Publicação
Prediction of Health of Corals Mussismilia hispida Based on the Microorganisms Present in their Microbiome
| 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 |
| _version_ | 1867172680408498176 |
|---|---|
| author | Barque, Barry Malick |
| author2 | Rodrigues, Pedro João Paula Filho, Pedro Luiz de Peixoto, Raquel Silva Leite, Deborah Catharine de Assis |
| author2_role | author author author author |
| author_facet | Barque, Barry Malick Rodrigues, Pedro João Paula Filho, Pedro Luiz de Peixoto, Raquel Silva Leite, Deborah Catharine de Assis |
| author_role | author |
| contributor_name_str_mv | Biblioteca Digital do IPB |
| country_str | PT |
| creators_json_txt | [{\"Person.name\":\"Barque, Barry Malick\"},{\"Person.name\":\"Rodrigues, Pedro João\",\"Person.identifier.orcid\":\"0000-0002-0555-2029\"},{\"Person.name\":\"Paula Filho, Pedro Luiz de\"},{\"Person.name\":\"Peixoto, Raquel Silva\"},{\"Person.name\":\"Leite, Deborah Catharine de Assis\"}] |
| datacite.contributors.contributor.contributorName.fl_str_mv | Biblioteca Digital do IPB |
| datacite.creators.creator.creatorName.fl_str_mv | Barque, Barry Malick Rodrigues, Pedro João Paula Filho, Pedro Luiz de Peixoto, Raquel Silva Leite, Deborah Catharine de Assis |
| datacite.date.Accepted.fl_str_mv | 2024-01-01T00:00:00Z |
| datacite.date.available.fl_str_mv | 2024-10-09T08:53:43Z |
| datacite.date.embargoed.fl_str_mv | 2024-10-09T08:53:43Z |
| datacite.rights.fl_str_mv | http://purl.org/coar/access_right/c_16ec |
| datacite.subjects.subject.fl_str_mv | Coral reef Microbiome Machine learning algorithm |
| datacite.titles.title.fl_str_mv | Prediction of Health of Corals Mussismilia hispida Based on the Microorganisms Present in their Microbiome |
| dc.contributor.none.fl_str_mv | Biblioteca Digital do IPB |
| dc.creator.none.fl_str_mv | Barque, Barry Malick Rodrigues, Pedro João Paula Filho, Pedro Luiz de Peixoto, Raquel Silva Leite, Deborah Catharine de Assis |
| dc.date.Accepted.fl_str_mv | 2024-01-01T00:00:00Z |
| dc.date.available.fl_str_mv | 2024-10-09T08:53:43Z |
| dc.date.embargoed.fl_str_mv | 2024-10-09T08:53:43Z |
| dc.format.none.fl_str_mv | application/pdf |
| dc.identifier.none.fl_str_mv | http://hdl.handle.net/10198/30390 |
| dc.language.none.fl_str_mv | eng |
| dc.publisher.none.fl_str_mv | Springer Nature |
| dc.rights.cclincense.fl_str_mv | http://creativecommons.org/licenses/by/4.0/ |
| dc.rights.none.fl_str_mv | http://purl.org/coar/access_right/c_16ec |
| dc.subject.none.fl_str_mv | Coral reef Microbiome Machine learning algorithm |
| dc.title.fl_str_mv | Prediction of Health of Corals Mussismilia hispida Based on the Microorganisms Present in their Microbiome |
| dc.type.none.fl_str_mv | http://purl.org/coar/resource_type/c_5794 |
| description | 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. |
| dirty | 0 |
| eu_rights_str_mv | restrictedAccess |
| format | conferencePaper |
| fulltext.url.fl_str_mv | https://bibliotecadigital.ipb.pt/bitstreams/b699f061-f31e-4010-9708-c2440f853b69/download |
| id | ipb_cda9f10fcd1368cdb10fcd118c845ce0 |
| identifier.url.fl_str_mv | http://hdl.handle.net/10198/30390 |
| instacron_str | ipb |
| institution | Instituto Politécnico de Bragança |
| instname_str | Instituto Politécnico de Bragança |
| language | eng |
| network_acronym_str | ipb |
| network_name_str | Biblioteca Digital do IPB |
| oai_identifier_str | oai:bibliotecadigital.ipb.pt:10198/30390 |
| organization_str_mv | urn:organizationAcronym:ipb |
| person_str_mv | Barque, Barry Malick Rodrigues, Pedro João Rodrigues, Pedro João https://www.ciencia-id.pt/1316-21BB-9015 1316-21BB-9015 http://orcid.org/0000-0002-0555-2029 0000-0002-0555-2029 Paula Filho, Pedro Luiz de Peixoto, Raquel Silva Leite, Deborah Catharine de Assis |
| publishDate | 2024 |
| publisher.none.fl_str_mv | Springer Nature |
| reponame_str | Biblioteca Digital do IPB |
| repository_id_str | urn:repositoryAcronym:ipb |
| service_str_mv | urn:repositoryAcronym:ipb |
| spelling | engSpringer Naturept_PTOne 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.application/pdfpt_PTPrediction of Health of Corals Mussismilia hispida Based on the Microorganisms Present in their MicrobiomeBarque, Barry MalickPersonalRodrigues, Pedro JoãoDSpacehttp://dspace.org/items/6c5911a6-b62b-4876-9def-60096b52383aDSpacehttp://dspace.org/items/6c5911a6-b62b-4876-9def-60096b52383aRodriguesPedro JoãoCiência IDhttps://www.ciencia-id.pt1316-21BB-9015ORCIDhttp://orcid.org0000-0002-0555-2029Paula Filho, Pedro Luiz dePeixoto, Raquel SilvaLeite, Deborah Catharine de AssisHostingInstitutionOrganizationalBiblioteca Digital do IPBe-mailmailto:dspace@ipb.ptdspace@ipb.ptISBNIsPartOf978-3-031-53024-1ISBNIsPartOf978-3-031-53025-8DOIIsPartOf10.1007/978-3-031-53025-8_282024-10-09T08:53:43Z20242024-01-01T00:00:00ZHandlehttp://hdl.handle.net/10198/30390http://purl.org/coar/access_right/c_16ecrestricted accessCoral reefMicrobiomeMachine learning algorithm4177650 bytesother research producthttp://purl.org/coar/resource_type/c_5794conference paper2024http://creativecommons.org/licenses/by/4.0/http://purl.org/coar/access_right/c_16ecapplication/pdffulltexthttps://bibliotecadigital.ipb.pt/bitstreams/b699f061-f31e-4010-9708-c2440f853b69/download3rd International Conference on Optimization, Learning Algorithms and Applications (OL2A 2023)409423 |
| spellingShingle | Prediction of Health of Corals Mussismilia hispida Based on the Microorganisms Present in their Microbiome Barque, Barry Malick Coral reef Microbiome Machine learning algorithm |
| status | SINGLETON |
| subject.fl_str_mv | Coral reef Microbiome Machine learning algorithm |
| title | Prediction of Health of Corals Mussismilia hispida Based on the Microorganisms Present in their Microbiome |
| title_full | Prediction of Health of Corals Mussismilia hispida Based on the Microorganisms Present in their Microbiome |
| title_fullStr | Prediction of Health of Corals Mussismilia hispida Based on the Microorganisms Present in their Microbiome |
| title_full_unstemmed | Prediction of Health of Corals Mussismilia hispida Based on the Microorganisms Present in their Microbiome |
| title_short | Prediction of Health of Corals Mussismilia hispida Based on the Microorganisms Present in their Microbiome |
| title_sort | Prediction of Health of Corals Mussismilia hispida Based on the Microorganisms Present in their Microbiome |
| topic | Coral reef Microbiome Machine learning algorithm |
| topic_facet | Coral reef Microbiome Machine learning algorithm |
| url | http://hdl.handle.net/10198/30390 |
| visible | 1 |