411,878 research outputs found
A Survey on Continuous Time Computations
We provide an overview of theories of continuous time computation. These
theories allow us to understand both the hardness of questions related to
continuous time dynamical systems and the computational power of continuous
time analog models. We survey the existing models, summarizing results, and
point to relevant references in the literature
A guided tour of asynchronous cellular automata
Research on asynchronous cellular automata has received a great amount of
attention these last years and has turned to a thriving field. We survey the
recent research that has been carried out on this topic and present a wide
state of the art where computing and modelling issues are both represented.Comment: To appear in the Journal of Cellular Automat
A note on the shortest common superstring of NGS reads
The Shortest Superstring Problem (SSP) consists, for a set of strings S =
{s_1,...,s_n}, to find a minimum length string that contains all s_i, 1 <= i <=
k, as substrings. This problem is proved to be NP-Complete and APX-hard.
Guaranteed approximation algorithms have been proposed, the current best ratio
being 2+11/23, which has been achieved following a long and difficult quest.
However, SSP is highly used in practice on next generation sequencing (NGS)
data, which plays an increasingly important role in sequencing. In this note,
we show that the SSP approximation ratio can be improved on NGS reads by
assuming specific characteristics of NGS data that are experimentally verified
on a very large sampling set
Abstract State Machines 1988-1998: Commented ASM Bibliography
An annotated bibliography of papers which deal with or use Abstract State
Machines (ASMs), as of January 1998.Comment: Also maintained as a BibTeX file at http://www.eecs.umich.edu/gasm
Flux Analysis in Process Models via Causality
We present an approach for flux analysis in process algebra models of
biological systems. We perceive flux as the flow of resources in stochastic
simulations. We resort to an established correspondence between event
structures, a broadly recognised model of concurrency, and state transitions of
process models, seen as Petri nets. We show that we can this way extract the
causal resource dependencies in simulations between individual state
transitions as partial orders of events. We propose transformations on the
partial orders that provide means for further analysis, and introduce a
software tool, which implements these ideas. By means of an example of a
published model of the Rho GTP-binding proteins, we argue that this approach
can provide the substitute for flux analysis techniques on ordinary
differential equation models within the stochastic setting of process algebras
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