Behcet Melih SaribatirKayhan ErciyeşErciyes, KayhanSaribatir, Behcet MelihA. Varol , M. Karabatak , C. Varol2025-10-062022978166545995210.1109/IISEC56263.2022.99982452-s2.0-85146366627https://www.scopus.com/inward/record.uri?eid=2-s2.0-85146366627&doi=10.1109%2FIISEC56263.2022.9998245&partnerID=40&md5=ee7c726d1fd8a7d209e8f485793d0868https://gcris.yasar.edu.tr/handle/123456789/8767https://doi.org/10.1109/IISEC56263.2022.9998245We propose a new parallel algorithm based on a distributed matching algorithm for the network alignment problem which can be used to find similarities in biological networks. This information may be used to form phylogenetic trees and consequently understand the evolution process better. We provide preliminary implementation results in sample networks which provide significant speedups with respect to sequential algorithms. © 2023 Elsevier B.V. All rights reserved.Englishinfo:eu-repo/semantics/closedAccessAlgorithm, Biological Network, Evolution, Network Alignment, Parallel, Alignment, Alignment Algorithms, Alignment Problems, Biological Networks, Evolution, Evolution Process, Matching Algorithm, Network Alignments, Parallel, Parallel Network, Phylogenetic Trees, BioinformaticsAlignment, Alignment algorithms, Alignment Problems, Biological networks, Evolution, Evolution process, Matching algorithm, Network alignments, Parallel, Parallel network, Phylogenetic trees, BioinformaticsBiological NetworkEvolutionParallelAlgorithmNetwork AlignmentConference Object