iGENE: Application for filamentous and yeast genomic identification
Autor(a) principal: | |
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Data de Publicação: | 2022 |
Outros Autores: | , , , , , , , , |
Tipo de documento: | Artigo |
Idioma: | por |
Título da fonte: | Research, Society and Development |
Texto Completo: | https://rsdjournal.org/index.php/rsd/article/view/25103 |
Resumo: | Innovations in genomic and proteomic methodologies for identification of microrganisms associated with digital technologies are in alignment with Industry 4.0 vision and are increasing. The objective of this work was to develop a prototype of an application (App) for the identification of filamentous fungi and yeasts at the species level. The construction of the prototype was carried out in order to present a web application with a responsive interface. The App was developed using a cloud computing process with a cascade model. As part of the App’s requirements, a Cloud Firestore database was built with image processing through a skImage library. For this purpose, agarose gels with filamentous fungi and yeasts restriction profiles previously identified at the species level by genomic (PCR/RFLP) and proteomic (mass spectrometry) methodologies were selected. The App identified as iGENE was able to perform the recognition of restriction profiles of agarose gels, comparing it to the filamentous fungi and yeasts registered in its library. The result at the species level was possible for profiles with more than 90% similarity. Although the analyzed images presented this profile, the App was built in order to also consider identifications at the genus level for similarities between 89 and 70%, as well as “unidentified microorganism” below this score. The inclusion of new filamentous fungi and yeasts species in the App library will allow for greater robustness in the generation of the identification result at the species level. |
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iGENE: Application for filamentous and yeast genomic identification iGENE: Aplicación para la identificación genómica de levaduras y filamentosasiGENE: Aplicativo para identificação genômica de fungos filamentosos e leveduras BiotecnologíaVisión por computadorProcesamiento de imágenesIdentificación de microorganismosPerfil de restricciónBiblioteca.BiotecnologiaVisão computacionalProcessamento de imagensIdentificação de microrganismosPerfil de restriçãoBiblioteca.BiotechnologyComputer visionImage processingIdentification of microorganismsLibrary.Innovations in genomic and proteomic methodologies for identification of microrganisms associated with digital technologies are in alignment with Industry 4.0 vision and are increasing. The objective of this work was to develop a prototype of an application (App) for the identification of filamentous fungi and yeasts at the species level. The construction of the prototype was carried out in order to present a web application with a responsive interface. The App was developed using a cloud computing process with a cascade model. As part of the App’s requirements, a Cloud Firestore database was built with image processing through a skImage library. For this purpose, agarose gels with filamentous fungi and yeasts restriction profiles previously identified at the species level by genomic (PCR/RFLP) and proteomic (mass spectrometry) methodologies were selected. The App identified as iGENE was able to perform the recognition of restriction profiles of agarose gels, comparing it to the filamentous fungi and yeasts registered in its library. The result at the species level was possible for profiles with more than 90% similarity. Although the analyzed images presented this profile, the App was built in order to also consider identifications at the genus level for similarities between 89 and 70%, as well as “unidentified microorganism” below this score. The inclusion of new filamentous fungi and yeasts species in the App library will allow for greater robustness in the generation of the identification result at the species level.Las innovaciones en las metodologías para la identificación de microorganismos genómicos y proteómicos asociados a las tecnologías digitales están en línea con la visión de la industria 4.0. El objetivo de este trabajo fue desarrollar un prototipo de aplicación (App) para la identificación de hongos filamentosos y levaduras a nivel de especie. La construcción del prototipo se realizó para presentar una aplicación web con una interfaz receptiva. La aplicación fue desarrollada en cloud computing con un modelo en cascada. Como parte de los requisitos de la aplicación, se creó una base de datos de Cloud Firestore con procesamiento de imágenes a través de una biblioteca skImage. Para ello, se seleccionaron geles de agarosa con perfiles de restricción de hongos filamentosos y levaduras previamente identificadas a nivel de especie mediante metodologías genómicas (PCR / RFLP) y proteómicas (espectrometría de masas). La aplicación identificada como iGENE pudo reconocer perfiles de restricción de geles de agarosa, comparándolo con hongos filamentosos y levaduras registrados en su biblioteca. El resultado a nivel de especie fue posible para perfiles con más del 90% de similitud. Si bien las imágenes analizadas presentaban este perfil, la App fue construida para considerar también identificaciones a nivel de género para similitudes entre 89 y 70%, así como “microorganismos no identificados” por debajo de esta puntuación. La inclusión de nuevas especies de hongos filamentosos y levaduras en la librería de la App permitirá una mayor robustez en la generación del resultado de identificación a nivel de especie.Inovações em metodologias para identificação de microrganismos genômicas e proteômicas associadas a tecnologias digitais estão em alinhamento com a visão de indústria 4.0 e estão em ascensão. O objetivo desse trabalho foi o desenvolvimento de um protótipo de um aplicativo (App) para a identificação de fungos filamentosos e leveduras ao nível de espécie. A construção do protótipo foi realizada de modo a apresentar uma aplicação web com interface responsiva. O App foi desenvolvido em processo cloud computing com modelo em cascata. Como parte dos requisitos do App foi construído um banco de dados Cloud Firestore com processamento de imagens através de uma biblioteca skImage. Para tal, foram selecionados géis de agarose com perfis de restrição de fungos filamentosos e leveduras previamente identificados ao nível de espécie por metodologias genômicas (PCR/RFLP) e proteômica (espectrometria de massa). O App identificado como iGENE foi capaz de realizar o reconhecimento de perfis de restrição de géis de agarose, comparando-o aos fungos filamentosos e leveduras cadastrados em sua biblioteca. O resultado ao nível de espécie foi possível para perfis com similaridade superior a 90%. Embora as imagens analisadas tenham apresentado esse perfil, o App foi construído de modo a considerar também identificações ao nível de gênero para similaridades entre 89 e 70%, bem como “microrganismo não identificado” abaixo desse escore. A inclusão de novas espécies de fungos filamentosos e leveduras na biblioteca do App permitirá uma maior robustez na geração do resultado da identificação ao nível de espécie.Research, Society and Development2022-01-21info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://rsdjournal.org/index.php/rsd/article/view/2510310.33448/rsd-v11i2.25103Research, Society and Development; Vol. 11 No. 2; e13011225103Research, Society and Development; Vol. 11 Núm. 2; e13011225103Research, Society and Development; v. 11 n. 2; e130112251032525-3409reponame:Research, Society and Developmentinstname:Universidade Federal de Itajubá (UNIFEI)instacron:UNIFEIporhttps://rsdjournal.org/index.php/rsd/article/view/25103/22384Copyright (c) 2022 Selena Dias Borborema Antunes; Heveraldo Rodrigues de Oliveira ; Marcos Flávio Silveira D'Angelis; Mauro Aparecido de Sousa Xavier; Fabiana Brandão Alves Silva; Dario Alves de Oliveira; Luciana Nobre Leite; Josiane dos Santos; Frederico Santos Barbosa; Alessandra Rejane Ericsson de Oliveira Xavierhttps://creativecommons.org/licenses/by/4.0info:eu-repo/semantics/openAccessAntunes, Selena Dias Borborema Rodrigues de Oliveira , HeveraldoD'Angelis, Marcos Flávio Silveira Xavier, Mauro Aparecido de Sousa Silva, Fabiana Brandão Alves Oliveira, Dario Alves de Leite, Luciana Nobre Santos, Josiane dos Barbosa, Frederico Santos Xavier, Alessandra Rejane Ericsson de Oliveira 2022-02-07T01:42:50Zoai:ojs.pkp.sfu.ca:article/25103Revistahttps://rsdjournal.org/index.php/rsd/indexPUBhttps://rsdjournal.org/index.php/rsd/oairsd.articles@gmail.com2525-34092525-3409opendoar:2024-01-17T09:43:28.158633Research, Society and Development - Universidade Federal de Itajubá (UNIFEI)false |
dc.title.none.fl_str_mv |
iGENE: Application for filamentous and yeast genomic identification iGENE: Aplicación para la identificación genómica de levaduras y filamentosas iGENE: Aplicativo para identificação genômica de fungos filamentosos e leveduras |
title |
iGENE: Application for filamentous and yeast genomic identification |
spellingShingle |
iGENE: Application for filamentous and yeast genomic identification Antunes, Selena Dias Borborema Biotecnología Visión por computador Procesamiento de imágenes Identificación de microorganismos Perfil de restricción Biblioteca. Biotecnologia Visão computacional Processamento de imagens Identificação de microrganismos Perfil de restrição Biblioteca. Biotechnology Computer vision Image processing Identification of microorganisms Library. |
title_short |
iGENE: Application for filamentous and yeast genomic identification |
title_full |
iGENE: Application for filamentous and yeast genomic identification |
title_fullStr |
iGENE: Application for filamentous and yeast genomic identification |
title_full_unstemmed |
iGENE: Application for filamentous and yeast genomic identification |
title_sort |
iGENE: Application for filamentous and yeast genomic identification |
author |
Antunes, Selena Dias Borborema |
author_facet |
Antunes, Selena Dias Borborema Rodrigues de Oliveira , Heveraldo D'Angelis, Marcos Flávio Silveira Xavier, Mauro Aparecido de Sousa Silva, Fabiana Brandão Alves Oliveira, Dario Alves de Leite, Luciana Nobre Santos, Josiane dos Barbosa, Frederico Santos Xavier, Alessandra Rejane Ericsson de Oliveira |
author_role |
author |
author2 |
Rodrigues de Oliveira , Heveraldo D'Angelis, Marcos Flávio Silveira Xavier, Mauro Aparecido de Sousa Silva, Fabiana Brandão Alves Oliveira, Dario Alves de Leite, Luciana Nobre Santos, Josiane dos Barbosa, Frederico Santos Xavier, Alessandra Rejane Ericsson de Oliveira |
author2_role |
author author author author author author author author author |
dc.contributor.author.fl_str_mv |
Antunes, Selena Dias Borborema Rodrigues de Oliveira , Heveraldo D'Angelis, Marcos Flávio Silveira Xavier, Mauro Aparecido de Sousa Silva, Fabiana Brandão Alves Oliveira, Dario Alves de Leite, Luciana Nobre Santos, Josiane dos Barbosa, Frederico Santos Xavier, Alessandra Rejane Ericsson de Oliveira |
dc.subject.por.fl_str_mv |
Biotecnología Visión por computador Procesamiento de imágenes Identificación de microorganismos Perfil de restricción Biblioteca. Biotecnologia Visão computacional Processamento de imagens Identificação de microrganismos Perfil de restrição Biblioteca. Biotechnology Computer vision Image processing Identification of microorganisms Library. |
topic |
Biotecnología Visión por computador Procesamiento de imágenes Identificación de microorganismos Perfil de restricción Biblioteca. Biotecnologia Visão computacional Processamento de imagens Identificação de microrganismos Perfil de restrição Biblioteca. Biotechnology Computer vision Image processing Identification of microorganisms Library. |
description |
Innovations in genomic and proteomic methodologies for identification of microrganisms associated with digital technologies are in alignment with Industry 4.0 vision and are increasing. The objective of this work was to develop a prototype of an application (App) for the identification of filamentous fungi and yeasts at the species level. The construction of the prototype was carried out in order to present a web application with a responsive interface. The App was developed using a cloud computing process with a cascade model. As part of the App’s requirements, a Cloud Firestore database was built with image processing through a skImage library. For this purpose, agarose gels with filamentous fungi and yeasts restriction profiles previously identified at the species level by genomic (PCR/RFLP) and proteomic (mass spectrometry) methodologies were selected. The App identified as iGENE was able to perform the recognition of restriction profiles of agarose gels, comparing it to the filamentous fungi and yeasts registered in its library. The result at the species level was possible for profiles with more than 90% similarity. Although the analyzed images presented this profile, the App was built in order to also consider identifications at the genus level for similarities between 89 and 70%, as well as “unidentified microorganism” below this score. The inclusion of new filamentous fungi and yeasts species in the App library will allow for greater robustness in the generation of the identification result at the species level. |
publishDate |
2022 |
dc.date.none.fl_str_mv |
2022-01-21 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
https://rsdjournal.org/index.php/rsd/article/view/25103 10.33448/rsd-v11i2.25103 |
url |
https://rsdjournal.org/index.php/rsd/article/view/25103 |
identifier_str_mv |
10.33448/rsd-v11i2.25103 |
dc.language.iso.fl_str_mv |
por |
language |
por |
dc.relation.none.fl_str_mv |
https://rsdjournal.org/index.php/rsd/article/view/25103/22384 |
dc.rights.driver.fl_str_mv |
https://creativecommons.org/licenses/by/4.0 info:eu-repo/semantics/openAccess |
rights_invalid_str_mv |
https://creativecommons.org/licenses/by/4.0 |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
Research, Society and Development |
publisher.none.fl_str_mv |
Research, Society and Development |
dc.source.none.fl_str_mv |
Research, Society and Development; Vol. 11 No. 2; e13011225103 Research, Society and Development; Vol. 11 Núm. 2; e13011225103 Research, Society and Development; v. 11 n. 2; e13011225103 2525-3409 reponame:Research, Society and Development instname:Universidade Federal de Itajubá (UNIFEI) instacron:UNIFEI |
instname_str |
Universidade Federal de Itajubá (UNIFEI) |
instacron_str |
UNIFEI |
institution |
UNIFEI |
reponame_str |
Research, Society and Development |
collection |
Research, Society and Development |
repository.name.fl_str_mv |
Research, Society and Development - Universidade Federal de Itajubá (UNIFEI) |
repository.mail.fl_str_mv |
rsd.articles@gmail.com |
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1797052791939661824 |