Difference between revisions of "Phylogenetic Trees"
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The project focus on the study, implementation, comparison and analysis of different statistical inference techniques for phylogenetic trees. | The project focus on the study, implementation, comparison and analysis of different statistical inference techniques for phylogenetic trees. | ||
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The framework used is '''[http://www.r-project.org/ R]''', a software environment for statistical computing which already provide a set of classes implementhing those phylogenetic inference models and methods, good enough to start. | The framework used is '''[http://www.r-project.org/ R]''', a software environment for statistical computing which already provide a set of classes implementhing those phylogenetic inference models and methods, good enough to start. | ||
| − | We already have got a very large amount of data about classified malwares (collected by a team of PoliMi researchers), so we just have to test how standard phylogenetic methods react to such | + | We already have got a very large amount of data about classified malwares (collected by a team of PoliMi researchers), so we just have to test how standard phylogenetic methods react to such an enormous group of data. |
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== Bibliography == | == Bibliography == | ||
# Joseph Felsenstein. '''Inferring Phylogenies'''. Sinauer Associates, Inc., 2004. | # Joseph Felsenstein. '''Inferring Phylogenies'''. Sinauer Associates, Inc., 2004. | ||
Revision as of 12:40, 22 March 2010
Phylogenetic Trees
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| Corresponding Proposal: | Statistical inference for phylogenetic trees |
| Coordinator: | MatteoMatteucci (matteo.matteucci@polimi.it) |
| Tutor: | LuigiMalago (malago@elet.polimi.it) |
| Collaborator: | |
| Students: | RiccardoDesantis (effetti@gmail.com) |
| Research Area: | Machine Learning |
| Research Topic: | Information Geometry, Stocastic Optimization, Evolutionary Computation |
| Start: | 2009/05/01 |
| Status: | Active |
| Level: | Bs |
| Type: | Thesis |
The project focus on the study, implementation, comparison and analysis of different statistical inference techniques for phylogenetic trees.
The aim of this project is to create a taxonomy of malicious software (aka malware), because new malwares are often related to the older ones, creating something like an evolutionary relationship between them.
The framework used is R, a software environment for statistical computing which already provide a set of classes implementhing those phylogenetic inference models and methods, good enough to start.
We already have got a very large amount of data about classified malwares (collected by a team of PoliMi researchers), so we just have to test how standard phylogenetic methods react to such an enormous group of data.
Bibliography
- Joseph Felsenstein. Inferring Phylogenies. Sinauer Associates, Inc., 2004.
- Barry G. Hall. Phylogenetic trees made easy: A How-To manual. Sinauer Associates, Inc., third edition, 2008.
- Masatoshi Nei and Sudhir Kumar. Molecular Evolution and Phylogenetics. Oxford University Press, 2000.
- Emmanuel Paradis. Analysis of Phylogenetics and Evolution with R. Springer, 2006.
- Charles Semple and Mike Steel. Phylogenetics. Oxford University Press, 2003.
