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Prediction of Health of Corals Mussismilia hispida Based on the Microorganisms Present in their Microbiome

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Detalhes bibliográficos
Resumo:One of the most diverse and productive marine ecosystems in the world are the corals, providing not only tourism but also an important economic contribution to the countries that have them on their coasts. Thanks to genome sequencing techniques, it is possible to identify the microorganisms that form the coral microbiome. The generation of large amounts of data, thanks to the low cost of sequencing since 2005, provides an opening for the use of artificial neural networks for the advancement of sciences such as biology and medicine. This work aims to predict the healthy microbiome present in samples of Mussismilia hispida coral, using machine learning algorithms, in which the algorithms SVM, Decision Tree, and Random Forest achieved a rate of 61%, 74%, and 72%, respectively. Additionally, it aims to identify possible microorganisms related to the disease in question in corals.
Autores principais:Barque, Barry Malick
Outros Autores:Rodrigues, Pedro João; Paula Filho, Pedro Luiz de; Peixoto, Raquel Silva; Leite, Deborah Catharine de Assis
Assunto:Coral reef Microbiome Machine learning algorithm
Ano:2024
País:Portugal
Tipo de documento:comunicação em conferência
Tipo de acesso:acesso restrito
Instituição associada:Instituto Politécnico de Bragança
Idioma:inglês
Origem:Biblioteca Digital do IPB

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