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The analysis of exonic DNA from prostate cancers has identified recurrently mutated genes, but the spectrum of genome-wide alterations has not been profiled extensively in this disease. We sequenced the genomes of 57 prostate tumors and matched normal tissues to characterize somatic alterations and to study how they accumulate during oncogenesis and(More)
A stochastic extension of COWS is presented. First the formalism is given an operational semantics leading to finitely branching transition systems. Then its syntax and semantics are enriched along the lines of Markovian extensions of process calculi. This allows addressing quantitative reasoning about the behaviour of the specified web services. For(More)
This paper focuses on Beta-binders, a language of processes with typed interaction sites which has been recently introduced to represent biological entities. Here the syntax and semantics of Beta-binders are enriched to achieve a stochastic version of it, in order to obtain quantitative measures on biological phenomena. The relevance of quantitative(More)
Defining the chronology of molecular alterations may identify milestones in carcinogenesis. To unravel the temporal evolution of aberrations from clinical tumors, we developed CLONET, which upon estimation of tumor admixture and ploidy infers the clonal hierarchy of genomic aberrations. Comparative analysis across 100 sequenced genomes from prostate,(More)
Biological systems are characterised by a large number of interacting entities whose dynamics is described by a number of reaction equations. Mathematical methods for modelling biological systems are mostly based on a centralised solution approach: the modelled system is described as a whole and the solution technique, normally the integration of a system(More)
Data protection legislation requires personal data to be collected and processed only for lawful and legitimate purposes. Unfortunately, existing protection mechanisms are not appropriate for purpose control: they only prevent unauthorized actions from occurring and do not guarantee that the data are actually used for the intended purpose. In this paper, we(More)
The Stochastic Simulation Algorithm (SSA) is a milestone in the realm of stochastic modeling of biological systems, as it inspires all the current algorithms for stochastic simulation. Essentially, the SSA shows that under certain hypothesis the time to the next occurrence of a biochemical reaction is a random variable following a negative exponential(More)
We consider the problem of verifying stochastic models of biochemical networks against behavioral properties expressed in temporal logic terms. Exact probabilistic verification approaches such as, for example, CSL/PCTL model checking, are undermined by a huge computational demand which rule them out for most real case studies. Less demanding approaches,(More)