Zobrazeno 1 - 10
of 26
pro vyhledávání: '"Paolo Perlasca"'
Autor:
Emanuele Cavalleri, Alberto Cabri, Mauricio Soto-Gomez, Sara Bonfitto, Paolo Perlasca, Jessica Gliozzo, Tiffany J. Callahan, Justin Reese, Peter N. Robinson, Elena Casiraghi, Giorgio Valentini, Marco Mesiti
Publikováno v:
Scientific Data, Vol 11, Iss 1, Pp 1-24 (2024)
Abstract The “RNA world” represents a novel frontier for the study of fundamental biological processes and human diseases and is paving the way for the development of new drugs tailored to each patient’s biomolecular characteristics. Although s
Externí odkaz:
https://doaj.org/article/bf58cdba16da4012b04049f45ff9f53e
Publikováno v:
IEEE Access, Vol 11, Pp 103585-103600 (2023)
Nowadays there is a great interest in the visualization of property graphs to make their navigation, inspection, and visual analysis easier. However, property graphs can be quite large and their rendering on web browsers can lead to a dark cloud of p
Externí odkaz:
https://doaj.org/article/6d6bc09bfa904f17af5965cac547f036
Autor:
Paolo Perlasca, Marco Frasca, Cheick Tidiane Ba, Marco Notaro, Alessandro Petrini, Elena Casiraghi, Giuliano Grossi, Jessica Gliozzo, Giorgio Valentini, Marco Mesiti
Publikováno v:
BMC Bioinformatics, Vol 20, Iss 1, Pp 1-19 (2019)
Abstract Background One of the main issues in the automated protein function prediction (AFP) problem is the integration of multiple networked data sources. The UNIPred algorithm was thereby proposed to efficiently integrate —in a function-specific
Externí odkaz:
https://doaj.org/article/b44a7925b6f34577b2d0fcf025f530e2
Autor:
Paolo Perlasca, Marco Frasca, Cheick Tidiane Ba, Jessica Gliozzo, Marco Notaro, Mario Pennacchioni, Giorgio Valentini, Marco Mesiti
Publikováno v:
PLoS ONE, Vol 15, Iss 12, p e0244241 (2020)
The visual exploration and analysis of biomolecular networks is of paramount importance for identifying hidden and complex interaction patterns among proteins. Although many tools have been proposed for this task, they are mainly focused on the query
Externí odkaz:
https://doaj.org/article/2e89b0ec8dcc49f5b6fd3762e2afefae
Autor:
Marco Frasca, Giuliano Grossi, Jessica Gliozzo, Marco Mesiti, Marco Notaro, Paolo Perlasca, Alessandro Petrini, Giorgio Valentini
Publikováno v:
BMC Bioinformatics, Vol 19, Iss S10, Pp 63-74 (2018)
Abstract Background Several problems in network biology and medicine can be cast into a framework where entities are represented through partially labeled networks, and the aim is inferring the labels (usually binary) of the unlabeled part. Connectio
Externí odkaz:
https://doaj.org/article/4c2096baea9049e6a22441e0d63a5f50
Autor:
Paolo Perlasca, Marco Frasca, Cheick Tidiane Ba, Jessica Gliozzo, Marco Notaro, Mario Pennacchioni, Giorgio Valentini, Marco Mesiti
Publikováno v:
Communications in Computer and Information Science ISBN: 9783031253799
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b48e86f3f048507fd33d1678568f8283
https://doi.org/10.1007/978-3-031-25380-5_15
https://doi.org/10.1007/978-3-031-25380-5_15
Autor:
Cheick Tidiane Ba, Marco Mesiti, Paolo Perlasca, Marco Notaro, Jessica Gliozzo, Mario Pennacchioni, Marco Frasca, Giorgio Valentini
Publikováno v:
PLoS ONE
PLoS ONE, Vol 15, Iss 12, p e0244241 (2020)
PLoS ONE, Vol 15, Iss 12, p e0244241 (2020)
The visual exploration and analysis of biomolecular networks is of paramount importance for identifying hidden and complex interaction patterns among proteins. Although many tools have been proposed for this task, they are mainly focused on the query
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::abf099cb785f4c2e0add2227d7f5a49b
https://pubmed.ncbi.nlm.nih.gov/33351828
https://pubmed.ncbi.nlm.nih.gov/33351828
Autor:
Marco Frasca, Viviana Vallacchi, Matteo Re, Giuliano Grossi, Jessica Gliozzo, Elena Casiraghi, Paolo Perlasca, Marco Mesiti, Elisabetta Vergani, Alessandro Petrini, Giorgio Valentini, Alberto Paccanaro
Publikováno v:
Scientific Reports
Scientific Reports, Vol 10, Iss 1, Pp 1-15 (2020)
Scientific Reports, Vol 10, Iss 1, Pp 1-15 (2020)
Methods for phenotype and outcome prediction are largely based on inductive supervised models that use selected biomarkers to make predictions, without explicitly considering the functional relationships between individuals. We introduce a novel netw
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5339dbbba093c24f154c415a4d6d6f75
http://europepmc.org/articles/PMC7046773
http://europepmc.org/articles/PMC7046773
Autor:
Elena Casiraghi, Marco Notaro, Giuliano Grossi, Marco Mesiti, Matteo Re, Marco Frasca, Cheick Tidiane Ba, Paolo Perlasca, Alessandro Petrini, Giorgio Valentini, Jessica Gliozzo
Publikováno v:
Computational Intelligence Methods for Bioinformatics and Biostatistics ISBN: 9783030345846
CIBB
CIBB
Many interactions among bio-molecular entities, e.g. genes, proteins, metabolites, can be easily represented by means of property graphs, i.e. graphs that are annotated both on the vertices (e.g. entity identifier, Gene Ontology or Human Phenotype On
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a161693921eebc15452f36106ec48576
https://doi.org/10.1007/978-3-030-34585-3_8
https://doi.org/10.1007/978-3-030-34585-3_8
Publikováno v:
Multimedia Tools and Applications. 77:2083-2114
A large range of new applications are appearing nowadays on the Web in which content and data produced by single users or groups are going to be adapted, composed and aggregated and then redistributed in other forms to other users and/or groups. In t
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ae10e7363e2656914cfc9d5d6079b607
https://doi.org/10.1007/s11042-017-4382-x
https://doi.org/10.1007/s11042-017-4382-x