8,528 research outputs found
Integrating heterogeneous knowledges for understanding biological behaviors: a probabilistic approach
Despite recent molecular technique improvements, biological knowledge remains
incomplete. Reasoning on living systems hence implies to integrate
heterogeneous and partial informations. Although current investigations
successfully focus on qualitative behaviors of macromolecular networks, others
approaches show partial quantitative informations like protein concentration
variations over times. We consider that both informations, qualitative and
quantitative, have to be combined into a modeling method to provide a better
understanding of the biological system. We propose here such a method using a
probabilistic-like approach. After its exhaustive description, we illustrate
its advantages by modeling the carbon starvation response in Escherichia coli.
In this purpose, we build an original qualitative model based on available
observations. After the formal verification of its qualitative properties, the
probabilistic model shows quantitative results corresponding to biological
expectations which confirm the interest of our probabilistic approach.Comment: 10 page
Nonmonotonic Probabilistic Logics between Model-Theoretic Probabilistic Logic and Probabilistic Logic under Coherence
Recently, it has been shown that probabilistic entailment under coherence is
weaker than model-theoretic probabilistic entailment. Moreover, probabilistic
entailment under coherence is a generalization of default entailment in System
P. In this paper, we continue this line of research by presenting probabilistic
generalizations of more sophisticated notions of classical default entailment
that lie between model-theoretic probabilistic entailment and probabilistic
entailment under coherence. That is, the new formalisms properly generalize
their counterparts in classical default reasoning, they are weaker than
model-theoretic probabilistic entailment, and they are stronger than
probabilistic entailment under coherence. The new formalisms are useful
especially for handling probabilistic inconsistencies related to conditioning
on zero events. They can also be applied for probabilistic belief revision.
More generally, in the same spirit as a similar previous paper, this paper
sheds light on exciting new formalisms for probabilistic reasoning beyond the
well-known standard ones.Comment: 10 pages; in Proceedings of the 9th International Workshop on
Non-Monotonic Reasoning (NMR-2002), Special Session on Uncertainty Frameworks
in Nonmonotonic Reasoning, pages 265-274, Toulouse, France, April 200
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