Abstract:
:Identification of new drug-target interactions (DTIs) is an important but a time-consuming and costly step in drug discovery. In recent years, to mitigate these drawbacks, researchers have sought to identify DTIs using computational approaches. However, most existing methods construct drug networks and target networks separately, and then predict novel DTIs based on known associations between the drugs and targets without accounting for associations between drug-protein pairs (DPPs). To incorporate the associations between DPPs into DTI modeling, we built a DPP network based on multiple drugs and proteins in which DPPs are the nodes and the associations between DPPs are the edges of the network. We then propose a novel learning-based framework, 'graph convolutional network (GCN)-DTI', for DTI identification. The model first uses a graph convolutional network to learn the features for each DPP. Second, using the feature representation as an input, it uses a deep neural network to predict the final label. The results of our analysis show that the proposed framework outperforms some state-of-the-art approaches by a large margin.
journal_name
Brief Bioinformjournal_title
Briefings in bioinformaticsauthors
Zhao T,Hu Y,Valsdottir LR,Zang T,Peng Jdoi
10.1093/bib/bbaa044subject
Has Abstractpub_date
2020-05-04 00:00:00eissn
1467-5463issn
1477-4054pii
5828123pub_type
杂志文章abstract::Prognostic tests using expression profiles of several dozen genes help provide treatment choices for prostate cancer (PCa). However, these tests require improvement to meet the clinical need for resolving overtreatment, which continues to be a pervasive problem in PCa management. Genomic selection (GS) methodology, wh...
journal_title:Briefings in bioinformatics
pub_type: 杂志文章
doi:10.1093/bib/bbaa197
更新日期:2020-09-08 00:00:00
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journal_title:Briefings in bioinformatics
pub_type: 杂志文章,评审
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journal_title:Briefings in bioinformatics
pub_type: 杂志文章,评审
doi:10.1093/bib/bbx010
更新日期:2018-09-28 00:00:00
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journal_title:Briefings in bioinformatics
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journal_title:Briefings in bioinformatics
pub_type: 杂志文章,评审
doi:10.1093/bib/4.1.7
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journal_title:Briefings in bioinformatics
pub_type: 杂志文章,评审
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pub_type: 杂志文章
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pub_type: 杂志文章,评审
doi:10.1093/bib/bbw108
更新日期:2018-03-01 00:00:00
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journal_title:Briefings in bioinformatics
pub_type: 杂志文章
doi:10.1093/bib/bbz113
更新日期:2020-12-01 00:00:00
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journal_title:Briefings in bioinformatics
pub_type: 杂志文章,评审
doi:10.1093/bib/bby028
更新日期:2019-03-25 00:00:00
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pub_type: 杂志文章
doi:10.1093/bib/bbt075
更新日期:2015-01-01 00:00:00
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pub_type: 杂志文章
doi:10.1093/bib/bbs074
更新日期:2014-07-01 00:00:00
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journal_title:Briefings in bioinformatics
pub_type: 杂志文章
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更新日期:2014-01-01 00:00:00
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journal_title:Briefings in bioinformatics
pub_type: 杂志文章
doi:10.1093/bib/1.3.297
更新日期:2000-09-01 00:00:00
abstract::As one of the most important fundamental problems in protein sequence analysis, protein remote homology detection is critical for both theoretical research (protein structure and function studies) and real world applications (drug design). Although several computational predictors have been proposed, their detection p...
journal_title:Briefings in bioinformatics
pub_type: 杂志文章
doi:10.1093/bib/bby104
更新日期:2018-11-07 00:00:00
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pub_type: 杂志文章
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更新日期:2021-01-06 00:00:00
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pub_type: 杂志文章
doi:10.1093/bib/bbv064
更新日期:2016-03-01 00:00:00
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journal_title:Briefings in bioinformatics
pub_type: 杂志文章
doi:10.1093/bib/bbaa109
更新日期:2020-06-10 00:00:00
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pub_type: 杂志文章
doi:10.1093/bib/bbaa429
更新日期:2021-01-30 00:00:00
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journal_title:Briefings in bioinformatics
pub_type: 杂志文章
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更新日期:2016-09-01 00:00:00
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journal_title:Briefings in bioinformatics
pub_type: 杂志文章
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更新日期:2020-07-01 00:00:00
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更新日期:2014-01-01 00:00:00
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pub_type: 杂志文章
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journal_title:Briefings in bioinformatics
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pub_type: 杂志文章
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