BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

142 related articles for article (PubMed ID: 30576487)

  • 1. Potent pairing: ensemble of long short-term memory networks and support vector machine for chemical-protein relation extraction.
    Mehryary F; Björne J; Salakoski T; Ginter F
    Database (Oxford); 2018 Jan; 2018():. PubMed ID: 30576487
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Extracting chemical-protein relations with ensembles of SVM and deep learning models.
    Peng Y; Rios A; Kavuluru R; Lu Z
    Database (Oxford); 2018 Jan; 2018():. PubMed ID: 30020437
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Chemical-gene relation extraction using recursive neural network.
    Lim S; Kang J
    Database (Oxford); 2018 Jan; 2018():. PubMed ID: 29961818
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Extraction of chemical-protein interactions from the literature using neural networks and narrow instance representation.
    Antunes R; Matos S
    Database (Oxford); 2019 Jan; 2019():. PubMed ID: 31622463
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Overview of the BioCreative VI Precision Medicine Track: mining protein interactions and mutations for precision medicine.
    Islamaj Dogan R; Kim S; Chatr-Aryamontri A; Wei CH; Comeau DC; Antunes R; Matos S; Chen Q; Elangovan A; Panyam NC; Verspoor K; Liu H; Wang Y; Liu Z; Altinel B; Hüsünbeyi ZM; Özgür A; Fergadis A; Wang CK; Dai HJ; Tran T; Kavuluru R; Luo L; Steppi A; Zhang J; Qu J; Lu Z
    Database (Oxford); 2019 Jan; 2019():. PubMed ID: 30689846
    [TBL] [Abstract][Full Text] [Related]  

  • 6. BO-LSTM: classifying relations via long short-term memory networks along biomedical ontologies.
    Lamurias A; Sousa D; Clarke LA; Couto FM
    BMC Bioinformatics; 2019 Jan; 20(1):10. PubMed ID: 30616557
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Improving the learning of chemical-protein interactions from literature using transfer learning and specialized word embeddings.
    Corbett P; Boyle J
    Database (Oxford); 2018 Jan; 2018():. PubMed ID: 30010749
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Extracting chemical-protein interactions from literature using sentence structure analysis and feature engineering.
    Lung PY; He Z; Zhao T; Yu D; Zhang J
    Database (Oxford); 2019 Jan; 2019():. PubMed ID: 30624652
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Extracting chemical-protein interactions from biomedical literature via granular attention based recurrent neural networks.
    Lu H; Li L; He X; Liu Y; Zhou A
    Comput Methods Programs Biomed; 2019 Jul; 176():61-68. PubMed ID: 31200912
    [TBL] [Abstract][Full Text] [Related]  

  • 10. LPTK: a linguistic pattern-aware dependency tree kernel approach for the BioCreative VI CHEMPROT task.
    Warikoo N; Chang YC; Hsu WL
    Database (Oxford); 2018 Jan; 2018():. PubMed ID: 30346607
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Assessing the state of the art in biomedical relation extraction: overview of the BioCreative V chemical-disease relation (CDR) task.
    Wei CH; Peng Y; Leaman R; Davis AP; Mattingly CJ; Li J; Wiegers TC; Lu Z
    Database (Oxford); 2016; 2016():. PubMed ID: 26994911
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Extracting chemical-protein relations using attention-based neural networks.
    Liu S; Shen F; Komandur Elayavilli R; Wang Y; Rastegar-Mojarad M; Chaudhary V; Liu H
    Database (Oxford); 2018 Jan; 2018():. PubMed ID: 30295724
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Effectively Identifying Compound-Protein Interactions by Learning from Positive and Unlabeled Examples.
    Cheng Z; Zhou S; Wang Y; Liu H; Guan J; Chen YP
    IEEE/ACM Trans Comput Biol Bioinform; 2018; 15(6):1832-1843. PubMed ID: 28113437
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Chemical named entity recognition in patents by domain knowledge and unsupervised feature learning.
    Zhang Y; Xu J; Chen H; Wang J; Wu Y; Prakasam M; Xu H
    Database (Oxford); 2016; 2016():. PubMed ID: 27087307
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Artificial intelligence to deep learning: machine intelligence approach for drug discovery.
    Gupta R; Srivastava D; Sahu M; Tiwari S; Ambasta RK; Kumar P
    Mol Divers; 2021 Aug; 25(3):1315-1360. PubMed ID: 33844136
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Clinical Relation Extraction Toward Drug Safety Surveillance Using Electronic Health Record Narratives: Classical Learning Versus Deep Learning.
    Munkhdalai T; Liu F; Yu H
    JMIR Public Health Surveill; 2018 Apr; 4(2):e29. PubMed ID: 29695376
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Chemical-protein interaction extraction via contextualized word representations and multihead attention.
    Zhang Y; Lin H; Yang Z; Wang J; Sun Y
    Database (Oxford); 2019 Jan; 2019():. PubMed ID: 31125403
    [TBL] [Abstract][Full Text] [Related]  

  • 18. A hybrid model based on neural networks for biomedical relation extraction.
    Zhang Y; Lin H; Yang Z; Wang J; Zhang S; Sun Y; Yang L
    J Biomed Inform; 2018 May; 81():83-92. PubMed ID: 29601989
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Biomedical named entity recognition using deep neural networks with contextual information.
    Cho H; Lee H
    BMC Bioinformatics; 2019 Dec; 20(1):735. PubMed ID: 31881938
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Multichannel Convolutional Neural Network for Biological Relation Extraction.
    Quan C; Hua L; Sun X; Bai W
    Biomed Res Int; 2016; 2016():1850404. PubMed ID: 28053977
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 8.