Zobrazeno 1 - 10
of 17
pro vyhledávání: '"Castelli M."'
Publikováno v:
Repositório Científico de Acesso Aberto de Portugal
Repositório Científico de Acesso Aberto de Portugal (RCAAP)
instacron:RCAAP
Repositório Científico de Acesso Aberto de Portugal (RCAAP)
instacron:RCAAP
Bakurov, I., Buzzelli, M., Schettini, R., Castelli, M., & Vanneschi, L. (2022). Structural similarity index (SSIM) revisited: A data-driven approach. Expert Systems with Applications, 189, 1-19. [116087]. [Advanced online publication on 27 October 20
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9843548d4dbccae8705fb8a2d19cdea0
Publikováno v:
Journal of Computational Biology. 25:1091-1105
Expression quantitative trait loci (eQTL) analysis is an emerging method for establishing the impact of genetic variations (such as single nucleotide polymorphisms) on the expression levels of genes. Although different methods for evaluating the impa
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783030227432
ICCS (3)
ICCS (3)
MicroRNAs (miRNAs) are small non-coding RNAs with a key role in the post-transcriptional gene expression regularization, thanks to their ability to link with the target mRNA through the complementary base pairing mechanism. Given their role, it is im
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::807c41963edb0e10912f28e1f8d4f5c3
https://doi.org/10.1007/978-3-030-22744-9_3
https://doi.org/10.1007/978-3-030-22744-9_3
Publikováno v:
Complexity, Vol 2018 (2018)
One of the most challenging tasks when adopting Bayesian networks (BNs) is the one of learning their structure from data. This task is complicated by the huge search space of possible solutions and by the fact that the problem isNP-hard. Hence, a ful
Publikováno v:
Scopus-Elsevier
Beretta, S., Castelli, M., Gonçalves, I., Merelli, I., & Ramazzotti, D. (2016). Combining Bayesian approaches and evolutionary techniques for the inference of breast cancer networks. In J. J. Merelo, J. M. Cadenas, F. Melicio, A. Dourado, A. Ruano,
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::31814cbac45329413a53cdd0e5b9ea80
http://arxiv.org/abs/1703.03041
http://arxiv.org/abs/1703.03041
In this work, we study the influence of the population size on the learning ability of Geometric Semantic Genetic Programming for the task of symbolic regression. A large set of experiments, considering different population size values on different r
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::99bba1039d238028fb564b62181ee171
https://hdl.handle.net/11368/2947794
https://hdl.handle.net/11368/2947794
Publikováno v:
IEEE Transactions on Cybernetics. 44:103-113
SFX(opens in a new window)|View at Publisher| Export | Download | More... IEEE Transactions on Cybernetics Volume 44, Issue 1, January 2014, Article number 6476653, Pages 103-113 Semantic search-based genetic programming and the effect of intron dele
Publikováno v:
Expert Systems with Applications. 40:6856-6862
Concrete is a composite construction material made primarily with aggregate, cement, and water. In addition to the basic ingredients used in conventional concrete, high-performance concrete incorporates supplementary cementitious materials, such as f
Autor:
Yuliana Martínez, Luis Muñoz, Stefano Beretta, Sara Silva, Leonardo Trujillo, Ivan Merelli, Mauro Castelli, Luciano Milanesi
Publikováno v:
PDP
PDP2016, pp. 528–534, Heraklion, Greece, 17-19 Feb. 2016
info:cnr-pdr/source/autori:Beretta, Stefano; Castelli, Mauro; Martinez, Yuliana; Munoz, Luis; Silva, Sara; Trujillo, Leonardo; Milanesi, Luciano; Merelli, Ivan/congresso_nome:PDP2016/congresso_luogo:Heraklion, Greece/congresso_data:17-19 Feb. 2016/anno:2016/pagina_da:528/pagina_a:534/intervallo_pagine:528–534
PDP2016, pp. 528–534, Heraklion, Greece, 17-19 Feb. 2016
info:cnr-pdr/source/autori:Beretta, Stefano; Castelli, Mauro; Martinez, Yuliana; Munoz, Luis; Silva, Sara; Trujillo, Leonardo; Milanesi, Luciano; Merelli, Ivan/congresso_nome:PDP2016/congresso_luogo:Heraklion, Greece/congresso_data:17-19 Feb. 2016/anno:2016/pagina_da:528/pagina_a:534/intervallo_pagine:528–534
Although several computational methods have been developed for predicting interactions between miRNA and target genes, there are substantial differences in the achieved results. For this reason, machine learning approaches are widely used for integra
Big data knowledge discovery emerged as an important factor contributing to advancements in society at large. Still, researchers continuously seek to advance existing methods and provide novel ones for analysing vast data sets to make sense of the da
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8ac65e5791b5d90a7a60c6b21ca582db
http://hdl.handle.net/10281/107079
http://hdl.handle.net/10281/107079