Andre C P L F de Carvalho
Overview
Explore the profile of Andre C P L F de Carvalho including associated specialties, affiliations and a list of published articles.
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15
Citations
101
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Recent Articles
1.
Florentino B, Parmezan Bonidia R, Sanches N, da Rocha U, de Carvalho A
Comput Struct Biotechnol J
. 2024 Jun;
23:2267-2276.
PMID: 38827228
Machine Learning (ML) algorithms have been important tools for the extraction of useful knowledge from biological sequences, particularly in healthcare, agriculture, and the environment. However, the categorical and unstructured nature...
2.
Avila Santos A, de Almeida B, Bonidia R, Stadler P, Stefanic P, Mandic-Mulec I, et al.
RNA Biol
. 2024 Mar;
21(1):1-12.
PMID: 38528797
The accurate classification of non-coding RNA (ncRNA) sequences is pivotal for advanced non-coding genome annotation and analysis, a fundamental aspect of genomics that facilitates understanding of ncRNA functions and regulatory...
3.
Bonidia R, Avila Santos A, de Almeida B, Stadler P, da Rocha U, Sanches D, et al.
Entropy (Basel)
. 2023 Jul;
24(10).
PMID: 37420418
In recent years, there has been an exponential growth in sequencing projects due to accelerated technological advances, leading to a significant increase in the amount of data and resulting in...
4.
Menezes A, de Moura G, Alves C, de Carvalho A
Neural Netw
. 2023 Feb;
161:476-493.
PMID: 36805263
The field of Continual Learning investigates the ability to learn consecutive tasks without losing performance on those previously learned. The efforts of researchers have been mainly focused on incremental classification...
5.
Bonidia R, Avila Santos A, de Almeida B, Stadler P, da Rocha U, Sanches D, et al.
Brief Bioinform
. 2022 Jun;
23(4).
PMID: 35753697
Recent technological advances have led to an exponential expansion of biological sequence data and extraction of meaningful information through Machine Learning (ML) algorithms. This knowledge has improved the understanding of...
6.
Bonidia R, Domingues D, Sanches D, de Carvalho A
Brief Bioinform
. 2021 Nov;
23(1).
PMID: 34750626
One of the main challenges in applying machine learning algorithms to biological sequence data is how to numerically represent a sequence in a numeric input vector. Feature extraction techniques capable...
7.
Alkhnbashi O, Mitrofanov A, Bonidia R, Raden M, Tran V, Eggenhofer F, et al.
Nucleic Acids Res
. 2021 Jun;
49(W1):W125-W130.
PMID: 34133710
CRISPR-Cas systems are adaptive immune systems in prokaryotes, providing resistance against invading viruses and plasmids. The identification of CRISPR loci is currently a non-standardized, ambiguous process, requiring the manual combination...
8.
Feature extraction approaches for biological sequences: a comparative study of mathematical features
Bonidia R, Sampaio L, Domingues D, Paschoal A, Lopes F, de Carvalho A, et al.
Brief Bioinform
. 2021 Feb;
22(5).
PMID: 33585910
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...
9.
Padilha V, Alkhnbashi O, Shah S, de Carvalho A, Backofen R
Gigascience
. 2020 Jun;
9(6).
PMID: 32556168
Background: CRISPR-Cas genes are extraordinarily diverse and evolve rapidly when compared to other prokaryotic genes. With the rapid increase in newly sequenced archaeal and bacterial genomes, manual identification of CRISPR-Cas...
10.
Spadon G, de Carvalho A, Rodrigues-Jr J, Alves L
Sci Rep
. 2019 Aug;
9(1):11801.
PMID: 31409862
Human mobility has a significant impact on several layers of society, from infrastructural planning and economics to the spread of diseases and crime. Representing the system as a complex network,...