Laurence Calzone

Langages formels dans la machine abstraite biochimique BIOCHAM

Le développement de langages formels pour modéliser les systèmes biologiques ouvre la voie à la conception de nouveaux outils de raisonnement automatique destinés au biologiste …

Machine Learning Biochemical Networks from Temporal Logic Properties

One central issue in systems biology is the definition of formal languages for describing complex biochemical systems and their behavior at different levels. The biochemical …

Coupling the Cell cycle and the Circadian Cycle

Cancer treatments based on the administration of medicines at different times of the day have been shown to be more efficient against malign cells and less damaging towards …

BIOCHAM: an environment for modeling biological systems and formalizing experimental knowledge

BIOCHAM (the BIOCHemical Abstract Machine) is a software environment for modeling biochemical systems. It is based on two aspects: (1) the analysis and simulation of boolean, …

Learning Transition Rules from Temporal Logic Properties

Most of the work on temporal representation issues in Machine Learning deals with the problem of learning/mining temporal patterns from a large set of temporal data. In this paper …

A Machine Learning approach to Biochemical Reaction Rules Discovery

Beyond numerical simulation, the possibility of performing symbolic computation on bio-molecular interaction networks opens the way to the design of new automated reasoning tools …

Apprentissage de règles de réactions biochimiques à partir de propriétés en logique temporelle

Machine Learning Bio-molecular Interactions from Temporal Logic Properties

With the advent of formal languages for modeling bio-molecu-lar interaction systems, the design of automated reasoning tools to assist the biologist becomes possible. The …