Zobrazeno 1 - 10
of 54
pro vyhledávání: '"Luca Tesei"'
Publikováno v:
BMC Bioinformatics, Vol 23, Iss S6, Pp 1-25 (2023)
Abstract Background The ability to compare RNA secondary structures is important in understanding their biological function and for grouping similar organisms into families by looking at evolutionarily conserved sequences such as 16S rRNA. Most compa
Externí odkaz:
https://doaj.org/article/1771e534251545858acf608b50514e7a
Publikováno v:
BMC Bioinformatics, Vol 20, Iss S4, Pp 1-18 (2019)
Abstract Background RNA secondary structure comparison is a fundamental task for several studies, among which are RNA structure prediction and evolution. The comparison can currently be done efficiently only for pseudoknot-free structures due to thei
Externí odkaz:
https://doaj.org/article/dcb808a05d114dc18a3b0f5782b6747d
Publikováno v:
BMC Research Notes, Vol 11, Iss 1, Pp 1-7 (2018)
Abstract Objective An innovative method based on topological data analysis is introduced for classifying EEG recordings of patients affected by epilepsy. We construct a topological space from a collection of EEGs signals using Persistent Homology; th
Externí odkaz:
https://doaj.org/article/c8e35556971e4325adcda4fbcd838306
Publikováno v:
Electronic Proceedings in Theoretical Computer Science, Vol 231, Iss Proc. GaM 2016, Pp 31-41 (2016)
We propose a new approach for modelling the process of RNA folding as a graph transformation guided by the global value of free energy. Since the folding process evolves towards a configuration in which the free energy is minimal, the global behaviou
Externí odkaz:
https://doaj.org/article/751337c4da03486aa0d501da457b7a04
Publikováno v:
Entropy, Vol 17, Iss 10, Pp 6872-6892 (2015)
In this paper, we propose a methodology for deriving a model of a complex system by exploiting the information extracted from topological data analysis. Central to our approach is the S[B] paradigm in which a complex system is represented by a two-le
Externí odkaz:
https://doaj.org/article/4cacf6e33d074f36b7a258e9d86330f2
Publikováno v:
Electronic Proceedings in Theoretical Computer Science, Vol 91, Iss Proc. FOCLASA 2012, Pp 112-126 (2012)
This work introduces a general multi-level model for self-adaptive systems. A self-adaptive system is seen as composed by two levels: the lower level describing the actual behaviour of the system and the upper level accounting for the dynamically cha
Externí odkaz:
https://doaj.org/article/daa8d45ee4be4bc8ba8c34d27b2e2326
Publikováno v:
Electronic Proceedings in Theoretical Computer Science, Vol 40, Iss Proc. MeCBIC 2010, Pp 70-84 (2010)
Many biological phenomena are inherently multiscale, i.e. they are characterized by interactions involving different spatial and temporal scales simultaneously. Though several approaches have been proposed to provide "multilayer" models, only Complex
Externí odkaz:
https://doaj.org/article/57791b31622e4c0f8ca816bb665d22aa
Autor:
Federico Buti, Flavio Corradini, Emanuela Merelli, Elio Paschini, Pierluigi Penna, Luca Tesei
Publikováno v:
Electronic Proceedings in Theoretical Computer Science, Vol 33, Iss Proc. AMCA-POP 2010, Pp 37-55 (2010)
We define an individual-based probabilistic model of a sole (Solea solea) behaviour. The individual model is given in terms of an Extended Probabilistic Discrete Timed Automaton (EPDTA), a new formalism that is introduced in the paper and that is sho
Externí odkaz:
https://doaj.org/article/a1fe6448eab84f4c8ec39f862dca9abb
Summary Current methods for comparing RNA secondary structures are based on tree representations and exploit edit distance or alignment algorithms. Most of them can only process structures without pseudoknots. To overcome this limitation, we introduc
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::818643f9fbec995bf25512db6db117d0
http://hdl.handle.net/11581/440804
http://hdl.handle.net/11581/440804
Autor:
Emanuela Merelli, Marco Piangerelli, Luca Tesei, Jose Barbosa, Paulo Leitão, Riccardo Paci, Marco Amador, Jeff Johnson, Nenad Stojanovic
Publikováno v:
Ubiquity. 2018:1-13
Transforming the latent value of big data into real value requires the great human intelligence and application of human-data scientists. Data scientists are expected to have a wide range of technical skills alongside being passionate self-directed p
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d316d2aee4f97d2695202065fe167bc0
https://doi.org/10.1145/3158350
https://doi.org/10.1145/3158350