Baobab Group

Members

baobab team

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:

  • Goals:

    • 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.

    • 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.

  • Axes:

    • (pan)genomics and transcriptomics in general,

    • metabolism and (post)transcriptional regulation,

    • (co)evolution

    • health in general, of living systems and environmental.

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 300 publications on 308 in total

Perfect sorting by reversals

M.-F. Sagot, Eric Tannier

International Computing and Combinatorics Conference . 3595 : 42-51

DOI: 10.1007/11533719_7

Conference paper

see the publication

A new distance for high level RNA secondary structure comparison

Julien Allali, Marie-France Sagot

IEEE/ACM Transactions on Computational Biology and Bioinformatics . 2 : 3--14

Journal article

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Bases of motifs for generating repeated patterns with wild cards

Nadia Pisanti, Maxime Crochemore, Roberto Grossi, Marie-France Sagot

IEEE/ACM Transactions on Computational Biology and Bioinformatics . 2 : 40-50

DOI: 10.1109/TCBB.2005.5

Journal article

see the publication

A first approach to finding common motifs with gaps,

Costas Iliopoulos, J. Mchugh, Pierre Peterlongo, Nadia Pisanti, W. Rytter, Marie-France Sagot

International Journal of Foundations of Computer Science . 16 ( 6 ) : 1145--1155

Journal article

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Efficient Extraction of Structured Motifs Using Box-links

A. Carvalho, A.T. Freitas, A.L. Oliveira, M.-F. Sagot

International Symposium on String Processing and Information Retrieval : SPIRE . 3246 : 267-268

DOI: 10.1007/978-3-540-30213-1_37

Conference paper

see the publication

A first approach to finding common motifs with Gaps

Costas S. Iliopoulos, James Mchugh, Pierre Peterlongo, Nadia Pisanti, Wojciech Rytter, Marie-France Sagot

Prague Stringology Conference 2004 . : 88-97

Conference paper

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A parallel algorithm for the extraction of structured motifs

A. Carvalho, A.T. Freitas, A.L. Oliveira, M.-F. Sagot

ACM Symposium on Applied Computing . -- : 147-153

Conference paper

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The at-most $k$-deep factor tree

Julien Allali, Marie-France Sagot

Report

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Motifs in Sequences: Localization and Extraction

Maxime Crochemore, Marie-France Sagot

Compact Handbook of Computational Biology . : 47-97

Book chapter

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Novel tree edit operations for RNA secondary structure comparison

Julien Allali, Marie-France Sagot

Workshop on Algorithms in Bioinformatics 2004 . 3240 : 412--425

DOI: 10.1007/978-3-540-30219-3_35

Conference paper

see the publication

Sorting by reversals in subquadratic time

Eric Tannier, Marie-France Sagot

Report

see the publication

Longest repeated motif with a block of don't cares

Maxime Crochemore, Costas S. Iliopoulos, Manal Mohamed, Marie-France Sagot

6th Latin American Theoretical Informatics (LATIN'04) . 2976 : 271-278

DOI: 10.1007/978-3-540-24698-5_31

Conference paper

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Contribution of Computational Tree Logic to Biological Regulatory Networks: Example from Pseudomonas Aeruginosa

Sabine Peres, Comet Jean-Paul

Lecture Notes in Computer Sciences . 2602 : 47-56

DOI: 10.1007/3-540-36481-1_5

Journal article

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A basis of tiling motifs for generating repeated patterns and its complexity for higher quorum

Nadia Pisanti, Maxime Crochemore, Roberto Grossi, Marie-France Sagot

International Symposium on Mathematical Foundations of Computer Science 2003 . 2747 : 622-632

DOI: 10.1007/978-3-540-45138-9_56

Conference paper

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Orphan gene finding - An exon assembly approach

Philippe Blayo, Pierre Rouzé, Marie-France Sagot

Theoretical Computer Science . 290 ( 1 ) : 1407-1431

Journal article

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Pattern inference under many guises

M.-F. Sagot, Y. Wakabayashi

incollection . -- : 245-288

Journal article

see the publication

Further thoughts on the syntenic distance between genomes

N. Pisanti, M.-F. Sagot

Algorithmica . 34 : 157-180

Journal article

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Gene finding in eukaryotes

C. Mathé, Thomas Schiex, Pierre Rouzé, Philippe Blayo, Marie-France Sagot

Cloning and expression technologies . : 27-43

Book chapter

see the publication

A Basis for Repeated Motifs in Pattern Discovery and Text Mining

Nadia Pisanti, Maxime Crochemore, Roberto Grossi, Marie-France Sagot

Report

see the publication

Gene finding in eukaryotes

C. Mathé, Thomas Schiex, P. Rouzé, P. Blayo, M.-F. Sagot

incollection . -- : 27-43

Journal article

see the publication

Current methods of gene prediction their strengths and weaknesses

C. Mathé, M.-F. Sagot, Thomas Schiex, P. Rouzé

Nucleic Acids Research . 30 : 4103-4117

Journal article

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Occurrence probability of structured motifs in random sequences

S. Robin, J.J. Daudin, H. Richard, M.-F. Sagot, S. Schbath

Journal of Computational Biology . 9 ( 6 ) : 761-773

DOI: 10.1089/10665270260518254

Journal article

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Algorithms for extracting structured motifs using a suffix tree with application to promoter and regulatory site consensus identification

Laurent Marsan, Marie-France Sagot

Journal of Computational Biology . 7 ( 1 ) : 345-360

Journal article

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Some approximation results for the maximum agreement forest problem

E. M. Rodrigues, Marie-France Sagot, Y. Wakabayashi

Approximation, Randomization and Combinatorial Optimization: Algorithms and Techniques (APPROX RANDOM 2001) . 2129 : 159-169

Conference paper

see the publication

Infering regulatory elements from a whole genome. An application to the analysis of genome of $\itemize{Helicobacter Pylori}$ $\sigma_{80}$ family of promoter signals

A. Vanet, Laurent Marsan, A. Labigne, Marie-France Sagot

Journal of Molecular Biology . 297 ( 1 ) : 335-353

Journal article

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Inferring regulatory elements from a whole genome. An application to the analysis of the genome of Helicobacter pylori sigma 80 family of promoter signals

A. Vanet, L. Marsan, A. Labigne, M.-F. Sagot

Journal of Molecular Biology . 297 : 335-353

Journal article

see the publication

Algorithms for extracting structured motifs using a suffix tree with application to promoter and regulatory site consensus identification

L. Marsan, M.-F. Sagot

Journal of Computational Biology . 7 : 345-360

Journal article

see the publication

Promoter sequences and algorithmical methods for identifying them

A. Vanet, L. Marsan, M.-F. Sagot

Research in Microbiology . 150 : 779-799

Journal article

see the publication