Published November 8, 2024 | Version v1
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GA2Vec: Optimizing Global Network Alignment with a Genetic Algorithm

  • 1. ROR icon Tunis El Manar University
  • 2. ROR icon Université Bordeaux-I

Description

GA2Vec is a novel method for the global alignment of multiple PPI networks in a many-to-many framework, utilizing genetic algorithms. It reconstructs weighted PPI networks by incorporating protein sequence embeddings from ProtBERT, ESM-2, and ProtT5-XL-UniRef50 and functional similarity from Gene Ontology (GO) embeddings via Anc2vec. To generate candidate clusters as initial alignment solutions, GA2Vec applies four community detection algorithms on the weighted graph. The genetic algorithm then iteratively refines these clusters, optimizing network alignment through a fitness function that combines similarity scores from both sequence embeddings and GO terms, achieving robust global alignment across PPI networks.

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Additional details

Related works

Is derived from
Software: 10.5281/zenodo.10701120 (DOI)

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