Evidence map›Paper›PMID 34777564›Full record

ArticleComputational and mathematical methods in medicine2021

Pairwise Biological Network Alignment Based on Discrete Bat Algorithm.

Jing Chen, Ying Zhang, Jin-Fang Xia

Abstract read
In one paragraph

Article in Computational and mathematical methods in medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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4 · The record

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5 · Who and what money

Authors and funding

3 authors.

Jing ChenSchool of Artificial Intelligence and Computer Science, Jiangnan University, Wuxi, Jiangsu 214122, China.ORCID https://orcid.org/0000-0001-7549-7339
Ying ZhangSchool of Artificial Intelligence and Computer Science, Jiangnan University, Wuxi, Jiangsu 214122, China.ORCID https://orcid.org/0000-0003-1662-4590
Jin-Fang XiaSchool of Artificial Intelligence and Computer Science, Jiangnan University, Wuxi, Jiangsu 214122, China.ORCID https://orcid.org/0000-0001-9737-0961

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The development of high-throughput technology has provided a reliable technical guarantee for an increased amount of available data on biological networks. Network alignment is used to analyze these data to identify conserved functional network modules and understand evolutionary relationships across species. Thus, an efficient computational network aligner is needed for network alignment. In this paper, the classic bat algorithm is discretized and applied to the network alignment. The bat algorithm initializes the population randomly and then searches for the optimal solution iteratively. Based on the bat algorithm, the global pairwise alignment algorithm BatAlign is proposed. In BatAlign, the individual velocity and the position are represented by a discrete code. BatAlign uses a search algorithm based on objective function that uses the number of conserved edges as the objective function. The similarity between the networks is used to initialize the population. The experimental results showed that the algorithm was able to match proteins with high functional consistency and reach a relatively high topological quality.

Indexed as

AlgorithmsAnimalsChiropteraComputational BiologyComputer SimulationDatabases, GeneticEcholocationGene OntologyGene Regulatory NetworksHumansMetabolic Networks and PathwaysProtein Interaction MapsSequence AlignmentSynthetic Biology

Identifiers

PMID34777564
PMCPMC8580637

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.