1,141 research outputs found
An immune network approach to learning qualitative models of biological pathways
ACKNOWLEDGMENT GMC is supported by the CRISP project (Combinatorial Responses In Stress Pathways) funded by the BBSRC (BB/F00513X/1) under the Systems Approaches to Biological Research (SABR) Initiative. WP and GMC are also supported by the partnership fund from dot.rural, RCUK Digital Economy research.Postprin
Using qualitative models to define sustainable management for the commons in data poor conditions
Acknowledgments This work was funded by the University of Aberdeen and Scottish Natural Heritage (SNH) and their support is gratefully acknowledged. We thank MASTS (the Marine Alliance for Science and Technology for Scotland) for their role in funding this work and B. Leyshon and F. Manson (SNH) for fruitful discussion.Peer reviewedPostprin
An integrative top-down and bottom-up qualitative model construction framework for exploration of biochemical systems
The authors would like to thank the support on this research by the CRISP project (Combinatorial Responses In Stress Pathways) funded by the BBSRC (BB/F00513X/1) under the Systems Approaches to Biological Research (SABR) Initiative.Peer reviewedPublisher PD
Qualitative System Identification from Imperfect Data
Experience in the physical sciences suggests that the only realistic means of
understanding complex systems is through the use of mathematical models.
Typically, this has come to mean the identification of quantitative models
expressed as differential equations. Quantitative modelling works best when the
structure of the model (i.e., the form of the equations) is known; and the
primary concern is one of estimating the values of the parameters in the model.
For complex biological systems, the model-structure is rarely known and the
modeler has to deal with both model-identification and parameter-estimation. In
this paper we are concerned with providing automated assistance to the first of
these problems. Specifically, we examine the identification by machine of the
structural relationships between experimentally observed variables. These
relationship will be expressed in the form of qualitative abstractions of a
quantitative model. Such qualitative models may not only provide clues to the
precise quantitative model, but also assist in understanding the essence of
that model. Our position in this paper is that background knowledge
incorporating system modelling principles can be used to constrain effectively
the set of good qualitative models. Utilising the model-identification
framework provided by Inductive Logic Programming (ILP) we present empirical
support for this position using a series of increasingly complex artificial
datasets. The results are obtained with qualitative and quantitative data
subject to varying amounts of noise and different degrees of sparsity. The
results also point to the presence of a set of qualitative states, which we
term kernel subsets, that may be necessary for a qualitative model-learner to
learn correct models. We demonstrate scalability of the method to biological
system modelling by identification of the glycolysis metabolic pathway from
data
Statistical and Comparative Phylogeography of Mexican Freshwater Taxa in Extreme Aquatic Environments
Phylogeography aims to understand the processes that underlie the distribution of genetic variation within and among closely related species. Although the means by which this goal might be achieved differ considerably from those that spawned the field some thirty years ago, the foundation and conceptual breakthroughs made by Avise are nonetheless the same and are as relevant today as they were two decades ago. Namely, patterns of neutral genetic variation among individuals carry the signature of a species’ demographic past, and the spatial and temporal environmental heterogeneity across a species’ geographic range can influence patterns of evolutionary change. Aquatic systems throughout Mexico provide unique opportunities to study phenotypic plasticity and evolution in relation to climatic and environmental selective forces. There are several unique, often isolated aquatic environments throughout Mexico that have a history of geographic isolation and reconnection. The first study presented herein shows significant mitochondrial sequence divergence was also discovered between L. megalotis populations on either side of the Sierra de San Marcos that bisects the valley of Cuatro Ciénegas and that the populations in the valley are genetically distinct from those found outside of the valley. The second study recovered signals of two divergence events in Cuatro Ciénegas for six codistributed taxa, and reveals that both events occured in the Pleistocene during periods of increased aridity suggesting that climatic effects might have played a role in these species’ divergence. The final study presents an Illumina-based high-resolution species phylogeny for Astyanax mexicanus providing added support that there are multiple origins to cave populations and further clarifying the uniqueness of the Sabinos and Rio Subterráneo caves
Gender-Inclusive Library Workgroup Report
The Gender-Inclusive Workgroup explored how VCU Libraries can better serve trans and gender-nonconforming users and staff. The group’s recommendations cover library spaces, staff, systems, services, and culture. Key recommendations include highlighting existing all-gender restrooms; building more gender-inclusive restrooms; expanding availability of menstrual products and disposal bins; continuing support for name-of-use changes in library systems; minimizing display of legal name in library systems; offering ongoing staff training in gender-inclusive language and customer service; and encouraging staff to share pronouns. The workgroup also recommends pursuing a culture of shared learning and inclusive thinking, with a reminder that gender identity is one facet of multiple intersecting identities for people in the VCU community
Analysing GCN4 Translational Control in Yeast by Stochastic Chemical Kinetics Modelling and Simulation
Peer reviewedPublisher PD
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