A5101837634- Biomedical Text Mining and Ontologies
- Topic Modeling
- Organophosphorus compounds synthesis
- Metal-Organic Frameworks: Synthesis and Applications
- Advanced Text Analysis Techniques
- Phosphorus compounds and reactions
- Synthesis and Reactivity of Sulfur-Containing Compounds
- Sentiment Analysis and Opinion Mining
- Natural Language Processing Techniques
- Bioinformatics and Genomic Networks
- Genomics and Rare Diseases
- Healthcare Education and Workforce Issues
- Cancer-related molecular mechanisms research
- Hedgehog Signaling Pathway Studies
- Intelligent Tutoring Systems and Adaptive Learning
- Education, Safety, and Science Studies
- Chemical Synthesis and Characterization
- Sulfur Compounds in Biology
- FOXO transcription factor regulation
- Genetics, Bioinformatics, and Biomedical Research
- Academic Publishing and Open Access
- Text Readability and Simplification
- Organometallic Compounds Synthesis and Characterization
- Chemical Synthesis and Analysis
- Career Development and Diversity
Chongqing Medical University
2025
Minzu University of China
2024
Jinan University
2024
Guangzhou University
2021-2023
Xi’an University of Posts and Telecommunications
2022-2023
European Bioinformatics Institute
2020-2023
Wellcome Trust
2020-2023
Zhejiang Hospital
2022
Northwest University
2021
Donghua University
2011
Abstract Europe PMC (https://europepmc.org) is a database of research articles, including peer reviewed full text articles and abstracts, preprints - all freely available for use via website, APIs bulk download. This article outlines new developments since 2017 where work has focussed on three key areas: (i) added to its core content include life science preprint abstracts special collection COVID-19-related preprints. unique as an aggregator biomedical alongside peer-reviewed with over 180...
Triple-negative breast cancer (TNBC) is a highly lethal malignancy with limited therapy options. Aberrant metabolism, key hallmark of human cancers, plays crucial role in tumor progression, therapeutic responses and TNBC-related death. However, the underlying mechanisms are not fully understood. In this study, we delineate previously unrecognized aberrant glucose metabolism regulating turnover Snail1, which transcriptional factor epithelial-mesenchymal transition (EMT) critically contributes...
Natural language processing (NLP) tasks aim to convert unstructured text data (e.g. articles or dialogues) structured information. In recent years, we have witnessed fundamental advances of NLP technique, which has been widely used in many applications such as financial mining, news recommendation and machine translation. However, its application the biomedical space remains challenging due a lack labeled data, ambiguities inconsistencies biological terminology. marker discovery studies,...
Named entity recognition (NER) is a widely used text-mining and natural language processing (NLP) subtask. In recent years, deep learning methods have superseded traditional dictionary- rule-based NER approaches. A high-quality dataset essential to fully leverage advancements. While several gold-standard corpora for biomedical entities in abstracts exist, only few are based on full-text research articles. The Europe PMC literature database routinely annotates Gene/Proteins, Diseases,...
ADVERTISEMENT RETURN TO ISSUEPREVArticleNEXTAsymmetric synthesis of a potent and selective competitive NMDA antagonistGregory S. Hamilton, Zhiwen Huang, Xiao Jing Yang, Raymond J. Patch, B. A. Narayanan, John W. FerkanyCite this: Org. Chem. 1993, 58, 25, 7263–7270Publication Date (Print):December 1, 1993Publication History Published online1 May 2002Published inissue 1 December 1993https://pubs.acs.org/doi/10.1021/jo00077a058https://doi.org/10.1021/jo00077a058research-articleACS...
Abstract Motivation The associations between biomarkers and human diseases play a key role in understanding complex pathology developing targeted therapies. Wet lab experiments for biomarker discovery are costly, laborious time-consuming. Computational prediction methods can be used to greatly expedite the identification of candidate biomarkers. Results Here, we present novel computational model named GTGenie predicting biomarker–disease based on graph text features. In GTGenie, attention...
Identifying biomarkers of Multiple Sclerosis is important for the diagnosis and treatment Sclerosis. The existing study has shown that miRNA one most diseases. However, few methods are designed predicting Sclerosis-related miRNAs. To fill this gap, we proposed a novel computation framework Sclerosis-associated uses network representation model to learn feature deep learning-based predict miRNAs associated with evaluation result shows can precisely. In addition, outperform several in large margin.
ADVERTISEMENT RETURN TO ISSUEPREVArticleNEXTSynthesis and conformational analysis of torsionally constrained 1,3,2-dioxaphosphepanesWilliam N. Setzer, Milton L. Brown, Xiao Jing Yang, Melody A. Thompson, Kylen W. WhitakerCite this: J. Org. Chem. 1992, 57, 10, 2812–2818Publication Date (Print):May 1, 1992Publication History Published online1 May 2002Published inissue 1 1992https://pubs.acs.org/doi/10.1021/jo00036a011https://doi.org/10.1021/jo00036a011research-articleACS PublicationsRequest...
Graph Neural Networks (GNNs) have significantly advanced various downstream graph-relevant tasks, encompassing recommender systems, molecular structure prediction, social media analysis, etc. Despite the boosts of GNN, recent research has empirically demonstrated its potential vulnerability to backdoor attacks, wherein adversaries employ triggers poison input samples, inducing GNN adversary-premeditated malicious outputs. This is typically due controlled training process, or deployment...
ABSTRACT Named entity recognition (NER) is a widely used text-mining and natural language processing (NLP) sub-task. In recent years, deep learning methods have superseded traditional dictionary, rule-based NER approaches. A high-quality dataset essential to take full advantage of the advancements. While several gold standard corpora for biomedical entities in abstracts exist, only few are based on full-text research articles. The Europe PMC literature database routinely annotates...
College counselor is one of the hit groups for job burnout, which directly harms psychological health and college education quality. Based on localized contract theory, author analyzes four aspects: normative obligation: ambiguity in duty boundaries non-identity financial return; interpersonal lack necessary support humanistic care; developmental obscurity career development limit promotion; effective interaction care. It comes to a conclusion that violation main cause burnout counselors....
ABSTRACT: Cation adsorbent was prepared from the Solidago Canadensis（which are abandoned agricultural land of alien invasive plants）by Sulfuric acid esterification modified , isoamyl alcohol as reaction medium. Design L934 orthogonal experiment, canadensis cation exchange adsorbent, optimal preparation conditions. Experimental results show that at 15°C, concentrated sulfuric and amyl volume ratio 5:6 obtained under conditions for Pb(II) best. The experimental adsorption onto Canadensis based...
Text matching is a fundamental task in natural language processing. It widely used information retrieval, text excavation and other fields. There are many problems, such as multiple meanings of words improper word segmentation text. These problems lead to the contextual sentences implied semantic not being extracted effectively. Therefore, we propose Multi-granularity Knowledge Enhancement (MGKE) model. Firstly, perform embedding at character granularity. At same time, HowNet external...
Conversational sentiment recognition has been widely used in people's lives and work. However, machines do not understand emotions through common-sense cognition. We propose an Incremental Encoding Transformer Incorporating Common-sense Awareness (IETCA) model. The model helps the use knowledge to better conversation. uses a context-aware graph attention mechanism obtain knowledge-rich utterance representations incremental encoding get rich contextual representations. some experiments on...
Unethical pro-organizational behavior (UPB) is one type of crucial organizational behaviors within work environments which aroused the academic interest researchers recently over past few decades.However, we still know little about how things are going under complex and uncertain environmental conditions.The present study explores influence paradoxical leader (PLB) on followers' unethical with followers perceived inclusive climate being mediator frequent change moderator based social...
Abstract ChemInform is a weekly Abstracting Service, delivering concise information at glance that was extracted from about 100 leading journals. To access of an article which published elsewhere, please select “Full Text” option. The original trackable via the “References”