13,716 research outputs found
NEXUS/Physics: An interdisciplinary repurposing of physics for biologists
In response to increasing calls for the reform of the undergraduate science
curriculum for life science majors and pre-medical students (Bio2010,
Scientific Foundations for Future Physicians, Vision & Change), an
interdisciplinary team has created NEXUS/Physics: a repurposing of an
introductory physics curriculum for the life sciences. The curriculum interacts
strongly and supportively with introductory biology and chemistry courses taken
by life sciences students, with the goal of helping students build general,
multi-discipline scientific competencies. In order to do this, our two-semester
NEXUS/Physics course sequence is positioned as a second year course so students
will have had some exposure to basic concepts in biology and chemistry.
NEXUS/Physics stresses interdisciplinary examples and the content differs
markedly from traditional introductory physics to facilitate this. It extends
the discussion of energy to include interatomic potentials and chemical
reactions, the discussion of thermodynamics to include enthalpy and Gibbs free
energy, and includes a serious discussion of random vs. coherent motion
including diffusion. The development of instructional materials is coordinated
with careful education research. Both the new content and the results of the
research are described in a series of papers for which this paper serves as an
overview and context.Comment: 12 page
Remarks on logic for process descriptions in ontological reasoning: A Drug Interaction Ontology case study
We present some ideas on logical process descriptions, using relations from the DIO (Drug Interaction Ontology) as examples and explaining how these relations can be naturally decomposed in terms of more basic structured logical process descriptions using terms from linear logic. In our view, the process descriptions are able to clarify the usual relational descriptions of DIO. In particular, we discuss the use of logical process descriptions in proving linear logical theorems. Among the types of reasoning supported by DIO one can distinguish both (1) basic reasoning about general structures in reality and (2) the domain-specific reasoning of experts. We here propose a clarification of this important distinction between (realist) reasoning on the basis of an ontology and rule-based inferences on the basis of an expert’s view
Abstract Interpretation for Probabilistic Termination of Biological Systems
In a previous paper the authors applied the Abstract Interpretation approach
for approximating the probabilistic semantics of biological systems, modeled
specifically using the Chemical Ground Form calculus. The methodology is based
on the idea of representing a set of experiments, which differ only for the
initial concentrations, by abstracting the multiplicity of reagents present in
a solution, using intervals. In this paper, we refine the approach in order to
address probabilistic termination properties. More in details, we introduce a
refinement of the abstract LTS semantics and we abstract the probabilistic
semantics using a variant of Interval Markov Chains. The abstract probabilistic
model safely approximates a set of concrete experiments and reports
conservative lower and upper bounds for probabilistic termination
Logical operators for ontological modeling
We show that logic has more to offer to ontologists than standard first order
and modal operators. We first describe some operators of linear logic which we
believe are particularly suitable for ontological modeling, and suggest how to interpret
them within an ontological framework. After showing how they can coexist
with those of classical logic, we analyze three notions of artifact from the literature
to conclude that these linear operators allow for reducing the ontological commitment
needed for their formalization, and even simplify their logical formulation
Noise and Correlations in a Spatial Population Model with Cyclic Competition
Noise and spatial degrees of freedom characterize most ecosystems. Some
aspects of their influence on the coevolution of populations with cyclic
interspecies competition have been demonstrated in recent experiments [e.g. B.
Kerr et al., Nature {\bf 418}, 171 (2002)]. To reach a better theoretical
understanding of these phenomena, we consider a paradigmatic spatial model
where three species exhibit cyclic dominance. Using an individual-based
description, as well as stochastic partial differential and deterministic
reaction-diffusion equations, we account for stochastic fluctuations and
spatial diffusion at different levels, and show how fascinating patterns of
entangled spirals emerge. We rationalize our analysis by computing the
spatio-temporal correlation functions and provide analytical expressions for
the front velocity and the wavelength of the propagating spiral waves.Comment: 4 pages of main text, 3 color figures + 2 pages of supplementary
material (EPAPS Document). Final version for Physical Review Letter
Modelling Cell Cycle using Different Levels of Representation
Understanding the behaviour of biological systems requires a complex setting
of in vitro and in vivo experiments, which attracts high costs in terms of time
and resources. The use of mathematical models allows researchers to perform
computerised simulations of biological systems, which are called in silico
experiments, to attain important insights and predictions about the system
behaviour with a considerably lower cost. Computer visualisation is an
important part of this approach, since it provides a realistic representation
of the system behaviour. We define a formal methodology to model biological
systems using different levels of representation: a purely formal
representation, which we call molecular level, models the biochemical dynamics
of the system; visualisation-oriented representations, which we call visual
levels, provide views of the biological system at a higher level of
organisation and are equipped with the necessary spatial information to
generate the appropriate visualisation. We choose Spatial CLS, a formal
language belonging to the class of Calculi of Looping Sequences, as the
formalism for modelling all representation levels. We illustrate our approach
using the budding yeast cell cycle as a case study
Process Calculi Abstractions for Biology
Several approaches have been proposed to model biological systems by means of the formal techniques and tools available in computer science. To mention just a few of them, some representations are inspired by Petri Nets theory, and some other by stochastic processes. A most recent approach consists in interpreting the living entities as terms of process calculi where the behavior of the represented systems can be inferred by applying syntax-driven rules. A comprehensive picture of the state of the art of the process calculi approach to biological modeling is still missing. This paper goes in the direction of providing such a picture by presenting a comparative survey of the process calculi that have been used and proposed to describe the behavior of living entities. This is the preliminary version of a paper that was published in Algorithmic Bioprocesses. The original publication is available at http://www.springer.com/computer/foundations/book/978-3-540-88868-
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