reference/6131810

http://rdf.ncbi.nlm.nih.gov/pubchem/reference/6131810

Outgoing Links

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contentType	Journal Article\|Research Support, Non-U.S. Gov't
endingPage	662
issn	1367-4811 1367-4803
issueIdentifier	3
pageRange	655-662
publicationName	Bioinformatics (Oxford, England)
startingPage	655
hasFundingAgency	http://rdf.ncbi.nlm.nih.gov/pubchem/organization/MD5_b6ba7b45d4175c9be91d883514bc4509 http://rdf.ncbi.nlm.nih.gov/pubchem/organization/MD5_487baf6554eb36bb22c6138d90a7c50f http://rdf.ncbi.nlm.nih.gov/pubchem/organization/MD5_1c0aa062611518a12552a116a65f748d http://rdf.ncbi.nlm.nih.gov/pubchem/organization/MD5_ef9cfa541454b186bc61664fdae00f1d http://rdf.ncbi.nlm.nih.gov/pubchem/organization/MD5_0c21611b8eb598b5073a8282586e13be http://rdf.ncbi.nlm.nih.gov/pubchem/organization/MD5_c0faacb6354ced772865ea66aea4bc1a http://rdf.ncbi.nlm.nih.gov/pubchem/organization/MD5_6655586123c3d14198009b14c4ffc578 http://rdf.ncbi.nlm.nih.gov/pubchem/organization/MD5_11386d84d73baefb90cb05a392e4d2c2
bibliographicCitation	Zhao Q, Zhao H, Zheng K, Wang J. HyperAttentionDTI: improving drug-protein interaction prediction by sequence-based deep learning with attention mechanism. Bioinformatics. 2022 Jan 12;38(3):655–62. doi: 10.1093/bioinformatics/btab715. PMID: 34664614.
creator	http://rdf.ncbi.nlm.nih.gov/pubchem/author/MD5_93d85386c5a085c7aaca02a519b9e619 http://rdf.ncbi.nlm.nih.gov/pubchem/author/ORCID_0000-0003-1516-0480 http://rdf.ncbi.nlm.nih.gov/pubchem/author/MD5_24dcc92d4458b4bb2c15347f4a956c31 http://rdf.ncbi.nlm.nih.gov/pubchem/author/ORCID_0000-0002-8319-9793
date	2021-10-19^^<http://www.w3.org/2001/XMLSchema#date>
identifier	https://pubmed.ncbi.nlm.nih.gov/34664614 https://doi.org/10.1093/bioinformatics/btab715
isPartOf	https://portal.issn.org/resource/ISSN/1367-4803 https://portal.issn.org/resource/ISSN/1367-4811 http://rdf.ncbi.nlm.nih.gov/pubchem/journal/20940
language	English
source	https://pubmed.ncbi.nlm.nih.gov/ https://www.crossref.org/
title	HyperAttentionDTI: improving drug–protein interaction prediction by sequence-based deep learning with attention mechanism
discusses	http://id.nlm.nih.gov/mesh/M0000922 http://id.nlm.nih.gov/mesh/M0017890
hasPrimarySubjectTerm	http://id.nlm.nih.gov/mesh/D000077321
hasSubjectTerm	http://id.nlm.nih.gov/mesh/D016571 http://id.nlm.nih.gov/mesh/D011506Q000737 http://id.nlm.nih.gov/mesh/D006801 http://id.nlm.nih.gov/mesh/D000596 http://id.nlm.nih.gov/mesh/D055808Q000379

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