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Advisor(s)
Abstract(s)
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.
Description
Keywords
Coral reef Microbiome Machine learning algorithm
Citation
Barque, Barry Malick; Rodrigues, Pedro João Soares; Paula Filho, Pedro Luiz de; Peixoto, Raquel Silva; Leite, Deborah Catharine de Assis (2024). Prediction of Health of Corals Mussismilia hispida Based on the Microorganisms Present in their Microbiome. In 3rd International Conference on Optimization, Learning Algorithms and Applications (OL2A 2023). Cham: Springer Nature, Vol. 1, p. 409–423. ISBN 978-3-031-53024-1
Publisher
Springer Nature