Demo Data from EDBT 2026 / reviewers in the wild / expert
Michele Petterlini
dblp:07/2578
· DBLP profile ↗
2ranked-venue papers
0as first author
0since 2021 · last 2009
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 1Applied, interdisciplinary, general and emerging computing · 1
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Interdisciplinary, comprehensive, and emerging computing
1 paper |
Bioinformatics and computational biology · 100% |
Topics — the 2 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Bioinformatics and computational biology › network bioinformatics
biological network analysis |
0.1 | 1 | 2009 | Analyzing biological network parameters with CentiScaPe · Bioinform. 2009 |
Bioinformatics and computational biology › network bioinformatics › biological network analysis › network analysis
network centrality |
0.1 | 1 | 2009 | Analyzing biological network parameters with CentiScaPe · Bioinform. 2009 |
Methods — techniques the papers use, named apart from their topics
graph theory · 0.1boolean logic · 0.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2009 | Analyzing biological network parameters with CentiScaPeabstractSUMMARY: The increasing availability of large network datasets along with the progresses in experimental high-throughput technologies have prompted the need for tools allowing easy integration of experimental data with data derived form network computational analysis. In order to enrich experimental data with network topological parameters, we have developed the Cytoscape plug-in CentiScaPe. The plug-in computes several network centrality parameters and allows the user to analyze existing relationships between experimental data provided by the users and node centrality values computed by the plug-in. CentiScaPe allows identifying network nodes that are relevant from both experimental and topological viewpoints. CentiScaPe also provides a Boolean logic-based tool that allows easy characterization of nodes whose topological relevance depends on more than one centrality. Finally, different graphic outputs and the included description of biological significance for each computed centrality facilitate the analysis by the end users not expert in graph theory, thus allowing easy node categorization and experimental prioritization. AVAILABILITY: CentiScaPe can be downloaded via the Cytoscape web site: http://chianti.ucsd.edu/cyto_web/plugins/index.php. Tutorial, centrality descriptions and example data are available at: http://profs.sci.univr.it/ approximately scardoni/centiscape/centiscapepage.php CONTACT: [email protected] SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. Giovanni Scardoni, Michele Petterlini, Carlo Laudanna |
Bioinform. | 2 |
| 2007 | Psim: a simulator for biomolecular dynamics based on P systemsabstractMetabolic P systems, shortly MP systems, are a special class of P systems, introduced for expressing biological metabolism. Their dynamics is computed by metabolic algorithms which transform populations of objects according to a mass partition principle, based on suitable generalizations of chemical laws. The basic principles of MP systems are discussed and Psim, a simulation tool we developed in this context to discretely compute systems dynamics, is highlighted in its basic features. A concrete example is reported as well including a real simulation experiment by means of Psim. Luca Bianco, Vincenzo Manca, Luca Marchetti, Michele Petterlini |
IEEE Congress on Evolutionary Computation | 4 |