reference/2002935

http://rdf.ncbi.nlm.nih.gov/pubchem/reference/2002935

Outgoing Links

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contentType	Journal Article\|Research Support, Non-U.S. Gov't
issn	2218-273X
issueIdentifier	6
pageRange	872-
publicationName	Biomolecules
startingPage	872
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bibliographicCitation	Wang H, Zhao H, Yan Z, Zhao J, Han J. MDCAN-Lys: A Model for Predicting Succinylation Sites Based on Multilane Dense Convolutional Attention Network. Biomolecules. 2021 Jun 11;11(6). PMID: 34208298; PMCID: PMC8231176.
creator	http://rdf.ncbi.nlm.nih.gov/pubchem/author/MD5_c53d8b9306de5f9c5f495c677ddb9b4a http://rdf.ncbi.nlm.nih.gov/pubchem/author/ORCID_0000-0002-1092-6443 http://rdf.ncbi.nlm.nih.gov/pubchem/author/MD5_d354a9f4cf01c7e1abfb08333d727ae7 http://rdf.ncbi.nlm.nih.gov/pubchem/author/ORCID_0000-0003-1757-3609 http://rdf.ncbi.nlm.nih.gov/pubchem/author/MD5_b4ed3ea00b80738aca8281766dea41dd
date	2021-06-11^^<http://www.w3.org/2001/XMLSchema#date>
identifier	https://pubmed.ncbi.nlm.nih.gov/34208298 https://pubmed.ncbi.nlm.nih.gov/PMC8231176 https://doi.org/10.3390/biom11060872
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language	English
source	https://www.crossref.org/ https://pubmed.ncbi.nlm.nih.gov/
title	MDCAN-Lys: A Model for Predicting Succinylation Sites Based on Multilane Dense Convolutional Attention Network
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