@inproceedings{1234,
abstract = {We present a new algorithm for the statistical model checking of Markov chains with respect to unbounded temporal properties, including full linear temporal logic. The main idea is that we monitor each simulation run on the fly, in order to detect quickly if a bottom strongly connected component is entered with high probability, in which case the simulation run can be terminated early. As a result, our simulation runs are often much shorter than required by termination bounds that are computed a priori for a desired level of confidence on a large state space. In comparison to previous algorithms for statistical model checking our method is not only faster in many cases but also requires less information about the system, namely, only the minimum transition probability that occurs in the Markov chain. In addition, our method can be generalised to unbounded quantitative properties such as mean-payoff bounds.},
author = {Daca, Przemyslaw and Henzinger, Thomas A and Kretinsky, Jan and Petrov, Tatjana},
location = {Eindhoven, The Netherlands},
pages = {112 -- 129},
publisher = {Springer},
title = {{Faster statistical model checking for unbounded temporal properties}},
doi = {10.1007/978-3-662-49674-9_7},
volume = {9636},
year = {2016},
}
@article{1359,
abstract = {The role of gene interactions in the evolutionary process has long
been controversial. Although some argue that they are not of
importance, because most variation is additive, others claim that
their effect in the long term can be substantial. Here, we focus on
the long-term effects of genetic interactions under directional
selection assuming no mutation or dominance, and that epistasis is
symmetrical overall. We ask by how much the mean of a complex
trait can be increased by selection and analyze two extreme
regimes, in which either drift or selection dominate the dynamics
of allele frequencies. In both scenarios, epistatic interactions affect
the long-term response to selection by modulating the additive
genetic variance. When drift dominates, we extend Robertson
’
s
[Robertson A (1960)
Proc R Soc Lond B Biol Sci
153(951):234
−
249]
argument to show that, for any form of epistasis, the total response
of a haploid population is proportional to the initial total genotypic
variance. In contrast, the total response of a diploid population is
increased by epistasis, for a given initial genotypic variance. When
selection dominates, we show that the total selection response can
only be increased by epistasis when s
ome initially deleterious alleles
become favored as the genetic background changes. We find a sim-
ple approximation for this effect and show that, in this regime, it is
the structure of the genotype - phenotype map that matters and not
the variance components of the population.},
author = {Paixao, Tiago and Barton, Nicholas H},
journal = {PNAS},
number = {16},
pages = {4422 -- 4427},
publisher = {National Academy of Sciences},
title = {{The effect of gene interactions on the long-term response to selection}},
doi = {10.1073/pnas.1518830113},
volume = {113},
year = {2016},
}
@article{1666,
abstract = {Evolution of gene regulation is crucial for our understanding of the phenotypic differences between species, populations and individuals. Sequence-specific binding of transcription factors to the regulatory regions on the DNA is a key regulatory mechanism that determines gene expression and hence heritable phenotypic variation. We use a biophysical model for directional selection on gene expression to estimate the rates of gain and loss of transcription factor binding sites (TFBS) in finite populations under both point and insertion/deletion mutations. Our results show that these rates are typically slow for a single TFBS in an isolated DNA region, unless the selection is extremely strong. These rates decrease drastically with increasing TFBS length or increasingly specific protein-DNA interactions, making the evolution of sites longer than ∼ 10 bp unlikely on typical eukaryotic speciation timescales. Similarly, evolution converges to the stationary distribution of binding sequences very slowly, making the equilibrium assumption questionable. The availability of longer regulatory sequences in which multiple binding sites can evolve simultaneously, the presence of “pre-sites” or partially decayed old sites in the initial sequence, and biophysical cooperativity between transcription factors, can all facilitate gain of TFBS and reconcile theoretical calculations with timescales inferred from comparative genomics.},
author = {Tugrul, Murat and Paixao, Tiago and Barton, Nicholas H and Tkacik, Gasper},
journal = {PLoS Genetics},
number = {11},
publisher = {Public Library of Science},
title = {{Dynamics of transcription factor binding site evolution}},
doi = {10.1371/journal.pgen.1005639},
volume = {11},
year = {2015},
}
@article{1542,
abstract = {The theory of population genetics and evolutionary computation have been evolving separately for nearly 30 years. Many results have been independently obtained in both fields and many others are unique to its respective field. We aim to bridge this gap by developing a unifying framework for evolutionary processes that allows both evolutionary algorithms and population genetics models to be cast in the same formal framework. The framework we present here decomposes the evolutionary process into its several components in order to facilitate the identification of similarities between different models. In particular, we propose a classification of evolutionary operators based on the defining properties of the different components. We cast several commonly used operators from both fields into this common framework. Using this, we map different evolutionary and genetic algorithms to different evolutionary regimes and identify candidates with the most potential for the translation of results between the fields. This provides a unified description of evolutionary processes and represents a stepping stone towards new tools and results to both fields. },
author = {Paixao, Tiago and Badkobeh, Golnaz and Barton, Nicholas H and Çörüş, Doğan and Dang, Duccuong and Friedrich, Tobias and Lehre, Per and Sudholt, Dirk and Sutton, Andrew and Trubenova, Barbora},
journal = { Journal of Theoretical Biology},
pages = {28 -- 43},
publisher = {Elsevier},
title = {{Toward a unifying framework for evolutionary processes}},
doi = {10.1016/j.jtbi.2015.07.011},
volume = {383},
year = {2015},
}
@article{1840,
abstract = {In this paper, we present a method for reducing a regular, discrete-time Markov chain (DTMC) to another DTMC with a given, typically much smaller number of states. The cost of reduction is defined as the Kullback-Leibler divergence rate between a projection of the original process through a partition function and a DTMC on the correspondingly partitioned state space. Finding the reduced model with minimal cost is computationally expensive, as it requires an exhaustive search among all state space partitions, and an exact evaluation of the reduction cost for each candidate partition. Our approach deals with the latter problem by minimizing an upper bound on the reduction cost instead of minimizing the exact cost. The proposed upper bound is easy to compute and it is tight if the original chain is lumpable with respect to the partition. Then, we express the problem in the form of information bottleneck optimization, and propose using the agglomerative information bottleneck algorithm for searching a suboptimal partition greedily, rather than exhaustively. The theory is illustrated with examples and one application scenario in the context of modeling bio-molecular interactions.},
author = {Geiger, Bernhard and Petrov, Tatjana and Kubin, Gernot and Koeppl, Heinz},
issn = {0018-9286},
journal = {IEEE Transactions on Automatic Control},
number = {4},
pages = {1010 -- 1022},
publisher = {IEEE},
title = {{Optimal Kullback-Leibler aggregation via information bottleneck}},
doi = {10.1109/TAC.2014.2364971},
volume = {60},
year = {2015},
}