Learning grammars and application to linguistic modelling of biological sequences

Keywords: Grammatical Inference, Machine Learning, Functions and Structures of Protein Sequences, DNA…


Protomata Learner infers automata to model (even heterogenous) families of protein sequences.
The current version, Protomata 2.0 can be used through a web interface on the Genouest Bioinformatics platform server.
We are working on version 3.0…

PPalign, Potts to Potts alignment of protein sequences taking into account residues coevolution, with Hugo Talibart.

PhD Students

Previous PhD Students

Funded projects

Previous funded projects:
  • IDEALG Seaweed for the future, ANR Investissements d’avenir, Biotechnology and Bioressource
  • Characterization of desaturases with Pleiade team, IPL Algae in silico
  • Grammatical inference methods in classification of amyloidogenic proteins with Politechnika Wroclawska, Polland, funded by Polish National Science Center
  • “Omics”-Line of the Chilean CIRIC-Inria Center
  • PEPS project: Characterisation and identification of viral sequences in marine metagenomes
  • ANR Biotempo: Languages, time representations and hybrid models for the analysis of incomplete models in molecular biology
  • ANR LepidOLF: Microgénomique de la sensille phéromonale d’un lépidoptère : une approche novatrice pour comprendre les mécanismes olfactifs et leur modulation
  • ANR Pelican : Competing for light in the ocean: An integrative genomic approach of the ecology, diversity and evolution of cyanobacterial pigment types in the marine environment
  • Collaboration MINCyT (ex SECyT) – INRIA with the  “Grupo de Procesamiento de Lenguaje Natural ” of Gabriel Infante-Lopez: Modélisation linguistique de séquences génomiques par apprentissage de grammaires
  • ANR Proteus: Reconnaissance de pli et repliement inverse : vers une prédiction à grande échelle des structures de protéines
  • ANR Modulome: Deciphering and modelling the structural organization of genomes

Grammatical Inference Benchmarks and Competitions

  • I gathered classical grammatical inference benchmarks in this GIB repository. Don’t hesitate to contribute with your own data sets, especially real world ones!
  • I set up the Gowachin server, a continuation of the Abbadingo One DFA learning competition, allowing to generate parametrized problems. I also co-organized Omphalos, the competition on learning context-free languages, which is now over but the data sets are still available… If you are interested in grammatical inference competitions, look at this page.

Selected publications

Primers and reviews
Looking at long distance correlations
Residues coevolution
Protein sequences and structures
Learning context-free grammars
Learning automata

Ph.D. Thesis

More complete list of publication here.
This page is updated on an irregular basis: browse HAL for new publications.

Comments are closed.