4,191 research outputs found
10271 Abstracts Collection -- Verification over discrete-continuous boundaries
From 4 July 2010 to 9 July 2010, the Dagstuhl Seminar 10271
``Verification over discrete-continuous boundaries\u27\u27
was held in Schloss Dagstuhl~--~Leibniz Center for Informatics.
During the seminar, several participants presented their current
research, and ongoing work and open problems were discussed. Abstracts of
the presentations given during the seminar as well as abstracts of
seminar results and ideas are put together in this paper. The first section
describes the seminar topics and goals in general.
Links to extended abstracts or full papers are provided, if available
Computational Logic for Biomedicine and Neurosciences
We advocate here the use of computational logic for systems biology, as a
\emph{unified and safe} framework well suited for both modeling the dynamic
behaviour of biological systems, expressing properties of them, and verifying
these properties. The potential candidate logics should have a traditional
proof theoretic pedigree (including either induction, or a sequent calculus
presentation enjoying cut-elimination and focusing), and should come with
certified proof tools. Beyond providing a reliable framework, this allows the
correct encodings of our biological systems. % For systems biology in general
and biomedicine in particular, we have so far, for the modeling part, three
candidate logics: all based on linear logic. The studied properties and their
proofs are formalized in a very expressive (non linear) inductive logic: the
Calculus of Inductive Constructions (CIC). The examples we have considered so
far are relatively simple ones; however, all coming with formal semi-automatic
proofs in the Coq system, which implements CIC. In neuroscience, we are
directly using CIC and Coq, to model neurons and some simple neuronal circuits
and prove some of their dynamic properties. % In biomedicine, the study of
multi omic pathway interactions, together with clinical and electronic health
record data should help in drug discovery and disease diagnosis. Future work
includes using more automatic provers. This should enable us to specify and
study more realistic examples, and in the long term to provide a system for
disease diagnosis and therapy prognosis
GUBS, a Behavior-based Language for Open System Dedicated to Synthetic Biology
In this article, we propose a domain specific language, GUBS (Genomic Unified
Behavior Specification), dedicated to the behavioral specification of synthetic
biological devices, viewed as discrete open dynamical systems. GUBS is a
rule-based declarative language. By contrast to a closed system, a program is
always a partial description of the behavior of the system. The semantics of
the language accounts the existence of some hidden non-specified actions
possibly altering the behavior of the programmed device. The compilation
framework follows a scheme similar to automatic theorem proving, aiming at
improving synthetic biological design safety.Comment: In Proceedings MeCBIC 2012, arXiv:1211.347
Algebra, coalgebra, and minimization in polynomial differential equations
We consider reasoning and minimization in systems of polynomial ordinary
differential equations (ode's). The ring of multivariate polynomials is
employed as a syntax for denoting system behaviours. We endow this set with a
transition system structure based on the concept of Lie-derivative, thus
inducing a notion of L-bisimulation. We prove that two states (variables) are
L-bisimilar if and only if they correspond to the same solution in the ode's
system. We then characterize L-bisimilarity algebraically, in terms of certain
ideals in the polynomial ring that are invariant under Lie-derivation. This
characterization allows us to develop a complete algorithm, based on building
an ascending chain of ideals, for computing the largest L-bisimulation
containing all valid identities that are instances of a user-specified
template. A specific largest L-bisimulation can be used to build a reduced
system of ode's, equivalent to the original one, but minimal among all those
obtainable by linear aggregation of the original equations. A computationally
less demanding approximate reduction and linearization technique is also
proposed.Comment: 27 pages, extended and revised version of FOSSACS 2017 pape
Under-approximating Cut Sets for Reachability in Large Scale Automata Networks
In the scope of discrete finite-state models of interacting components, we
present a novel algorithm for identifying sets of local states of components
whose activity is necessary for the reachability of a given local state. If all
the local states from such a set are disabled in the model, the concerned
reachability is impossible. Those sets are referred to as cut sets and are
computed from a particular abstract causality structure, so-called Graph of
Local Causality, inspired from previous work and generalised here to finite
automata networks. The extracted sets of local states form an
under-approximation of the complete minimal cut sets of the dynamics: there may
exist smaller or additional cut sets for the given reachability. Applied to
qualitative models of biological systems, such cut sets provide potential
therapeutic targets that are proven to prevent molecules of interest to become
active, up to the correctness of the model. Our new method makes tractable the
formal analysis of very large scale networks, as illustrated by the computation
of cut sets within a Boolean model of biological pathways interactions
gathering more than 9000 components
The 1991 3rd NASA Symposium on VLSI Design
Papers from the symposium are presented from the following sessions: (1) featured presentations 1; (2) very large scale integration (VLSI) circuit design; (3) VLSI architecture 1; (4) featured presentations 2; (5) neural networks; (6) VLSI architectures 2; (7) featured presentations 3; (8) verification 1; (9) analog design; (10) verification 2; (11) design innovations 1; (12) asynchronous design; and (13) design innovations 2
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