3,493 research outputs found
RNeXML: a package for reading and writing richly annotated phylogenetic, character, and trait data in R
NeXML is a powerful and extensible exchange standard recently proposed to
better meet the expanding needs for phylogenetic data and metadata sharing.
Here we present the RNeXML package, which provides users of the R programming
language with easy-to-use tools for reading and writing NeXML documents,
including rich metadata, in a way that interfaces seamlessly with the extensive
library of phylogenetic tools already available in the R ecosystem
Issues about the Adoption of Formal Methods for Dependable Composition of Web Services
Web Services provide interoperable mechanisms for describing, locating and
invoking services over the Internet; composition further enables to build
complex services out of simpler ones for complex B2B applications. While
current studies on these topics are mostly focused - from the technical
viewpoint - on standards and protocols, this paper investigates the adoption of
formal methods, especially for composition. We logically classify and analyze
three different (but interconnected) kinds of important issues towards this
goal, namely foundations, verification and extensions. The aim of this work is
to individuate the proper questions on the adoption of formal methods for
dependable composition of Web Services, not necessarily to find the optimal
answers. Nevertheless, we still try to propose some tentative answers based on
our proposal for a composition calculus, which we hope can animate a proper
discussion
A Grammatical Inference Approach to Language-Based Anomaly Detection in XML
False-positives are a problem in anomaly-based intrusion detection systems.
To counter this issue, we discuss anomaly detection for the eXtensible Markup
Language (XML) in a language-theoretic view. We argue that many XML-based
attacks target the syntactic level, i.e. the tree structure or element content,
and syntax validation of XML documents reduces the attack surface. XML offers
so-called schemas for validation, but in real world, schemas are often
unavailable, ignored or too general. In this work-in-progress paper we describe
a grammatical inference approach to learn an automaton from example XML
documents for detecting documents with anomalous syntax.
We discuss properties and expressiveness of XML to understand limits of
learnability. Our contributions are an XML Schema compatible lexical datatype
system to abstract content in XML and an algorithm to learn visibly pushdown
automata (VPA) directly from a set of examples. The proposed algorithm does not
require the tree representation of XML, so it can process large documents or
streams. The resulting deterministic VPA then allows stream validation of
documents to recognize deviations in the underlying tree structure or
datatypes.Comment: Paper accepted at First Int. Workshop on Emerging Cyberthreats and
Countermeasures ECTCM 201
SBML models and MathSBML
MathSBML is an open-source, freely-downloadable Mathematica package that facilitates working with Systems Biology Markup Language (SBML) models. SBML is a toolneutral,computer-readable format for representing models of biochemical reaction networks, applicable to metabolic networks, cell-signaling pathways, genomic regulatory networks, and other modeling problems in systems biology that is widely supported by the systems biology community. SBML is based on XML, a standard medium for representing and transporting data that is widely supported on the internet as well as in computational biology and bioinformatics. Because SBML is tool-independent, it enables model transportability, reuse, publication and survival. In addition to MathSBML, a number of other tools that support SBML model examination and manipulation are provided on the sbml.org website, including libSBML, a C/C++ library for reading SBML models; an SBML Toolbox for MatLab; file conversion programs; an SBML model validator and visualizer; and SBML specifications and schemas. MathSBML enables SBML file import to and export from Mathematica as well as providing an API for model manipulation and simulation
A Molecular Biology Database Digest
Computational Biology or Bioinformatics has been defined as the application of mathematical
and Computer Science methods to solving problems in Molecular Biology that require large scale
data, computation, and analysis [18]. As expected, Molecular Biology databases play an essential
role in Computational Biology research and development. This paper introduces into current
Molecular Biology databases, stressing data modeling, data acquisition, data retrieval, and the
integration of Molecular Biology data from different sources. This paper is primarily intended
for an audience of computer scientists with a limited background in Biology
BSML: A Binding Schema Markup Language for Data Interchange in Problem Solving Environments (PSEs)
We describe a binding schema markup language (BSML) for describing data
interchange between scientific codes. Such a facility is an important
constituent of scientific problem solving environments (PSEs). BSML is designed
to integrate with a PSE or application composition system that views model
specification and execution as a problem of managing semistructured data. The
data interchange problem is addressed by three techniques for processing
semistructured data: validation, binding, and conversion. We present BSML and
describe its application to a PSE for wireless communications system design
Simulation of networks of spiking neurons: A review of tools and strategies
We review different aspects of the simulation of spiking neural networks. We
start by reviewing the different types of simulation strategies and algorithms
that are currently implemented. We next review the precision of those
simulation strategies, in particular in cases where plasticity depends on the
exact timing of the spikes. We overview different simulators and simulation
environments presently available (restricted to those freely available, open
source and documented). For each simulation tool, its advantages and pitfalls
are reviewed, with an aim to allow the reader to identify which simulator is
appropriate for a given task. Finally, we provide a series of benchmark
simulations of different types of networks of spiking neurons, including
Hodgkin-Huxley type, integrate-and-fire models, interacting with current-based
or conductance-based synapses, using clock-driven or event-driven integration
strategies. The same set of models are implemented on the different simulators,
and the codes are made available. The ultimate goal of this review is to
provide a resource to facilitate identifying the appropriate integration
strategy and simulation tool to use for a given modeling problem related to
spiking neural networks.Comment: 49 pages, 24 figures, 1 table; review article, Journal of
Computational Neuroscience, in press (2007
Biochemical network matching and composition
This paper looks at biochemical network matching and compositio
Review of simulating four classes of window materials for daylighting with non-standard BSDF using the simulation program Radiance
This review describes the currently available simulation models for window
material to calculate daylighting with the program "Radiance". The review is
based on four abstract and general classes of window materials, depending on
their scattering and redirecting properties (bidirectional scatter distribution
function, BSDF). It lists potential and limits of the older models and includes
the most recent additions to the software. All models are demonstrated using an
exemplary indoor scene and two typical sky conditions. It is intended as
clarification for applying window material models in project work or teaching.
The underlying algorithmic problems apply to all lighting simulation programs,
so the scenarios of materials and skies are applicable to other lighting
programs
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