Recent Advances and Emerging Applications in Text and Data Mining for Biomedical Discovery - Wikidata - wikimedia - TriplyDB

Recent Advances and Emerging Applications in Text and Data Mining for Biomedical Discovery

Recent Advances and Emerging Applications in Text and Data Mining for Biomedical Discovery

http://www.wikidata.org/entity/Q28082443

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The academic, economic and societal impacts of Open Access: an evidence-based review Internet Databases of the Properties, Enzymatic Reactions, and Metabolism of Small Molecules-Search Options and Applications in Food Science Combining QSAR Modeling and Text-Mining Techniques to Link Chemical Structures and Carcinogenic Modes of Action BELMiner: adapting a rule-based relation extraction system to extract biological expression language statements from bio-medical literature evidence sentences.Natural Language Processing for EHR-Based Pharmacovigilance: A Structured Review.Coreference resolution improves extraction of Biological Expression Language statements from texts.Consensus strategy in genes prioritization and combined bioinformatics analysis for preeclampsia pathogenesis Biomedical text mining for research rigor and integrity: tasks, challenges, directions.Bridging semantics and syntax with graph algorithms-state-of-the-art of extracting biomedical relations.Prodromal signs and symptoms of serious infections with tocilizumab treatment for rheumatoid arthritis: Text mining of the Japanese postmarketing adverse event-reporting database.DES-TOMATO: A Knowledge Exploration System Focused On Tomato Species.Text Mining in Biomedical Domain with Emphasis on Document Clustering.A novel data-driven workflow combining literature and electronic health records to estimate comorbidities burden for a specific disease: a case study on autoimmune comorbidities in patients with celiac disease.A comparison of graph- and kernel-based -omics data integration algorithms for classifying complex traits.The research on gene-disease association based on text-mining of PubMed.A comprehensive and quantitative comparison of text-mining in 15 million full-text articles versus their corresponding abstracts.Finding novel relationships with integrated gene-gene association network analysis of Synechocystis sp. PCC 6803 using species-independent text-mining.Chemical–gene relation extraction using recursive neural network.Classification of Pediatric Asthma: From Phenotype Discovery to Clinical Practice

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Recent Advances and Emerging Applications in Text and Data Mining for Biomedical Discovery

http://www.wikidata.org/entity/Q28082443

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2016 nî lūn-bûn

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2016年の論文

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2016年論文

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Briefings in Bioinformatics

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Recent Advances and Emerging A ...... ining for Biomedical Discovery

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Anna C. Greene

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Britton C. Goodale

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Casey S. Greene

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Tasnia Tahsin

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Getting started in text mining

PubMed and beyond: a survey of web tools for searching biomedical literature

Gene ontology: tool for the unification of biology

The InterPro protein families database: the classification resource after 15 years

A large-scale evaluation of computational protein function prediction

A proteome-wide protein interaction map for Campylobacter jejuni

GeneMANIA: a real-time multiple association network integration algorithm for predicting gene function

Integration of text- and data-mining using ontologies successfully selects disease gene candidates

Speeding disease gene discovery by sequence based candidate prioritization

GeneSeeker: extraction and integration of human disease-related information from web-based genetic databases

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33-42

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scholarly article

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281392

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10.1093/BIB/BBV087

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1

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17

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Graciela Gonzalez

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2016-01-01T00:00:00Z

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282346289

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26420781

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