Powered by OpenAIRE graph
Found an issue? Give us feedback
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ arXiv.org e-Print Ar...arrow_drop_down
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
arXiv.org e-Print Archive
Other literature type . Preprint . 2021
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
https://doi.org/10.48550/arxiv...
Article . 2021
License: CC BY NC SA
Data sources: Datacite
versions View all 5 versions
addClaim

This Research product is the result of merged Research products in OpenAIRE.

You have already added 0 works in your ORCID record related to the merged Research product.

R-BERT-CNN: Drug-target interactions extraction from biomedical literature

Authors: Aldahdooh, Jehad; Tanoli, Ziaurrehman; Tang, Jing;

R-BERT-CNN: Drug-target interactions extraction from biomedical literature

Abstract

In this research, we present our work participation for the DrugProt task of BioCreative VII challenge. Drug-target interactions (DTIs) are critical for drug discovery and repurposing, which are often manually extracted from the experimental articles. There are >32M biomedical articles on PubMed and manually extracting DTIs from such a huge knowledge base is challenging. To solve this issue, we provide a solution for Track 1, which aims to extract 10 types of interactions between drug and protein entities. We applied an Ensemble Classifier model that combines BioMed-RoBERTa, a state of art language model, with Convolutional Neural Networks (CNN) to extract these relations. Despite the class imbalances in the BioCreative VII DrugProt test corpus, our model achieves a good performance compared to the average of other submissions in the challenge, with the micro F1 score of 55.67% (and 63% on BioCreative VI ChemProt test corpus). The results show the potential of deep learning in extracting various types of DTIs.

Peer reviewed

Country
Finland
Related Organizations
Keywords

FOS: Computer and information sciences, Computer Science - Computation and Language, Computer Science - Artificial Intelligence, Drug discovery, relation extraction, text mining, Drug-target interaction, Computer Science - Information Retrieval, Artificial Intelligence (cs.AI), 3111 Biomedicine, Computation and Language (cs.CL), Information Retrieval (cs.IR)

29 references, page 1 of 3

1. Nogrady,B. (2020) How cancer genomics is transforming diagnosis and treatment. Nature., 579(7800), S10-S11.

2. Oprea,T.I., Bologa,C.G., Brunak,S., Campbell,A., Gan,G.N., Gaulton,A., Gomez,S.M., Guha,R., Hersey,A., Holmes,J., et al. (2018) Unexplored therapeutic opportunities in the human genome. Nat Rev Drug Discov. 17, 317-332.

Lin,A., Giuliano,C.J., Palladino,A., John,K.M., Abramowicz,C., Yuan,M.L., Sausville,E.L., Lukow,D.A., Luwei,L., Chait,A.R., Galluzzo.,Z.C., Tucker, C., Sheltzer,J.M. (2019) Off-target toxicity is a common mechanism-of-action of cancer drugs undergoing clinical trials. Sci Transl Med. 11(509), eaaw8412.

Mendez,D., Gaulton,A., Bento,A.P., Chambers,J., De Veij,M., Felix,E., et al. (2019) ChEMBL: towards direct deposition of bioassay data. Nucleic Acids Res. 47, D930-D940.

Gilson,M.K., Liu,T., Baitaluk,M., Nicola,G., Hwang,L., and Chong,J. (2016) BindingDB in 2015: A public database for medicinal chemistry, computational chemistry and systems pharmacology. Nucleic Acids Res. 2016;44:D1045-D1053. [OpenAIRE]

Wang,Y., Bryant,S.H., Cheng,T., et al. (2017) PubChem BioAssay: 2017 update. Nucleic Acids Res., 45, D955-D963.

Wishart,D.S., Knox,C., Guo,A.C., et al. (2006) DrugBank: a comprehensive resource for in silico drug discovery and exploration. Nucleic Acids Res., 34, D668-D672.

Ursu, O., Holmes,J., Bologa,C.G., Yang,J.J., Mathias,S.L., Stathias,V., Nguyen,D.T., Schürer,S., and Oprea,T. (2019) DrugCentral 2018: An update. Nucleic Acids Res., 47, D963- D970. [OpenAIRE]

Alexander,S.P.H., Fabbro,D., Kelly,E., Marrion,N.V., Peters,J.A., Faccenda,E., et al. (2017) The Concise Guide to PHARMACOLOGY 2017/18: Overview. Br J Pharmacol., 174 (Suppl. 1), S272-S359. [OpenAIRE]

Wagner,A.H., Coffman,A.C., Ainscough,B.J., Spies,N.C., Skidmore,Z.L., Campbell,K.M., et al. (2016) DGIdb 2.0: mining clinically relevant drug-gene interactions. Nucleic Acids Res., 44, D1036-D1044.

  • BIP!
    Impact byBIP!
    citations
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    0
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Average
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Average
  • citations
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    0
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Average
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Average
    Powered byBIP!BIP!
Powered by OpenAIRE graph
Found an issue? Give us feedback
citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green