ERABLE Research team
European Research team in Algorithms and Biology, formaL and Experimental
- Leader : Marie-france Sagot
- Type : Project team
- Research center(s) : Grenoble
- Field : Digital Health, Biology and Earth
- Theme : Computational Biology
- Partner(s) : Université Claude Bernard (Lyon 1),Institut national des sciences appliquées de Lyon,Centrum Wiskunde & Informatica,Université de Rome la Sapienza
- Collaborator(s) : Laboratoire de Biométrie et Biologie Evolutive (LBBE) (UMR5558)
Cells are seen as the basic structural, functional and biological units of all living systems. They represent the smallest units of life that can replicate independently, and are often referred to as the building blocks of life. Living organisms are then classified into unicellular ones – this is the case of most bacteria and archea – or multicellular – this is the case of animals and plants. Actually, multicellular organisms, such as for instance human, may be seen as composed of native (human) cells, but also of extraneous cells represented by the diverse bacteria living inside the organism. The proportion in the number of the latter in relation to the number of native cells is believed to be high: this is for example of 90% in humans. Multicellular organisms have thus been described also as “superorganisms with an internal ecosystem of diverse symbiotic microbiota and parasites” (Nicholson et al, Nat Biotechnol, 22(10):1268-1274, 2004) where symbiotic means that the extraneous unicellular organisms (cells) live a close, and in this case, long-term relation both with the multicellular organisms they inhabit and among themselves. On the other hand, bacteria sometimes group into colonies of genetically identical individuals which may acquire both the ability to adhere together and to become specialised for different tasks. An example of this is the cyanobacterium Anabaena sphaerica who may group to form filaments of differentiated cells, some – the heterocysts – specialised for nitrogen fixation while the others are capable of photosynthesis. Such filaments have been seen as first examples of multicellular patterning.
At its extreme, one could then see life as one collection, or a collection of collections of genetically identical or distinct self-replicating cells who interact, sometimes closely and for long periods of evolutionary time, with same or distinct functional objectives. The interaction may be at equilibrium, meaning that it is beneficial or neutral to all, or it may be unstable meaning that the interaction may be or become at some time beneficial only to some and detrimental to other cells or collections of cells. The interaction may involve other living systems, or systems that have been described as being at the edge of life such as viruses, or else genetic or inorganic material such as, respectively, transposable elements and chemical compounds.
The application goal of ERABLE (European Research team in Algorithms and Biology, formaL and Experimental) is, through the use of mathematical models and algorithms, to better understand such close and often persistent interactions, with a longer term objective of becoming 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.
This goal requires to identify who are the partners in a closely interacting community, who is interacting with whom, how and by which means. Any model is a simplification of reality, but once selected, the algorithms to explore such model should address questions that are precisely defined and, whenever possible, be exact in the answer as well as exhaustive when more than one exists in order to guarantee an accurate interpretation of the results within the given model.
This fits well the mathematical and computational expertise of the team, and drives the methodological goal of ERABLE which will be to substantially and systematically contribute to the field of exact enumeration algorithms for problems that most often will be hard in terms of their complexity, and as such to also contribute to the field of combinatorics in as much as this may help in enlarging the scope of application of exact methods.
The key objective will be, by constantly crossing ideas from different models and types of approaches, to look for and to infer “patterns”, as simple and general as possible, either at the level of the biological application or in terms of methodology. This objective will drive which biological systems are considered, and also which models and in which order, going from simple discrete ones first on to more complex continuous models later if necessary and possible.
International and industrial relations
- Instituto de Matemática e Estatística, Universidade de São Paulo, São Paulo, Brazil
- Departamento de Computação e Estatística, Universidade Federal de Mato Grosso do Sul, Campo Grande, Brazil
- Laboratório Nacional de Computação Científica, Ministério da Ciência e da Teconologia, Petrópolis, Rio de Janeiro, Brazil
- Center for Mathematical Modeling (CMM), University of Chile at Santiago, Chile
- Knowledge Discovery and Bioinformatics Group, INESC-ID, Instituto Superior Técnico, Lisbon, Portugal
There are other groups from Brazil with whom ERABLE maintains a collaboration, including through shared students who have been representing the main pool of PhD students and postdocs of the previous Project-Team BAMBOO since 2001.
- Fabien Jourdan from the Xenotype Laboratory at the Inra-Toulouse who is an expert on (mainly but not only) metabolic network reconstruction, analysis, and visualisation.
- The GenScale Team at Inria that has an expertise on NGS and parallel algorithms, data structures, and genomics and evolution more in general.
- Biologists with whom members of BAMBOO have been interacting in the past, notably the groups of Roderic Guigó and Toni Galbadón at Barcelona in Spain, and of Andrés Moya at Valencia in Spain.
- Catherine Matias (University of Évry), Etienne Birmelé (University of Paris 5), and more generally the French Statistics for Systems Biology (SSB) group mainly attached to the MIA Department of Inra.
- Steven Kelk (University of Maastricht) who is an expert on phylogenetic networks, a topic closely related to co-phylogeny.
- Frank Bruggeman and Bas Teusink (Free University of Amsterdam) who are prominent system biologists with a strong understanding of mathematical modelling.
- Solon Pissis, Algorithms and Bioinformatics group, King’s College, London, UK, who works on string algorithms.
- Lodewyk Wessels, the Netherlands Cancer Institute; Didier Auboeuf, Centre National de Cancérologie of Lyon; members of the Plateforme Bio-Informatique Synergie Lyon Cancer at the Centre Léon Bérard in Lyon; all experts in cancer research.
More recent collaborations that may develop further in the future include both biology- and computation/math-oriented groups.
The main current industrial collaborators of ERABLE are:
- Bull Information Systems on NGS.
- Galileo Research, Italy on the analysis of preclinical data.
- Genostar technologies on some genome annotation problems.
- TecSinapse, Brazil, on biotechnology.
- The four industrial partners inside the FP7 KBBE BacHBerry project: Biofaction KG (Austria, research-oriented SME focusing on technology assessment, ELSI studies (ethical, legal and social issues), public dialogue, science communication, and the interaction between art and science), Evolva (Denmark, its mission is to discover and provide innovative, sustainable ingredients for health, nutrition and wellness using biosynthetic and evolutionary technologies to create and optimise small molecule compounds and their production), Chr. Hansen A/S (Denmark, global supplier of bioscience based ingredients to the food industry), and Biotempo (Portugal, specialised in the development of novel bioprocesses for the production of food ingredients).
Research teams of the same theme :
- ABS - Algorithms, Biology, Structure
- BEAGLE - Artificial Evolution and Computational Biology
- BIGS - Biology, genetics and statistics
- BONSAI - Bioinformatics and Sequence Analysis
- CAPSID - Computational Algorithms for Protein Structures and Interactions
- DYLISS - Dynamics, Logics and Inference for biological Systems and Sequences
- GENSCALE - Scalable, Optimized and Parallel Algorithms for Genomics
- IBIS - Modeling, simulation, measurement, and control of bacterial regulatory networks
- LIFEWARE - Computational systems biology and optimization
- MORPHEME - Morphologie et Images
- MOSAIC - MOrphogenesis Simulation and Analysis In siliCo
- PLEIADE - from patterns to models in computational biodiversity and biotechnology
- SERPICO - Space-timE RePresentation, Imaging and cellular dynamics of molecular COmplexes
- TAPDANCE - Theory and Practice of Nanoscale Computing Engines
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