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To be held at the
Academy House
Hertogsstraat/Rue ducale 1, 1000 Brussels
Objective
Genomics gives rise to a marvelously wide range of advanced mathematical
techniques.
The organizers hope that this study day will support and/or introduce
the scientific activities going on in the area of genomics.
Genomics provides the most direct aproach to the study of new species.
Genomic series as such already contain an incredible amount of data
that refer to the state and the development of the species.
Moreover, thanks to genomics, information became available that
would never have been into reach by classical biological techniques.
This study day will deal with a number of fascinating areas on the border
of mathematics and genomics.
For example, the structure of the genome itself has strong connections with the
spacial representation, hence with spacial geometry.
The dynamics of the genome is related with mathematical dynamics while
the stochastics is crucial in the recognition of series in DNA.
However, these are only some aspects of a much broader framework in which the lectures can be placed.
Final list of invited speakers:
Program:
Registration:
Registration is free of charge, but required for practical reasons.
Please send an email to adhemar.bultheel @ cs.kuleuven.ac.be before October 1, 2003.
Organization:
- The Belgian Mathematical Society
- The National Committee for Mathematics
- The Scientific Research Network
Advanced Numerical Methods for Mathematical Modeling
Sponsors:
Contact:
Adhemar Bultheel at adhemar.bultheel @ cs.kuleuven.ac.be
Jef Teugels at jef.teugels @ wis.kuleuven.ac.be
Jef Thas at jat @ cage.ugent.be
Abstracts
David Balding:
Inferring haplotypes from genotypes
Genetic data from humans and other diploid organisms usually come in
the form of genotypes: for each individual i there is a sequence of
unordered allele pairs (Aij1,Aij2), j=1,...,J, where j indexes
chromosomal locations (loci). One allele in each pair is maternal in
origin, the other paternal, but parent-of-origin information is
usually not available. However, if the loci are close together on a
chromosome, for example multiple genetic markers within or flanking a
single gene, then many methods of analysis require haplotype data,
which amounts to ordering each allele pair so that the Aij1,
j=1,...,J, all come from the same parent of individual i. I will
briefly review algorithms and software developed by other authors
for inferring haplotype data from population samples of the genotypes
of unrelated individuals. I will also describe joint work with
Laurent Excoffier (Univ. Bern) in which we develop a novel algorithm
that is designed to perform well for larger genomic regions and/or
high levels of recombination, including recombination hot-spots.
The slides of the lecture pdf
(881 Kb)
Alessandra Carbone:
Codon bias and the space of microorganisms
Proteins are formed out of 20 amino-acids which are coded in triplets of
nucleotides, called codons. The four nucleotides (A,T,C,G) define 64 codons
used in the cell. Codons are not uniformely employed in the cell, but at
the contrary, certain codons are preferred and we speak about codon bias.
There are several kinds of codon biases and some of them are linked to
specific biological functions. Based on some simple mathematical ideas
on sequence analysis we can detect dominating codon bias in prokaryotic and
eukaryotic organisms of any kind, and define a formal framework to interpret
genomic relationships derived from entire genome sequences rather than
individual loci.
The slides of the lecture pdf
(4 Mb)
Bart De Moor:
Bioinformatics: organisms from Venus, Technology from Jupiter, Algorithms from Mars.
In this lecture we discuss datasets that are being generated by microarray
technology, which makes it possible to measure in parallel the activity
or expansion of thousands of genes simultaneously.
We discuss the basics of the technology, how to preprocess the data, and how
classical and newly developed algorithms can be used to generate insight in the
biological processes that have generated the data. Algorithms we discuss
are Principal Component Analysis, clustering techniques such as
Hierarchical Clustering and Adaptive Quality Based Clustering
and statistical sampling methods, such as Monte Carlo Markov Chains and
Gibbs Sampling. We illustrate these algorithms with several real-life cases
from diagnostics and class discovery in leukemia, functional genomics
research on the mitotic cell cycle of yeast, and motif detection in
Arabidopsis thaliana using DNA background models.
We also discuss some bioinformatics software platforms.
We end our presentation by presenting some future perspectives on the
development of bioinformatics, including some visionary discussions on how
technology, algorithms, systems biology and computational biomedicine
will evolve.
The slides of the lecture
ppt
(56 Mb)
David Rand:
Design principles behind complex circadian clocks.
I will discuss some mathematical results relating the
structure of the associated regulatory networks to the functions of
the clock. A basic problem is to understand the roles of the
interlocking positive and negative feedback loops
Shoshana J. Wodak:
Bridging the molecular and systems level views in the post-genomic era: Role of bioinformatics.
Over one hundred or so complete genomes, of species ranging from bacteria to man, have now been sequenced and many more are in the pipeline. This flow of information is changing the way in which research in all fields of biology is performed. Until recently most biochemists and molecular biologists focused on the properties of single genes and proteins involved in individual biological processes. Now, it becomes possible to study how the individual genes and gene products co-operate to build up complex cellular structures and to perform all the elaborate processes that enable cells and organisms to live and reproduce themselves. This is an enormous challenge that requires multidisciplinary efforts and new systems-level approaches, ideally grounded on molecular level understanding. Computational biology and bioinformatics have a key role to play in these new developments. This role will be illustrated with several examples from our own work.
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