Baobab Group
Members
Post-doc
CNRS
Tel: 04 72 44 81 42
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Doctorante
INRIA
![](https://lbbe.univ-lyon1.fr/sites/default/files/styles/img__220x220__crop_main/public/media/directory_people/photo/DarmonS.jpg?itok=ljjc2l3-)
Doctorant
UCBL
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Ingénieur de recherche
INRIA
Tel: 04 72 44 81 42
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Maître de conférences
UCBL
Tel: 33 04 72 43 15 52
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Maître de conférences
UCBL
Tel: 04 72 43 15 52
![](https://lbbe.univ-lyon1.fr/sites/default/files/styles/img__220x220__crop_main/public/media/directory_people/photo/PeresS.jpg?itok=fi8Vla5f)
Professeur des universités
UCBL
Tel: 04 72 44 81 42
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Technicienne
INRIA
Tel: 04 72 44 81 54
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Directrice de recherche
INRIA
Tel: 33 04 72 44 82 38
![](https://lbbe.univ-lyon1.fr/sites/default/files/styles/img__220x220__crop_main/public/media/directory_people/photo/SiharathC.jpg?itok=ZREuT6sq)
Doctorante
UCBL
![baobab team](https://lbbe.univ-lyon1.fr/sites/default/files/styles/img__320x240__crop_main/public/media/images/baobab-team3.jpeg?itok=Hi4wVejN)
Baobab is a French research team of the Laboratoire de Biométrie et Biologie Évolutive, and at the same time represents the core of a European research team of Inria called Erable. Besides the members of Baobab, Erable has thus members in three institutions in Italy (Sapienza University of Rome, Luiss University, and University of Pisa) and two institutions in the Netherlands (CWI and Free University of Amsterdam).
Baobab has two main sets of research goals that currently cover four axes:
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Goals:
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The first is related to the original areas of expertise of the team, namely combinatorial and statistical modelling and algorithms, although more recently the team has also been joined by members that come from biology including experimental.
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The second set of goals concern its main Life Science interest which is to better understand interactions between living systems and their environment. This includes close and often persistent interactions between two living systems (symbiosis), interactions between living systems and viruses, and interactions between living systems and chemical compounds.
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Axes:
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(pan)genomics and transcriptomics in general,
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metabolism and (post)transcriptional regulation,
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(co)evolution
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health in general, of living systems and environmental.
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A longer objective of the team is to become able in some cases to suggest the means of controlling for or of re-establishing equilibrium in an interacting community by acting on its environment or on its players, how they play and who plays.
Two major steps are constantly involved in the research done by the team: a first one of modelling (i.e. translating) a Life Science problem into a mathematical one, and a second of algorithm analysis and design. The algorithms developed are then applied to the questions of interest in Life Science using data from the literature or from collaborators. More recently, thanks to the recruitment of young researchers (PhD students and postdocs) in biology, the team has become able to start doing experiments and producing data or validating some of the results obtained on its own.
From a methodological point of view, the main characteristic of the team is to consider that, once a model is selected, the algorithms to explore such model should, whenever possible, be exact in the answer provided as well as exhaustive when more than one exists for a more accurate interpretation of the results. More recently, the team has become interested in exploring the interface between exact algorithms on one hand, and probabilistic or statistical ones on the other such as used in machine learning approaches. More in particular, the team is interested in investigating an area of research called “interpretable machine learning” that has been developing more recently and its potential relations with exact, combinatorial approaches.
Besides being at the core of a European team, Baobab has a number of other collaborations at the international level.
Baobab is also strongly involved in teaching at the University of Lyon and Insa-Lyon, well as in other research institutions in Europe, directly or through the members of Erable that are not in France.
For more information, you may also visit the site of the Inria team Erable here: http://team.inria.fr/erable/en/.
Publications
Display of 271 to 293 publications on 293 in total
A basis of tiling motifs for generating repeated patterns and its complexity for higher quorum
International Symposium on Mathematical Foundations of Computer Science 2003 . 2747 : 622-632
Conference paper
see the publicationOrphan gene finding - An exon assembly approach
Theoretical Computer Science . 290 ( 1 ) : 1407-1431
Journal article
see the publicationFurther thoughts on the syntenic distance between genomes
Algorithmica . 34 : 157-180
Journal article
see the publicationGene finding in eukaryotes
Cloning and expression technologies . : 27-43
Book chapter
see the publicationCurrent methods of gene prediction their strengths and weaknesses
Nucleic Acids Research . 30 : 4103-4117
Journal article
see the publicationOccurrence probability of structured motifs in random sequences
Journal of Computational Biology . 9 ( 6 ) : 761-773
Journal article
see the publicationAlgorithms for extracting structured motifs using a suffix tree with application to promoter and regulatory site consensus identification
Journal of Computational Biology . 7 ( 1 ) : 345-360
Journal article
see the publicationSome approximation results for the maximum agreement forest problem
Approximation, Randomization and Combinatorial Optimization: Algorithms and Techniques (APPROX RANDOM 2001) . 2129 : 159-169
Conference paper
see the publicationInfering regulatory elements from a whole genome. An application to the analysis of genome of $\itemize{Helicobacter Pylori}$ $\sigma_{80}$ family of promoter signals
Journal of Molecular Biology . 297 ( 1 ) : 335-353
Journal article
see the publicationInferring regulatory elements from a whole genome. An application to the analysis of the genome of Helicobacter pylori sigma 80 family of promoter signals
Journal of Molecular Biology . 297 : 335-353
Journal article
see the publicationAlgorithms for extracting structured motifs using a suffix tree with application to promoter and regulatory site consensus identification
Journal of Computational Biology . 7 : 345-360
Journal article
see the publicationPromoter sequences and algorithmical methods for identifying them
Research in Microbiology . 150 : 779-799
Journal article
see the publicationIdentifying satellites and periodic repetitions in biological sequences
Journal of Computational Biology . 5 : 539-554
Journal article
see the publicationSpelling Approximate Repeated or Common Motifs Using a Suffix Tree
incollection . 1380 : 374-390
Journal article
see the publicationFlexible Identification of Structural Objects in Nucleic Acid Sequences: Palindromes Mirror Repeats Pseudoknots and Triple Helices
Annual Symposium on Combinatorial Pattern Matching (CPM) . 1264 : 224-246
Conference paper
see the publicationMultiple sequence comparison - A peptide matching approach
Theoretical Computer Science . 180 ( 1-2 ) : 115--137
Journal article
see the publicationA Double Combinatorial Approach to Discovering Patterns in Biological Sequences
incollection . 1075 : 186-208
Journal article
see the publicationSearching for repeated words in a text allowing for mismatches and gaps
incollection . -- : 87-100
Journal article
see the publicationFinding flexible patterns in a text - An application to 3D matching
Computer Applications in the Biosciences . 11 : 59-70
Journal article
see the publicationMultiple Sequence Comparison:A Peptide Matching Approach
incollection . 937 : 366-385
Journal article
see the publication