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- Alexis Lamiable, Dominique Barth, Alain Denise, Franck Quessette, Sandrine Vial, Eric Westhof
- Computational Biology and Chemistry
- 2012

We present an algorithm for automatically predicting the topological family of any RNA three-way junction, given only the information from the secondary structure: the sequence and the Watson-Crick pairings. The parameters of the algorithm have been determined on a data set of 33 three-way junctions whose 3D conformation is known. We applied the algorithm… (More)

- Tugrul Dayar, Franck Quessette
- SIAM J. Matrix Analysis Applications
- 2002

A special class of homogeneous continuous-time quasi-birth-and-death (QBD) Markov chains (MCs) which possess level-geometric (LG) stationary distribution is considered. Assuming that the stationary vector is partitioned by levels into subvectors, in an LG distribution all stationary subvectors beyond a finite level number are multiples of each other.… (More)

- Jean-Michel Fourneau, Franck Quessette
- ISCIS
- 2006

The Stochastic Automata Networks formalism is an attractive technique to model complex systems with interacting components. Each component of the system is modelled by a single automaton; interactions between components are modelled by labels on the arcs which may represent synchronization and state-dependent transitions. Every automaton is associated with… (More)

- Jean-Michel Fourneau, Leïla Kloul, Franck Quessette
- MASCOTS
- 1995

We consider multiple class G-networks of processor sharing queues with negative customers which destroy all the customers in a queue. We prove that these networks have a product form solution for steady-state distribution. These networks may have some applications in reliability or performability as the negative customers may clearly model breakdown of… (More)

- Jean-Michel Fourneau, Mathieu Le Coz, Nihal Pekergin, Franck Quessette
- MASCOTS
- 2003

We present X-Bounds, a new tool to implement a methodology based on stochastic ordering, algorithmic derivation of simpler Markov chains and numerical analysis of these chains. The performance indices defined by reward functions are stochastically bounded by reward functions computed on much simpler or smaller Markov chains obtained after aggregation or… (More)

- Alexis Lamiable, Franck Quessette, Sandrine Vial, Dominique Barth, Alain Denise
- IEEE/ACM Transactions on Computational Biology…
- 2013

We present a new approach for the prediction of the coarse-grain 3D structure of RNA molecules. We model a molecule as being made of helices and junctions. Those junctions are classified into topological families that determine their preferred 3D shapes. All the parts of the molecule are then allowed to establish long-distance contacts that induce a 3D… (More)

- J . M . Fourneau, L . Kloul, Lynda Mokdad, Franck Quessette
- 1994

We present a new performance evaluation tool based on the analysis of large Markov chains and Stochastic Automata Networks. Using some graph theoretical arguments, we show how to systematically perform state reduction. The graph properties can be checked easily because we take advantage of the tensorial construction of the Markov chain from the Stochastic… (More)

- Jean-Michel Fourneau, Leïla Kloul, Franck Quessette
- Perform. Eval.
- 2000

We present a new type of multiclass generalized networks of queues with a steady-state product form solution. At its arrival into a queue, a negative customer (or a signal) starts an iteration. At each step of the iteration, a customer is deleted according to a probability which may depend on the type of customer. The iteration stops when the deletion… (More)