Zobrazeno 1 - 10
of 49
pro vyhledávání: '"Gianvito Pio"'
Autor:
Andrea Simeon, Miloš Radovanović, Tatjana Lončar-Turukalo, Michelangelo Ceci, Sanja Brdar, Gianvito Pio
Publikováno v:
BMC Bioinformatics, Vol 25, Iss 1, Pp 1-19 (2024)
Abstract Background Microbiome dysbiosis has recently been associated with different diseases and disorders. In this context, machine learning (ML) approaches can be useful either to identify new patterns or learn predictive models. However, data to
Externí odkaz:
https://doaj.org/article/e0eef787c32241e5ada873995f307c95
Autor:
Laura Judith Marcos-Zambrano, Víctor Manuel López-Molina, Burcu Bakir-Gungor, Marcus Frohme, Kanita Karaduzovic-Hadziabdic, Thomas Klammsteiner, Eliana Ibrahimi, Leo Lahti, Tatjana Loncar-Turukalo, Xhilda Dhamo, Andrea Simeon, Alina Nechyporenko, Gianvito Pio, Piotr Przymus, Alexia Sampri, Vladimir Trajkovik, Blanca Lacruz-Pleguezuelos, Oliver Aasmets, Ricardo Araujo, Ioannis Anagnostopoulos, Önder Aydemir, Magali Berland, M. Luz Calle, Michelangelo Ceci, Hatice Duman, Aycan Gündoğdu, Aki S. Havulinna, Kardokh Hama Najib Kaka Bra, Eglantina Kalluci, Sercan Karav, Daniel Lode, Marta B. Lopes, Patrick May, Bram Nap, Miroslava Nedyalkova, Inês Paciência, Lejla Pasic, Meritxell Pujolassos, Rajesh Shigdel, Antonio Susín, Ines Thiele, Ciprian-Octavian Truică, Paul Wilmes, Ercument Yilmaz, Malik Yousef, Marcus Joakim Claesson, Jaak Truu, Enrique Carrillo de Santa Pau
Publikováno v:
Frontiers in Microbiology, Vol 14 (2023)
The human microbiome has become an area of intense research due to its potential impact on human health. However, the analysis and interpretation of this data have proven to be challenging due to its complexity and high dimensionality. Machine learni
Externí odkaz:
https://doaj.org/article/7e8c2a9ec3074e74b5f235b502816b53
Advancing microbiome research with machine learning: key findings from the ML4Microbiome COST action
Autor:
Domenica D’Elia, Jaak Truu, Leo Lahti, Magali Berland, Georgios Papoutsoglou, Michelangelo Ceci, Aldert Zomer, Marta B. Lopes, Eliana Ibrahimi, Aleksandra Gruca, Alina Nechyporenko, Marcus Frohme, Thomas Klammsteiner, Enrique Carrillo-de Santa Pau, Laura Judith Marcos-Zambrano, Karel Hron, Gianvito Pio, Andrea Simeon, Ramona Suharoschi, Isabel Moreno-Indias, Andriy Temko, Miroslava Nedyalkova, Elena-Simona Apostol, Ciprian-Octavian Truică, Rajesh Shigdel, Jasminka Hasić Telalović, Erik Bongcam-Rudloff, Piotr Przymus, Naida Babić Jordamović, Laurent Falquet, Sonia Tarazona, Alexia Sampri, Gaetano Isola, David Pérez-Serrano, Vladimir Trajkovik, Lubos Klucar, Tatjana Loncar-Turukalo, Aki S. Havulinna, Christian Jansen, Randi J. Bertelsen, Marcus Joakim Claesson
Publikováno v:
Frontiers in Microbiology, Vol 14 (2023)
The rapid development of machine learning (ML) techniques has opened up the data-dense field of microbiome research for novel therapeutic, diagnostic, and prognostic applications targeting a wide range of disorders, which could substantially improve
Externí odkaz:
https://doaj.org/article/5f8da7afb1744c6687be2586111ac38e
Publikováno v:
Scientific Reports, Vol 10, Iss 1, Pp 1-15 (2020)
Abstract The reconstruction of Gene Regulatory Networks (GRNs) from gene expression data, supported by machine learning approaches, has received increasing attention in recent years. The task at hand is to identify regulatory links between genes in a
Externí odkaz:
https://doaj.org/article/3fa04fcf691b4bbcbf6dcf37d380ecce
Publikováno v:
BMC Bioinformatics, Vol 21, Iss 1, Pp 1-24 (2020)
Abstract Background The study of functional associations between ncRNAs and human diseases is a pivotal task of modern research to develop new and more effective therapeutic approaches. Nevertheless, it is not a trivial task since it involves entitie
Externí odkaz:
https://doaj.org/article/e29df4a488b8465ebc2fe3c6a85f30c2
Publikováno v:
IEEE Access, Vol 8, Pp 156053-156066 (2020)
Smart grids are power grids where clients may actively participate in energy production, storage and distribution. Smart grid management raises several challenges, including the possible changes and evolutions in terms of energy consumption and produ
Externí odkaz:
https://doaj.org/article/7692e3cd523440ec9d8ec459bacac55d
Publikováno v:
Journal of Big Data, Vol 6, Iss 1, Pp 1-27 (2019)
Abstract Recent developments in sensor networks and mobile computing led to a huge increase in data generated that need to be processed and analyzed efficiently. In this context, many distributed data mining algorithms have recently been proposed. Fo
Externí odkaz:
https://doaj.org/article/f58cd3d407cb4a97887a4025b1a5fe95
Autor:
Isabel Moreno-Indias, Leo Lahti, Miroslava Nedyalkova, Ilze Elbere, Gennady Roshchupkin, Muhamed Adilovic, Onder Aydemir, Burcu Bakir-Gungor, Enrique Carrillo-de Santa Pau, Domenica D’Elia, Mahesh S. Desai, Laurent Falquet, Aycan Gundogdu, Karel Hron, Thomas Klammsteiner, Marta B. Lopes, Laura Judith Marcos-Zambrano, Cláudia Marques, Michael Mason, Patrick May, Lejla Pašić, Gianvito Pio, Sándor Pongor, Vasilis J. Promponas, Piotr Przymus, Julio Saez-Rodriguez, Alexia Sampri, Rajesh Shigdel, Blaz Stres, Ramona Suharoschi, Jaak Truu, Ciprian-Octavian Truică, Baiba Vilne, Dimitrios Vlachakis, Ercument Yilmaz, Georg Zeller, Aldert L. Zomer, David Gómez-Cabrero, Marcus J. Claesson
Publikováno v:
Frontiers in Microbiology, Vol 12 (2021)
The human microbiome has emerged as a central research topic in human biology and biomedicine. Current microbiome studies generate high-throughput omics data across different body sites, populations, and life stages. Many of the challenges in microbi
Externí odkaz:
https://doaj.org/article/58ddf268165e41df95208c7ec045cc9d
Publikováno v:
PLoS ONE, Vol 10, Iss 12, p e0144031 (2015)
The task of gene regulatory network reconstruction from high-throughput data is receiving increasing attention in recent years. As a consequence, many inference methods for solving this task have been proposed in the literature. It has been recently
Externí odkaz:
https://doaj.org/article/f36721dd62be4c37bdd189f4c48e6f9b
Publikováno v:
International Journal of Computational Intelligence Systems, Vol 6, Iss 2 (2013)
Fuzzy relations are simple mathematical structures that enable a very general representation of fuzzy knowledge, and fuzzy relational calculus offers a powerful machinery for approximate reasoning. However, one of the most relevant limitations of app
Externí odkaz:
https://doaj.org/article/211df7285ca54bec90137d63ac45a4db