Zobrazeno 1 - 10
of 60
pro vyhledávání: '"Fabrício Martins Lopes"'
Autor:
Juliana Costa-Silva, Douglas S. Domingues, David Menotti, Mariangela Hungria, Fabrício Martins Lopes
Publikováno v:
Computational and Structural Biotechnology Journal, Vol 21, Iss , Pp 86-98 (2023)
Analysis of differential gene expression from RNA-seq data has become a standard for several research areas. The steps for the computational analysis include many data types and file formats, and a wide variety of computational tools that can be appl
Externí odkaz:
https://doaj.org/article/06890cc1b1ae44559e9ae3a5a1725200
Autor:
Alex Nunes da Silva, Matheus Montanini Breve, Jesús Pascual Mena-Chalco, Fabrício Martins Lopes
Publikováno v:
PLoS ONE, Vol 17, Iss 1, p e0261200 (2022)
The growth and popularization of platforms on scientific production has been the subject of several studies, producing relevant analyses of co-authorship behavior among groups of researchers. Researchers and their scientific productions can be analys
Externí odkaz:
https://doaj.org/article/1c779492d3dc46e0aae2d2d912992665
Autor:
Matheus H. Pimenta-Zanon, Vinicius Augusto de Souza, Ronaldo Fumio Hashimoto, Fabrício Martins Lopes
Publikováno v:
Smart Innovation, Systems and Technologies ISBN: 9789811960673
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ec89b55a0500c3361340149c59093060
https://doi.org/10.1007/978-981-19-6068-0_44
https://doi.org/10.1007/978-981-19-6068-0_44
Autor:
Juliana Costa-Silva, Douglas S. Domingues, David Menotti, Mariangela Hungria, Fabrício Martins Lopes
Publikováno v:
Repositório Institucional da USP (Biblioteca Digital da Produção Intelectual)
Universidade de São Paulo (USP)
instacron:USP
Universidade de São Paulo (USP)
instacron:USP
Analysis of differential gene expression from RNA-seq data has become a standard for several research areas. The steps for the computational analysis include many data types and file formats, and a wide variety of computational tools that can be appl
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::053ba3764c14013c6c319ed73785af4e
https://pubmed.ncbi.nlm.nih.gov/36514333
https://pubmed.ncbi.nlm.nih.gov/36514333
Autor:
Eber Fabiano Pacanhela, Artur Berbel Lirio Rondina, Marco Antonio Nogueira, Mariangela Hungria, Priscila Tiemi Maeda Saito, Fabrício Martins Lopes
Publikováno v:
Anais do XVI Brazilian e-Science Workshop (BRESCI 2022).
A soja é a oleaginosa mais cultivada no mundo e requer grandes quantidades de nitrogênio para a nutrição da planta. O nutriente pode ser fornecido por fertilizantes químicos, prejudiciais ao meio ambiente. No entanto, o processo de fixação bio
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::cd29b866c92570937e4d55efad75273f
https://doi.org/10.5753/bresci.2022.222796
https://doi.org/10.5753/bresci.2022.222796
Publikováno v:
Briefings in bioinformatics. 23(5)
This letter points out a conceptual error made by the authors of a published paper, which presents a review and evaluation of computational methods in lncRNA identification. The error was made in the execution of the BASiNET method when considering a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e92df25b3268b9f3950d4088318e3891
https://pubmed.ncbi.nlm.nih.gov/35914949
https://pubmed.ncbi.nlm.nih.gov/35914949
Publikováno v:
Expert Systems with Applications. 133:215-224
Over the last years complex data (e.g. images) have been growing in a very fast pace. This demands the ability to describe and to categorize them. To solve this problem it is essential to develop efficient and effective vision-based expert techniques
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ab8586cad713b000749b3634b38dabb4
https://doi.org/10.1016/j.eswa.2019.05.021
https://doi.org/10.1016/j.eswa.2019.05.021
Autor:
Alexandre Rossi Paschoal, Fabrício Martins Lopes, Liliane Santana Oliveira, Danilo Sipoli Sanches, Vinicius Maracaja-Coutinho, Andressa Caroline Patera, Douglas Silva Domingues, Pedro Henrique Bugatti, Priscila T. M. Saito, Alan Mitchell Durham
Publikováno v:
Methods in Molecular Biology ISBN: 9781071616444
This chapter provides two main contributions: (1) a description of computational tools and databases used to identify and analyze transposable elements (TEs) and circRNAs in plants; and (2) data analysis on public TE and circRNA data. Our goal is to
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3257f99cdb6bd24d799886ff9146afe8
https://doi.org/10.1007/978-1-0716-1645-1_9
https://doi.org/10.1007/978-1-0716-1645-1_9
Feature extraction approaches for biological sequences: a comparative study of mathematical features
Autor:
Fabrício Martins Lopes, Alexandre Rossi Paschoal, André C. P. L. F. de Carvalho, Douglas Silva Domingues, Danilo Sipoli Sanches, Robson Parmezan Bonidia, Lucas Dias Hiera Sampaio
Publikováno v:
Repositório Institucional da USP (Biblioteca Digital da Produção Intelectual)
Universidade de São Paulo (USP)
instacron:USP
Universidade de São Paulo (USP)
instacron:USP
As consequence of the various genomic sequencing projects, an increasing volume of biological sequence data is being produced. Although machine learning algorithms have been successfully applied to a large number of genomic sequence-related problems,
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9ea5cf0f0b91ac89e3c1f3c5fc0ca598
https://pubmed.ncbi.nlm.nih.gov/33585910
https://pubmed.ncbi.nlm.nih.gov/33585910
Autor:
Fabrício Martins Lopes, Douglas Silva Domingues, André C. P. L. F. de Carvalho, Alexandre Rossi Paschoal, Danilo Sipoli Sanches, Lucas Dias Hiera Sampaio, Robson Parmezan Bonidia
The number of available biological sequences has increased significantly in recent years due to various genomic sequencing projects, creating a huge volume of data. Consequently, new computational methods are needed to analyze and extract information
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::97817e4e6d14e4524fae7486341e56f0
https://doi.org/10.1101/2020.06.08.140368
https://doi.org/10.1101/2020.06.08.140368