556 research outputs found
Optimal trading strategies - a time series approach
Motivated by recent advances in the spectral theory of auto-covariance
matrices, we are led to revisit a reformulation of Markowitz' mean-variance
portfolio optimization approach in the time domain. In its simplest incarnation
it applies to a single traded asset and allows to find an optimal trading
strategy which - for a given return - is minimally exposed to market price
fluctuations. The model is initially investigated for a range of synthetic
price processes, taken to be either second order stationary, or to exhibit
second order stationary increments. Attention is paid to consequences of
estimating auto-covariance matrices from small finite samples, and
auto-covariance matrix cleaning strategies to mitigate against these are
investigated. Finally we apply our framework to real world data
Increased signaling entropy in cancer requires the scale-free property of protein interaction networks
One of the key characteristics of cancer cells is an increased phenotypic
plasticity, driven by underlying genetic and epigenetic perturbations. However,
at a systems-level it is unclear how these perturbations give rise to the
observed increased plasticity. Elucidating such systems-level principles is key
for an improved understanding of cancer. Recently, it has been shown that
signaling entropy, an overall measure of signaling pathway promiscuity, and
computable from integrating a sample's gene expression profile with a protein
interaction network, correlates with phenotypic plasticity and is increased in
cancer compared to normal tissue. Here we develop a computational framework for
studying the effects of network perturbations on signaling entropy. We
demonstrate that the increased signaling entropy of cancer is driven by two
factors: (i) the scale-free (or near scale-free) topology of the interaction
network, and (ii) a subtle positive correlation between differential gene
expression and node connectivity. Indeed, we show that if protein interaction
networks were random graphs, described by Poisson degree distributions, that
cancer would generally not exhibit an increased signaling entropy. In summary,
this work exposes a deep connection between cancer, signaling entropy and
interaction network topology.Comment: 20 pages, 5 figures. In Press in Sci Rep 201
Reduction Methods in Climate Dynamics -- A Brief Review
We review a range of reduction methods that have been, or may be useful for
connecting models of the Earth's climate system of differing complexity. We
particularly focus on methods where rigorous reduction is possible. We aim to
highlight the main mathematical ideas of each reduction method and also provide
several benchmark examples from climate modelling
Ein Beitrag zur Biologie der Bacterien : Inaugural-Dissertation zur Erlangung des Grades eines Doctors der Medicin / verfasst und mit Bewilligung Einer Hochverordneten Medicinischen Facultät der Kaiserlichen Universität zu Dorpat zur öffentlichen Vertheidigung bestimmt
http://tartu.ester.ee/record=b2447970~S1*es
Signalling entropy: A novel network-theoretical framework for systems analysis and interpretation of functional omic data
a b s t r a c t A key challenge in systems biology is the elucidation of the underlying principles, or fundamental laws, which determine the cellular phenotype. Understanding how these fundamental principles are altered in diseases like cancer is important for translating basic scientific knowledge into clinical advances. While significant progress is being made, with the identification of novel drug targets and treatments by means of systems biological methods, our fundamental systems level understanding of why certain treatments succeed and others fail is still lacking. We here advocate a novel methodological framework for systems analysis and interpretation of molecular omic data, which is based on statistical mechanical principles. Specifically, we propose the notion of cellular signalling entropy (or uncertainty), as a novel means of analysing and interpreting omic data, and more fundamentally, as a means of elucidating systems-level principles underlying basic biology and disease. We describe the power of signalling entropy to discriminate cells according to differentiation potential and cancer status. We further argue the case for an empirical cellular entropy-robustness correlation theorem and demonstrate its existence in cancer cell line drug sensitivity data. Specifically, we find that high signalling entropy correlates with drug resistance and further describe how entropy could be used to identify the achilles heels of cancer cells. In summary, signalling entropy is a deep and powerful concept, based on rigorous statistical mechanical principles, which, with improved data quality and coverage, will allow a much deeper understanding of the systems biological principles underlying normal and disease physiology
Transparent Integration of Opportunistic Resources into the WLCG Compute Infrastructure
The inclusion of opportunistic resources, for example from High Performance Computing (HPC) centers or cloud providers, is an important contribution to bridging the gap between existing resources and future needs by the LHC collaborations, especially for the HL-LHC era. However, the integration of these resources poses new challenges and often needs to happen in a highly dynamic manner. To enable an effective and lightweight integration of these resources, the tools COBalD and TARDIS are developed at KIT.
In this contribution we report on the infrastructure we use to dynamically offer opportunistic resources to collaborations in the World Wide LHC Computing Grid (WLCG). The core components are COBalD/TARDIS, HTCondor, CVMFS and modern virtualization technology. The challenging task of managing the opportunistic resources is performed by COBalD/TARDIS. We showcase the challenges, employed solutions and experiences gained with the provisioning of opportunistic resources from several resource providers like university clusters, HPC centers and cloud setups in a multi VO environment. This work can serve as a blueprint for approaching the provisioning of resources from other resource providers
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