1,354,760 research outputs found
FuNeL
No full text<p>FuNeL is a protocol to infer functional networks from machine learning models. It is a general approach that uses BioHEL, a rule-based evolutionary classifier, to describe the expression samples as a set of rules and then infers interactions between genes that act together within rules to predict the samples class. FuNeL generates co-prediction networks, that capture biological knowledge complementary to that contained in popular similarity-based co-expression networks.</p>
A method to compute the communicability of nodes through causal paths in temporal networks
No full textWe present a method aimed to compute the communicability (broadcast and receive) of nodes through causal paths in temporal networks. The method considers all possible combinations of chronologically ordered products of adjacency matrices of the network snapshots and by means of a damping procedure favors the paths that have high communication efficiency. We apply the method to four real-world networks of face-to-face human contacts and identify the nodes with high communicability. The accuracy of the method is proved by studying the spread of an epidemic in the networks using the susceptible–infected–recovered model. We show that if a node with high broadcast is chosen as the origin of the outbreak of infection then the epidemic spreads early while it is delayed and inhibited if the origin of infection is a node with low broadcast. Receiving nodes can be treated as broadcasters if the arrow of time is reversed
Analysis of the Web Graph Aggregated by Host and Pay-Level Domain
No full textIn this paper the web is analyzed as a graph aggregated by host and pay-level domain (PLD). The web graph datasets, publicly available, have been released by the Common Crawl Foundation(http://commoncrawl.org ) and are based on a web crawl performed during the period May-June-July 2017. The host graph has ~ 1.3 billion nodes and ~ 5.3 billion arcs. The PLD graph has ~ 91 million nodes and ~ 1.1 billion arcs. We study the distributions of degree and sizes of strongly/weakly connected components (SCC/WCC) focusing on power laws detection using statistical methods. The statistical plausibility of the power law model is compared with that of several alternative distributions. While there is no evidence of power law tails on host level, they emerge on PLD aggregation for indegree, SCC and WCC size distributions. Finally, we analyze distance-related features by studying the cumulative distributions of the shortest path lengths, and give an estimation of the diameters of the graphs. © Springer Nature Switzerland AG 2019
The Graph Structure of the Internet at the Autonomous Systems Level during Ten Years
No full textWe study how the graph structure of the Internet at the Autonomous Systems(AS) level evolved during a decade. For each year of the period 2008-2017 weconsider a snapshot of the AS graph and examine how many features related tostructure, connectivity and centrality changed over time. The analysis of thesemetrics provides topological and data traffic information and allows to clarifysome assumptions about the models concerning the evolution of the Internetgraph structure. We find that the size of the Internet roughly doubled. Theoverall trend of the average connectivity is an increase over time, while thatof the shortest path length is a decrease over time. The internal core of theInternet is composed of a small fraction of big AS and is more stable andconnected that external cores. A hierarchical organization emerges where asmall fraction of big hubs are connected to many regions with high internalcohesiveness, poorly connected among them and containing AS with low and mediumnumber of links. Centrality measurements indicate that the average number ofshortest paths crossing an AS or containing a link between two of themdecreased over time
High performance computing on CRESCO infrastructure: research activities and results 2013
No full textIl volume, in inglese, contiene una raccolta di articoli che illustrano i principali risultati ottenuti nel 2013 utilizzando le infrastrutture di calcolo scientifico CRESCO in campi come la scienza dei materiali, la fluidodinamica computazionale, la ricerca sul clima, la fisica nucleare e la biofisica.
I sistemi CRESCO fanno parte di ENEA-GRID, l'infrastruttura di calcolo ENEA distribuita sui Centri di Portici, Frascati, Casaccia, Brindisi, Bologna e Trisaia. Le risorse di calcolo più importanti sono
ospitate nel Centro di Portici. I servizi di calcolo sono stati forniti a più di un centinaio di utenti, che svolgono attività di ricerca e sviluppo ENEA in molti settori scientifici e tecnologici, e a gruppi di ricerca universitari e industriali. Il rapporto mostra la varietà delle applicazioni del calcolo ad alte prestazioni, una tecnologia importante per la scienza e l'ingegneria
Causal Paths in Temporal Networks of Face-to-Face Human Interactions
No full textIn a temporal network, causal paths are characterized by the fact that links from a source to a target must respect the chronological order. In this paper we study the causal paths structure in temporal networks of face-to-face human interactions in different social contexts
Dynamics of a Deuterated C-Phycocyanin Protein as studied by Coherent inelastic Neutron scattering
No full text
Leiomyomatosis Peritonealis Disseminata: a case report
No full textA 32-year-old woman was referred to our Institution with a persistent abdominal distension lasting for two weeks.
On the admission she showed a normal serum haemoglobin level and thrombocytopenia.
She had a history of abdominal discomfort and uncommon pelvic pains.
These symptoms had been diagnosed and treated as a gastro-intestinal infection
In vivo PCR-DGGE analysis of Lactobacillus plantarum and Oenococcus oeni populations in red wine
No full textAbstract. In order to monitor Lactobacillus plantarum and Oenococcus oeni in red wine produced with
Italian grape (variety ‘‘Primitivo di Puglia’’), a polymerase chain reaction– denaturing gradient gel
electrophoresis (PCR-DGGE) approach using the rpoB as gene target was established. Wine was treated
or not with potassium metabisulphite and supplemented with a commercial bacterial starter of O. oeni to
encourage malolactic fermentation. Samples were taken from the vinification tanks at 4, 10, 16, 22, and
28 days after the start of alcoholic fermentation. Genomic DNA was directly isolated from wine and
identification of lactic acid bacteria was performed using primers rpoB1, rpoB1O, and rpoB2 able
to amplify a region of 336 bp corresponding to the rpoB gene. Amplified fragments were separated in a
30–60% DGGE gradient, and the ability of the PCR-DGGE analysis to distinguish L. plantarum and
O. oeni was assessed. The results reported suggest that the PCR-DGGE method, based on the rpoB gene
as molecular marker, is a reproducible and suitable tool and may be of great value for wine makers in
order to monitor spoilage microorganisms during wine fermentation
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