuracy of analysis. Therefore, it is important to detect the mis-configured author profiles. Dealing with this issue is challenging because the scale of the dataset is large and manual annotation is time-consuming and relatively subjective. In this paper, we first collect a dataset of Google Scholar’s author profiles in the field of computer science and compare the mis-configured author profiles with the reliable ones. Then, we propose an integrated model that utilizes machine learning and node embedding to automatically detect mis-configured author profiles. Additionally, we conduct two application case studies based on the data of Google Scholar, i.e., outstanding scholar searching and university ranking, to demonstrate how the improved dataset after filtering out the mis-configured author profiles will change the results. The two case studies validate the importance and meaningfulness of the detection of mis-configured author profiles.
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Pu, Juncai, Yue Yu, Yiyun Liu, Lu Tian, Siwen Gui, Xiaogang Zhong, Chu Fan, et al. "MENDA: a comprehensive curated resource of metabolic characterization in depression." Briefings in Bioinformatics 21, no. 4 (June 3, 2019): 1455–64. http://dx.doi.org/10.1093/bib/bbz055.
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Abstract Depression is a seriously disabling psychiatric disorder with a significant burden of disease. Metabolic abnormalities have been widely reported in depressed patients and animal models. However, there are few systematic efforts that integrate meaningful biological insights from these studies. Herein, available metabolic knowledge in the context of depression was integrated to provide a systematic and panoramic view of metabolic characterization. After screening more than 10 000 citations from five electronic literature databases and five metabolomics databases, we manually curated 5675 metabolite entries from 464 studies, including human, rat, mouse and non-human primate, to develop a new metabolite-disease association database, called MENDA (http://menda.cqmu.edu.cn:8080/index.php). The standardized data extraction process was used for data collection, a multi-faceted annotation scheme was developed, and a user-friendly search engine and web interface were integrated for database access. To facilitate data analysis and interpretation based on MENDA, we also proposed a systematic analytical framework, including data integration and biological function analysis. Case studies were provided that identified the consistently altered metabolites using the vote-counting method, and that captured the underlying molecular mechanism using pathway and network analyses. Collectively, we provided a comprehensive curation of metabolic characterization in depression. Our model of a specific psychiatry disorder may be replicated to study other complex diseases.
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Schrijvers, Marloes, Tanja Janssen, Olivia Fialho, and Gert Rijlaarsdam. "Gaining Insight Into Human Nature: A Review of Literature Classroom Intervention Studies." Review of Educational Research 89, no. 1 (November 22, 2018): 3–45. http://dx.doi.org/10.3102/0034654318812914.
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In this review, we explore whether and how literature education may foster adolescent students’ insight into human nature. A systematic search of five databases was complemented with citation tracking, hand searches, and expert consultation. We included 13 experimental and quasi-experimental intervention studies. Methodological quality and quality-of-intervention descriptions were assessed. Analysis of empirical support for expected intervention effects indicated that, under certain conditions, literature education may foster students’ insight into human nature. One intervention affected students’ insight into themselves, two affected their understanding of fictional others, and six affected their understanding of, views on, or intended behavior toward real-world others. Subsequent analysis of interventions with full or partial empirical support yielded instructional design principles on (a) text selection; (b) activating, annotating, and reflecting on personal life and reading experiences in writing activities; and (c) verbally sharing these experiences with others in exploratory dialogues. Limitations and implications for future studies are discussed.
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Buneman, Peter, Heiko Müller, and Chris Rusbridge. "Curating the CIA World Factbook." International Journal of Digital Curation 4, no. 3 (December 7, 2009): 29–43. http://dx.doi.org/10.2218/ijdc.v4i3.126.
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The CIA World Factbook is a prime example of a curated database – a database that is constructed and maintained with a great deal of human effort in collecting, verifying, and annotating data. Preservation of old versions of the Factbook is important for verification of citations; it is also essential for anyone interested in the history of the data such as demographic change. Although the Factbook has been published, both physically and electronically, only for the past 30 years, we appear in danger of losing this history. This paper investigates the issues involved in capturing the history of an evolving database and its application to the CIA World Factbook. In particular it shows that there is substantial added value to be gained by preserving databases in such a way that questions about the change in data, (longitudinal queries) can be readily answered. Within this paper, we describe techniques for recording change in a curated database and we describe novel techniques for querying the change. Using the example of this archived curated database, we discuss the extent to which the accepted practices and terminology of archiving, curation and digital preservation apply to this important class of digital artefacts.
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Andreev, Dmitrii N., Yury A. Kucheryavyy, Aleksandr N. Kaziulin, and Igor V. Maev. "Effect of adjuvant therapy with butyric acid on the safety profile of oral antibiotic therapy: a meta-analysis of controlled studies." Consilium Medicum 23, no. 5 (2021): 402–6. http://dx.doi.org/10.26442/20751753.2021.5.200883.
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Aim. Systematization of data on the effect of adjuvant therapy with butyric acid (BA) on the safety profile of oral antibiotic therapy (ABT). Methods. Search of studies were carried out in MEDLINE/PubMed, EMBASE, Cochrane, Google Scholar, Russian Science Citation Index (RSCI) electronic databases until April 2021 inclusive. We analyzed titles and annotations in the named databases. The following combination of keywords was used for the search: "butyric acid" or "butyrate" + "antibiotic therapy" or "antibiotics" or "eradication" or "eradication therapy", as well as their analogs in English for searching in foreign databases. Results. The meta-analysis included 9 controlled studies (1 – Italy, 8 – Russia) involving 1409 patients (700 – in groups with BA; 709 – in comparison groups). Meta-analysis showed that the addition of BA to ABT regimens contributes to a significant reduction in the overall incidence of gastrointestinal side effects (odds ratio – OR 0.424, 95% confidence interval – CI 0.218–0.824), the incidence of diarrhea during the 1st (OR 0.228 , 95% CI 0.103–0.507) and 2nd week (OR 0.141, 95% CI 0.0732–0.271), abdominal distention during 1st (OR 0.392, 95% CI 0.180–0.854) and 2nd week ( OR 0.136, 95% CI 0.0480–0.384), bitterness in the mouth during 2nd week (OR 0.284, 95% CI 0.115–0.700). Conclusion. A meta-analysis has shown that the inclusion of BA in ABT regimens significantly reduces the incidence of side effects (diarrhea, bloating, bitterness in the mouth).
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Sakurai, Nozomu, Takeshi Ara, Mitsuo Enomoto, Takeshi Motegi, Yoshihiko Morishita, Atsushi Kurabayashi, Yoko Iijima, et al. "Tools and Databases of the KOMICS Web Portal for Preprocessing, Mining, and Dissemination of Metabolomics Data." BioMed Research International 2014 (2014): 1–11. http://dx.doi.org/10.1155/2014/194812.
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A metabolome—the collection of comprehensive quantitative data on metabolites in an organism—has been increasingly utilized for applications such as data-intensive systems biology, disease diagnostics, biomarker discovery, and assessment of food quality. A considerable number of tools and databases have been developed to date for the analysis of data generated by various combinations of chromatography and mass spectrometry. We report here a web portal named KOMICS (The Kazusa Metabolomics Portal), where the tools and databases that we developed are available for free to academic users. KOMICS includes the tools and databases for preprocessing, mining, visualization, and publication of metabolomics data. Improvements in the annotation of unknown metabolites and dissemination of comprehensive metabolomic data are the primary aims behind the development of this portal. For this purpose, PowerGet and FragmentAlign include a manual curation function for the results of metabolite feature alignments. A metadata-specific wiki-based database, Metabolonote, functions as a hub of web resources related to the submitters' work. This feature is expected to increase citation of the submitters' work, thereby promoting data publication. As an example of the practical use of KOMICS, a workflow for a study onJatropha curcasis presented. The tools and databases available at KOMICS should contribute to enhanced production, interpretation, and utilization of metabolomic Big Data.
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Laak, Marin, Kaarel Veskis, Olga Gerassimenko, Neeme Kahusk, and Kadri Vider. "Digidokumendist tekstikorpuseks: Semperi ja Barbaruse kirjavahetuse töötlemine masinanalüüsitavaks päringusüsteemis KORP." Eesti ja soome-ugri keeleteaduse ajakiri. Journal of Estonian and Finno-Ugric Linguistics 10, no. 2 (February 10, 2020): 25–44. http://dx.doi.org/10.12697/jeful.2019.10.2.02.
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Kirjandusteadlaste ja arvutilingvistide koostöös katseprojektina valminud Johannes Semperi ja Johannes Barbaruse kirjavahetuse korpus on nii kirjanduslooliselt kui tekstilingvistiliselt huvipakkuv digitaalandmestik. Kirjandusteadlastele avab kaasaegsete digitaalsete meetodite kasutuselevõtt huvitavaid uurimisperspektiive ja vanade uurimistulemuste ülekontrollimise võimalusi arvutuslike meetoditega. Korpuslingvistidele on aga väljakutseks ajaloolise ja isikupärase keelekasutusega, erinevatest keeltest kubiseva ja rohkete koha-, aja- ja isikuviidetega tekstimaterjali ettevalmistamine rikkalikult märgendatud korpuseks. Artikkel peatub üksikasjalikumalt nii käsikirjalise materjali digitaalseks tekstiandmestikuks ettevalmistamise kui ka analüüsi- ja märgendamisprotsessi probleemidel ja nende võimalikel lahendustel. Kasutajatele tutvustatakse ka korpuste päringusüsteemi KORP võimalusi sarnaste tekstide uurimiseks.
Abstract. Marin Laak, Kaarel Veskis, Kadri Vider, Neeme Kahusk, and Olga Gerassimenko: Turning from digital document to text corpus: conversion of correspondence between Semper and Barbarus to a machine-readable unit in KORP. The article describes a joined pilot project of literary scholars and language technologists that resulted in a correspondence corpus of Estonian avant-garde poets Johannes Semper and Johannes Barbarus. The corpus is an inspiring digital dataset both for literary and linguistic researches. Contemporary digital methods allow literary scholars to find new interesting research perspectives and to revise the old research results with computational methods. Corpus linguists can find interesting challenges in historically and personally unique language use of the correspondents, in multiple languages used for citations and language play, in multiple references to places, events and persons in the textual material that was transformed to an annotated corpus. The article describes the preparation of typed-in manuscript material for a digital dataset in detail, problems of annotation and analysis and their possible solutions. The reader will get an insight to the possibilities that corpus query system KORP offers for the research of similar textual material.
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Cristia, Alejandrina, Federica Bulgarelli, and Elika Bergelson. "Accuracy of the Language Environment Analysis System Segmentation and Metrics: A Systematic Review." Journal of Speech, Language, and Hearing Research 63, no. 4 (April 27, 2020): 1093–105. http://dx.doi.org/10.1044/2020_jslhr-19-00017.
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Purpose The Language Environment Analysis (LENA) system provides automated measures facilitating clinical and nonclinical research and interventions on language development, but there are only a few, scattered independent reports of these measures' validity. The objectives of the current systematic review were to (a) discover studies comparing LENA output with manual annotation, namely, accuracy of talker labels, as well as involving adult word counts (AWCs), conversational turn counts (CTCs), and child vocalization counts (CVCs); (b) describe them qualitatively; (c) quantitatively integrate them to assess central tendencies; and (d) quantitatively integrate them to assess potential moderators. Method Searches on Google Scholar, PubMed, Scopus, and PsycInfo were combined with expert knowledge, and interarticle citations resulting in 238 records screened and 73 records whose full text was inspected. To be included, studies must target children under the age of 18 years and report on accuracy of LENA labels (e.g., precision and/or recall) and/or AWC, CTC, or CVC (correlations and/or error metrics). Results A total of 33 studies, in 28 articles, were discovered. A qualitative review revealed most validation studies had not been peer reviewed as such and failed to report key methodology and results. Quantitative integration of the results was possible for a broad definition of recall and precision ( M = 59% and 68%, respectively; N = 12–13), for AWC (mean r = .79, N = 13), CVC (mean r = .77, N = 5), and CTC (mean r = .36, N = 6). Publication bias and moderators could not be assessed meta-analytically. Conclusion Further research and improved reporting are needed in studies evaluating LENA segmentation and quantification accuracy, with work investigating CTC being particularly urgent. Supplemental Material https://osf.io/4nhms/
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DURDEN, LANCE A., and NANCY E. ADAMS. "Primary type specimens of sucking lice (Insecta: Phthiraptera: Anoplura) in the U.S. National Museum of Natural History, Smithsonian Institution." Zootaxa 1047, no. 1 (September 8, 2005): 21. http://dx.doi.org/10.11646/zootaxa.1047.1.2.
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An annotated list is presented of the 110 primary types (holotypes, lectotypes, syntypes, or neotypes) of sucking lice (Insecta: Phthiraptera: Anoplura) deposited in the U.S. National Museum of Natural History (USNM), Smithsonian Institution, as of May 2005. Annotations for each taxon are listed alphabetically by specific epithet, and are followed by the original generic assignment and (in parentheses) the current family designation. Next, the author, year of description, and original citation are provided. The primary type held in the USNM (with USNM type number, slide number and other relevant data, if these were assigned), original collection data, current taxonomic assignment (if different from the original designation), and additional taxonomic remarks, if relevant, are then given. Brief information on allotypes and paratypes are included if these are mounted on the same microscope slide as the primary type or if they are otherwise relevant. The types include those of the type species of seven genera (Abrocomaphthirus Durden & Webb, Atopophthirus Kim & Emerson, Haematopinoides Osborn, Latagophthirus Kim & Emerson, Pecaroecus Babcock &Ewing, Phthirpediculus Ewing, and Sathrax Johnson) one of which is the type genus of a family (Pecaroecidae). Primary types for five species of Anoplura that have not yet been described, and for another four species that were described in an unpublished dissertation are also deposited in the USNM. Hosts and collection data for these nine specimens are briefly mentioned after the main list; however, species names are excluded because these names currently have no nomenclatural standing. A neotype specimen is designated for Haematopinus montanus Osborn, 1896, a taxon which is currently treated as a junior synonym of Linognathoides laeviusculus (Grube, 1851).
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Hu, Yanhui, Verena Chung, Aram Comjean, Jonathan Rodiger, Fnu Nipun, Norbert Perrimon, and Stephanie E. Mohr. "BioLitMine: Advanced Mining of Biomedical and Biological Literature About Human Genes and Genes from Major Model Organisms." G3: Genes|Genomes|Genetics 10, no. 12 (October 7, 2020): 4531–39. http://dx.doi.org/10.1534/g3.120.401775.
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The accumulation of biological and biomedical literature outpaces the ability of most researchers and clinicians to stay abreast of their own immediate fields, let alone a broader range of topics. Although available search tools support identification of relevant literature, finding relevant and key publications is not always straightforward. For example, important publications might be missed in searches with an official gene name due to gene synonyms. Moreover, ambiguity of gene names can result in retrieval of a large number of irrelevant publications. To address these issues and help researchers and physicians quickly identify relevant publications, we developed BioLitMine, an advanced literature mining tool that takes advantage of the medical subject heading (MeSH) index and gene-to-publication annotations already available for PubMed literature. Using BioLitMine, a user can identify what MeSH terms are represented in the set of publications associated with a given gene of the interest, or start with a term and identify relevant publications. Users can also use the tool to find co-cited genes and a build a literature co-citation network. In addition, BioLitMine can help users build a gene list relevant to a MeSH term, such as a list of genes relevant to “stem cells” or “breast neoplasms.” Users can also start with a gene or pathway of interest and identify authors associated with that gene or pathway, a feature that makes it easier to identify experts who might serve as collaborators or reviewers. Altogether, BioLitMine extends the value of PubMed-indexed literature and its existing expert curation by providing a robust and gene-centric approach to retrieval of relevant information.
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Chen, Yili, Thomas W. Blackwell, Jing Gao, Anura Hewagama, Heather M. Grifka, Angel W. Lee, and David J. States. "Computational Prediction of c-MYC Binding and Action by Integration of Multiple Data Sources." Blood 108, no. 11 (November 16, 2006): 4345. http://dx.doi.org/10.1182/blood.v108.11.4345.4345.
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Abstract c-MYC is an important proto-oncogene. Its actions are mediated by sequence specific binding of the c-MYC protein to genomic DNA. While many c-MYC recognition sites can be identified in c-MYC responsive genes, many others are associated with genes showing no c-MYC response. It is not yet known how the cell determines which of the many c-MYC recognition sites are biologically active and directly bind c-MYC protein to regulate gene expression. We have developed a computational model that predict c-MYC binding and functional activation as distinct processes. Our model integrates four types of evidence to predict functional c-MYC targets: genomic sequence, MYC binding, gene expression and gene function annotations. First, a Bayesian network classifier is used to predict c-MYC recognition sites likely to exhibit high occupancy binding in chromatin immunoprecipitation studies using several types of sequence information, including predicted DNA methylation using a computational model to estimate the likelihood of genomic DNA methylation. In the second step, the DNA binding probability of MYC is combined with the gene expression information from 9 independent microarray datasets in multiple tissues and the gene function annotations in Gene Ontology to predict the c-MYC targets. The prediction results were compared with the c-MYC targets in public MYC target database [www.myccancergene.org], which collected the c-MYC targets identified in biomedical literatures. In total, we predicted 599 likely c-MYC genes on human genome, of which 73 have been reported to be both bound and regulated by MYC, 83 are bound by MYC in vivo and another 93 are MYC regulated. The approach thus successfully identified many known c-MYC targets as well as suggesting many novel sites including many sites that are remote from the transcription start site. Our findings suggest that to identify c-MYC genomic targets, any study based on single high throughput dataset is likely to be insufficient. Using multiple gene expression datasets helps to improve the sensitivity and integration of different data sources helps to improve the specificity. Summary of c-MYC Targets Prediction Microarray Dataset Data Source (Citation) Tissue Predicted Targets Binding&Regulation Reported Only Binding Reported Only Regulation Reported 1 PMID: 15778709 B Cell 421 61 60 56 2 PMID: 12086878 Prostate Cancer 428 56 65 76 3 PMID: 14722351 Prostate Cancer 50 4 7 13 4 PMID: 15254046 Prostate Cancer 66 19 8 14 5 PMID: 12747878 Breast Cancer 17 1 3 5 6 PMID: 11707567 Lung Cancer 295 51 42 59 7 PMID: 15820940 CML 8 1 1 2 8 PMID: 12704389 ALL 222 45 32 46 9 PMID: 11731795 ALL / MLL / AML 22 6 1 6 Total 599 73 83 93
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Borodina, V. A. "Master-class: from a bibliographic lists to mapping its content (evidently for modeling an exhibition)." Bibliosphere, no. 3 (September 30, 2016): 87–94. http://dx.doi.org/10.20913/1815-3186-2016-3-87-93.
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An innovative component of modern library-information education should become a trend, in which frames it is possible not only to compact and intensify the study of professional issues, but also to shape tools for future professional activities in the innovation logic of an effective character. This in turn requires integrating multiple types of work in a holistic format. A master class on modeling personal exhibitions and its results in developing problems of reading study with application of bibliographic reconstruction and knowledge mapping is chosen as one of these formats. In the master class course a complex of tasks was solved. Among them are the following: developing the strategy of exhibition modeling, its understanding according to the completeness of information and its degree of semantic coagulation as a way to learn and present information in the exhibition format; forming the communicative culture in the exhibition presentation process; improving analytical skills, creative thinking, and improvement of psychologic-pedagogical professionalism through familiarization with the personal contribution of a scientist related to readers study; the acquisition of knowledge and skills to map knowledge. The exhibition was carried out in several stages in the logic «from simple to complex» and starts with learning the exhibition structural design options, their semantic and color solutions; exploring the scientist contribution based on the bibliographic description of publications, annotations and abstracts, later on the basis of studying publications themselves and citation. The latter allows not only to map its content in different ways, but also to build the professional communication sociometric matrix. As a result of this master class with elements of a business game students acquire specific knowledge (in our case readers’ study); a various options of a personal exhibition intelligent-information products are created; the specialist intellectual capacity grows significantly, cognitive and metacognitive skills of specialists are developed; methodological knowledge based on innovative search activities is formed. The heuristic potential of the master class lies in the fact that the tendency to internal resources of a personality determining the propensity to innovate in their professional activities is clearly expressed in the world and domestic science.
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Cohen, Aaron M., Neil R. Smalheiser, Marian S. McDonagh, Clement Yu, Clive E. Adams, John M. Davis, and Philip S. Yu. "Automated confidence ranked classification of randomized controlled trial articles: an aid to evidence-based medicine." Journal of the American Medical Informatics Association 22, no. 3 (February 5, 2015): 707–17. http://dx.doi.org/10.1093/jamia/ocu025.
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ABSTRACT Objective: For many literature review tasks, including systematic review (SR) and other aspects of evidence-based medicine, it is important to know whether an article describes a randomized controlled trial (RCT). Current manual annotation is not complete or flexible enough for the SR process. In this work, highly accurate machine learning predictive models were built that include confidence predictions of whether an article is an RCT. Materials and Methods: The LibSVM classifier was used with forward selection of potential feature sets on a large human-related subset of MEDLINE to create a classification model requiring only the citation, abstract, and MeSH terms for each article. Results: The model achieved an area under the receiver operating characteristic curve of 0.973 and mean squared error of 0.013 on the held out year 2011 data. Accurate confidence estimates were confirmed on a manually reviewed set of test articles. A second model not requiring MeSH terms was also created, and performs almost as well. Discussion: Both models accurately rank and predict article RCT confidence. Using the model and the manually reviewed samples, it is estimated that about 8000 (3%) additional RCTs can be identified in MEDLINE, and that 5% of articles tagged as RCTs in Medline may not be identified. Conclusion: Retagging human-related studies with a continuously valued RCT confidence is potentially more useful for article ranking and review than a simple yes/no prediction. The automated RCT tagging tool should offer significant savings of time and effort during the process of writing SRs, and is a key component of a multistep text mining pipeline that we are building to streamline SR workflow. In addition, the model may be useful for identifying errors in MEDLINE publication types. The RCT confidence predictions described here have been made available to users as a web service with a user query form front end at: http://arrowsmith.psych.uic.edu/cgi-bin/arrowsmith_uic/RCT_Tagger.cgi.
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Hodgson, Cynthia. "NOTEWORTHY: NISO Recommended Practice on Test Modes for SUSHI Servers Issued for Trial Use; NISO Receives Mellon Foundation Grant for E-Book Annotation Sharing Workshops; Journal Usage Factors Project Publishes Results, Recommendations, and Next Steps; ISO Focus+ Magazine Now Available for Free Download; OpenURL Canonical Citation Profile Approved." Information Standards Quarterly 23, no. 3 (2011): 30. http://dx.doi.org/10.3789/isqv23n3.2011.08.
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Piazza, Rocco, Luca Mologni, Daniele Ramazzotti, Roberta Spinelli, Alessandra Pirola, Luca De Sano, Pierangelo Ferrari, et al. "Oncoscore, a Novel, Internet-Based Tool to Assess the Oncogenic Potential of Genes Can Differentiate Between CP-CML and BC-CML Associated Genes, and Between CP-CML Patients with Good and Bad Prognosis." Blood 128, no. 22 (December 2, 2016): 3075. http://dx.doi.org/10.1182/blood.v128.22.3075.3075.
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Abstract INTRODUCTION The huge amount of data emerging from Next-Generation Sequencing (NGS) projects is bringing a revolution in cancer medicine, leading to the discovery of a large number of new somatic alterations that are associated with the onset and/or progression of cancer. However, researchers are facing a formidable challenge in identifying oncogenic driver genes among the variants generated by NGS experiments. METHODS To overcome these limitations, we developed OncoScore, a bioinformatics text-mining tool capable of automatically scanning the biomedical literature by means of dynamically updatable web queries and measuring gene-specific cancer association in terms of gene citations (submitted). OncoScore is distributed as a R Bioconductor package (https://bioconductor.org/packages/release/bioc/html/OncoScore.html) and as a web tool (http://www.galseq.com/oncoscore.html). To assess the ability of OncoScore to discriminate between cancer and non-cancer genes we generated the OncoScore estimation for the whole Cancer Genes Census (CGC; 507 genes) dataset and for a manually curated list of genes not associated to cancer (nCan; 302 genes). The distribution of OncoScore values differed significantly between the two groups (mean: 48.8 and 14.8 for CGC and nCan, respectively; p-value = 2.2e-16). The receiver operating characteristic (ROC) curve and the area under the curve (AUC) metrics confirmed the excellent capability of OncoScore in discriminating the true positive from the true negative cancer genes at different cut-off values (OncoScore cut-off threshold = 21.09; AUC1 = 90.3%, 95% CI: 88.1-92.5). RESULTS To test OncoScore, we generated whole-exome sequencing data on 33 Chronic Myeloid Leukemia patients, 23 in Chronic Phase (CP) and 10 in Blast Crisis (BC). In order to selectively identify somatic mutations, CP samples were filtered against the germline exome data, while BC was filtered against the corresponding CP exome (thus filtering out all passenger mutations present at diagnosis). A total of 107 and 34 nonsynonymous somatic variants were identified in CP and BC, respectively. The mean OncoScore value of the BC samples was higher than that of CP ones (mean OncoScore = 35.6 ± 4.91 SEM vs. 19.2 ± 2.07 SEM; p=0.0007). Manual inspection of the 10 BC genes with the highest OncoScore values highlighted the presence of at least 5 genes (ABL1, NRAS, ASXL1, RUNX1, IKZF1) that were demonstrated to be functionally associated with CML progression, suggesting that OncoScore was able to correctly prioritize biologically relevant cancer genes relevant to CML progression. The 107 non-synonymous variants (range 0-11 per patient) identified in CP-CML patients at diagnosis were further analyzed. A positive correlation was observed between number of mutations and patient age (r=0.4638; p=0.0258), indicating that several events were passenger mutations being expanded by neoplastic transformation. However, when using OncoScore to weigh the oncogenic potential of each mutation, a significant correlation was observed between the Sokal score and OncoScore (r=0.6815, p=0.0003) suggesting that the identified mutations may have clinical impact.. On long term follow-up (>2 years), 17 CML patients remained on standard imatinib therapy while 6 were shifted to 2nd/3rdline therapy because of resistance to imatinib. According to OncoScore, the 6 imatinib-resistant patients had significantly higher scores at diagnosis than the 17 long-term imatinib responders (measured as the sum of all mutations with Oncoscore values >21: 120±16 SEM vs. 50±15; p=0.0098). No significant differences were instead observed in the Sokal score among the two groups (1.15±0.3 vs. 0.9±0.1, p=0.244). Among the identified genes with high OncoScore values, only ASXL1 was associated with hematological malignancies. CONCLUSIONS These data indicate that OncoScore is a useful prioritization tool for the annotation of somatic mutations in human cancer. Genes mutated selectively in BC samples had higher OncoScore values than genes mutated in CP at diagnosis (which contain also many passenger mutations). In addition, OncoScore can identify some genes mutated in CML patients at diagnosis which could be relevant for response to treatment, although not usually linked to hematological malignancies. Disclosures Gambacorti-Passerini: Pfizer: Consultancy, Research Funding; Bristol-Myers Squibb: Consultancy.
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Rodriguez-Esteban, Raul. "Biomedical articles share annotations with their citation neighbors." BMC Bioinformatics 22, no. 1 (February 26, 2021). http://dx.doi.org/10.1186/s12859-021-04044-4.
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Abstract Background Numerous efforts have been poured into annotating the wealth of knowledge contained in biomedical articles. Thanks to such efforts, it is now possible to quantitatively explore relations between these annotations and the citation network at large scale. Results With the aid of several large and small annotation databases, this study shows that articles share annotations with their citation neighborhood to the point that the neighborhood’s most common annotations are likely to be those appearing in the article. Conclusions These findings posit that an article’s citation neighborhood defines to a large extent the article’s annotated content. Thus, citations should be considered as a foundation for future knowledge management and annotation of biomedical articles.
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"Bibliographical Citations and Annotations." Studies in the Age of Chaucer 23, no. 1 (2001): 627–93. http://dx.doi.org/10.1353/sac.2001.0011.
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