Networks from Genomes and Metabolomes
Vincent Moulton,
University of East Anglia –
Abstract:
In this talk we will present two unrelated methods
for constructing networks from molecular sequence data
and from metabolic profiles.
Phylogenetic networks are a generalization of
phylogenetic trees that permit the representation
of conflicting signal or alternative phylogenetic histories.
šNetworks can provide a useful tool for phylogenetic
analysis when the underlying evolutionary history
is non treelike. For example, recombination,
hybridization, and lateral gene transfer
can all lead to histories that are not adequately
represented by a single tree. In the first part
of the talk, we present some techniques for
the whole-genome scale construction of phylogenetic networks.
The second part of the talk is concerned with
reconstruction of metabolic networks. A well-studied
problem in biochemical system analysis is the
reconstruction of model parameters from metabolic profiles.
Due to the high dimensionality of this problem,
most current methods for its solution are based on heuristic
Ëalgorithms. However, such methods often produce point estimates for
parameters, with no guarantees of accuracy. Here, we
present an alternative way to solve the reconstruction
problem that is based on the mathematical theory of
interval analysis that has the advantage of providing
reliable estimates of parameters.
Date: 2005-Nov-25 Time: 15:00:00 Room: VA5 (IST)
For more information:
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OLISSIPO Summer School in Lisbon | Computational phylogenetics to analyse the evolution of cells and communities

We are happy to announce the OLISSIPO Summer School on Computational phylogenetics to analyse the evolution of cells and communities, which will be held in Lisbon, Portugal, at INESC-ID, between July 2-7, 2023.
Keynote speakers:
David Posada, University of Vigo (class)
João Alves, University of Vigo (hands-on)
Nadia El-Mabrouk, Université de Montréal (class)
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Ran Libeskind-Hadas, Claremont McKenna College (class and hands-on)
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The school covers a range of machine learning topics, from theory to practice, that are important in solving natural language processing problems arising in different application areas. It is organized jointly by Instituto Superior Técnico (IST), a leading Engineering and Science school in Portugal, the Instituto de Telecomunicações, the Instituto de Engenharia de Sistemas e Computadores, Investigação e Desenvolvimento em Lisboa (INESC-ID), the Lisbon ELLIS Unit for Learning and Intelligent Systems (LUMLIS), Unbabel, Zendesk, and IBM Research.
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