People
| Projects | Data&Software
| Stages | Seminars
| Publications
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Equipe
de Génomique Analytique
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Mathematical and Algorithmic Approaches to Systems Biology Our group is working on various problems
connected with the functioning and evolution of biological systems. In
particular, we are interested in the systemic description of genetic and
biochemical networks, such as those responsible for gene regulation. Our
approach is based on quantitative experimental measurements and theoretical
modeling. We use mathematical tools (mainly from statistics and combinatorics)
and algorithmic tools to study basic principles of cellular functioning
starting from genomic data. |
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Projects
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1. Sequence evolution in microbial organisms: essential genes, synthetic biology and genome evolution. | |||
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2. Sequence evolution in eukaryotic organisms: detection of regulatory signals in sequences. | ||||
We are interested to search for other regulatory motifs
in intergenic regions of several genomes of the Plasmodium family.
The statistical and combinatorial analysis that we develop is based on
a comparative approach of genomic sequences. More precisely, we are interested
to study 3'UTR regions, 5'UTR regions and promoter regions of P. falciparum.
The recent discovery of specific motifs in mammalian genomes characterizing
the three types of regions above suggests to compare the four available
Plasmodium genomes to detect potential specific signals. |
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3. Protein evolution: detection of distantly related proteins | ||||
We propose to develop two novel computational approaches to annotation based on sequence and structural homology search. We have recently developed a new tool, named PHYBAL, for an optimal alignment of pairs of distantly related proteins as well as some numerical criteria for the selection, within large databases, of pairs of proteins susceptible to share the same structure. The method allows us to align protein pairs with very weak sequence identity (10-15%). The extension of the alignment tool to multiple alignment and the integration of suitable selecting criteria within the alignment tool will provide a way to realize a systematic large scale search of homologous proteins for genomes that demonstrated difficult annotation. The second bioinformatics approach takes advantage of the new amount of available protein structure information and of the structure-function relationship. We propose to adapt one of the existing threading methods, FROST, to local structural information coming from specific protein families. This information is expected to refine the outcomes nowadays attainable with FROST. Affinity between a sequence and its fold will be established through adequate scores, and selection criteria will be developed. We want to apply the methods to the detection of transcription factors in Plasmodium and of human glycosilase proteins. The predictons will be checked by two experimental biologists that collaborate with us. Both methodologies have general scope and multiple potential applications, other than the one we propose. As a result of a better alignment, the reconstruction of phylogenetic trees might result more trustful. J.Baussand, C.Deremble,
A.Carbone, Periodic distributions of hydrophobic amino acids allows to
define fundamental building blocks to align distantly related proteins,
Proteins: Structure, Function and Bioinformatics, 67(3):695-708,
2007. |
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3. Protein evolution: detection of functional sites on protein complexes and detection of potential protein partners. | ||||
The Joint Evolutionary Trees (JET) method
detects protein interfaces, a core of residues involved in the folding
process, residues susceptible to be relevant to site-directed mutagenesis
and to molecular recognition. JET is a fully automatized system that we
recently developed at the lab and it can be applied to a large scale analysis
of protein interfaces. This research constitutes now a part of the DECRYPTHON
project and it will be coupled with a docking algorithm for a large scale
detection of potential protein partners. We shall be particularly focused
in protein partners involved in neuromuscular deseases. We aim to construct
a new database of information on functionally interacting proteins. Further
extensions will include studies of protein binding sites involved in interactions
with DNA or ligands (such as drugs). This will be of significant medical
interest since, while it is now feasible to design a small molecule to
inhibit or enhance the binding of a given molecule to a given partner,
it is much more difficult to understand how that same small molecule could
directly or indirectly influence other existing interactions. The approach
proposed in this project combines evolutionary information (how evolution
modified proteins to enhance their function) and molecular modeling (computational
determination of the relative position of two interacting protein partners)
to identify potential interactions. A description of the project with an update on the current status can be found here. |
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4. Protein evolution: detection of networks of co-evolved residues. | ||||
J.Baussand, A.Carbone,
A combinatorial approach to detect co-evolved amino-acid networks in protein
families with variable divergence, 2008. Submitted. |
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7. DNA nanotechnologies: nanoscopic aperiodic tiling in 3 dimensions. | ||||
Periodic structures self-assemblying
in 3 dimensions have been conceived and realised experimentally with DNA
molecules. We study DNA molecules that can be used to realise molecular
assembly growing as three-dimensional fractals. On a theoretical base,
the interaction between geometry and tile codying plays a key role. |
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Collaborations
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Detection and classification of protein interaction sites | |||
Biological networks François Képès Richard Madden Comparative genomics, sequence analysis and codon bias François Képès Jacques van Helden Catherine Vaquero Thierry Grange DNA Nanotechnology Ned Seeman |
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