About: DLPAlign: A Deep Learning based Progressive Alignment for Multiple Protein Sequences

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An Entity of Type : schema:ScholarlyArticle, within Data Space : covidontheweb.inria.fr associated with source document(s)

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type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
title	DLPAlign: A Deep Learning based Progressive Alignment for Multiple Protein Sequences
Creator	Kuang, Mengmeng
source	BioRxiv
abstract	This paper proposed a novel and straightforward approach to improve the accuracy of progressive multiple protein sequence alignment. We trained a decision-making model based on the convolutional neural networks and bi-directional long short term memory networks, and based on this model, we progressively aligned the input sequences by calculating different posterior probability matrixes. To test the accuracy of this approach, we have implemented a multiple sequence alignment tool called DLPAlign and compared its performance with eleven leading alignment methods on three empirical alignment benchmarks (BAliBASE, OXBench and SABMark). Our results show that DLPAlign can get the best total-column scores on the three benchmarks. When evaluated against the 711 low similarity families with average PID ≤ 30%, DLPAlign improved about 2.8% over the second-best MSA software. Besides, we also compared the performance of DLPAlign and other alignment tools on a real-life application, namely protein secondary structure prediction on four protein sequences related to SARS-COV-2, and DLPAlign provides the best result in all cases.
has issue date	2020-07-17(xsd:dateTime)
bibo:doi	10.1101/2020.07.16.207951
has license	biorxiv
sha1sum (hex)	be69c9781f14d5d030629cc9a214d938d2e0c410
schema:url	https://doi.org/10.1101/2020.07.16.207951
resource representing a document's title	DLPAlign: A Deep Learning based Progressive Alignment for Multiple Protein Sequences
schema:publication	bioRxiv
resource representing a document's body	covid:be69c9781f14d5d030629cc9a214d938d2e0c410#body_text
is schema:about of	named entity 'based' named entity 'multiple' named entity 'Deep Learning' named entity 'XXX' named entity 'SHORT TERM MEMORY' »more»

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