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NLPropTest: Parsing English to Property-Based Tests with Categorial Grammars ...
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NLPropTest: Parsing English to Property-Based Tests with Categorial Grammars ...
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On the Transferability of Pre-trained Language Models for Low-Resource Programming Languages ...
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Chen, Fuxiang. - : Federated Research Data Repository / dépôt fédéré de données de recherche, 2022
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CSRS: Code Search with Relevance Matching and Semantic Matching ...
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Evaluating Video Conferencing Software for Remote Working Using Two-Stage Grey MCDM: A Case Study from Vietnam
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In: Mathematics; Volume 10; Issue 6; Pages: 946 (2022)
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Determinants of Adherence to a “GRADIOR” Computer-Based Cognitive Training Program in People with Mild Cognitive Impairment (MCI) and Mild Dementia
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In: Journal of Clinical Medicine; Volume 11; Issue 6; Pages: 1714 (2022)
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Potentials and Challenges in Students’ Meaning-Making via Sign Systems
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In: Multimodal Technologies and Interaction; Volume 6; Issue 2; Pages: 9 (2022)
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Are You Robert or RoBERTa? Deceiving Online Authorship Attribution Models Using Neural Text Generators
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Appendix _ A systematic mapping study on the application of design thinking in requirement engineering ...
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Appendix _ A systematic mapping study on the application of design thinking in requirement engineering ...
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31 |
Using social media and personality traits to assess software developers' emotions ...
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32 |
Using social media and personality traits to assess software developers' emotions ...
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Detecting Privacy Requirements from User Stories with NLP Transfer Learning Models ...
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Using Campaign Communications to Analyze Civility in Ranked Choice Voting Elections
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In: Politics and Governance ; 9 ; 2 ; 280-292 ; The Politics, Promise and Peril of Ranked Choice Voting (2022)
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LPInsider: a webserver for lncRNA–protein interaction extraction from the literature
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In: BMC Bioinformatics (2022)
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Abstract:
BACKGROUND: Long non-coding RNA (LncRNA) plays important roles in physiological and pathological processes. Identifying LncRNA–protein interactions (LPIs) is essential to understand the molecular mechanism and infer the functions of lncRNAs. With the overwhelming size of the biomedical literature, extracting LPIs directly from the biomedical literature is essential, promising and challenging. However, there is no webserver of LPIs relationship extraction from literature. RESULTS: LPInsider is developed as the first webserver for extracting LPIs from biomedical literature texts based on multiple text features (semantic word vectors, syntactic structure vectors, distance vectors, and part of speech vectors) and logistic regression. LPInsider allows researchers to extract LPIs by uploading PMID, PMCID, PMID List, or biomedical text. A manually filtered and highly reliable LPI corpus is integrated in LPInsider. The performance of LPInsider is optimal by comprehensive experiment on different combinations of different feature and machine learning models. CONCLUSIONS: LPInsider is an efficient analytical tool for LPIs that helps researchers to enhance their comprehension of lncRNAs from text mining, and also saving their time. In addition, LPInsider is freely accessible from http://www.csbg-jlu.info/LPInsider/ with no login requirement. The source code and LPIs corpus can be downloaded from https://github.com/qiufengdiewu/LPInsider. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12859-022-04665-3.
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Software
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URL: https://doi.org/10.1186/s12859-022-04665-3 http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9013167/ http://www.ncbi.nlm.nih.gov/pubmed/35428172
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