@article{1358,
  abstract     = {Gene regulation relies on the specificity of transcription factor (TF)–DNA interactions. Limited specificity may lead to crosstalk: a regulatory state in which a gene is either incorrectly activated due to noncognate TF–DNA interactions or remains erroneously inactive. As each TF can have numerous interactions with noncognate cis-regulatory elements, crosstalk is inherently a global problem, yet has previously not been studied as such. We construct a theoretical framework to analyse the effects of global crosstalk on gene regulation. We find that crosstalk presents a significant challenge for organisms with low-specificity TFs, such as metazoans. Crosstalk is not easily mitigated by known regulatory schemes acting at equilibrium, including variants of cooperativity and combinatorial regulation. Our results suggest that crosstalk imposes a previously unexplored global constraint on the functioning and evolution of regulatory networks, which is qualitatively distinct from the known constraints that act at the level of individual gene regulatory elements.},
  author       = {Friedlander, Tamar and Prizak, Roshan and Guet, Calin C and Barton, Nicholas H and Tkacik, Gasper},
  journal      = {Nature Communications},
  publisher    = {Nature Publishing Group},
  title        = {{Intrinsic limits to gene regulation by global crosstalk}},
  doi          = {10.1038/ncomms12307},
  volume       = {7},
  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{1427,
  abstract     = {Changes in gene expression are an important mode of evolution; however, the proximate mechanism of these changes is poorly understood. In particular, little is known about the effects of mutations within cis binding sites for transcription factors, or the nature of epistatic interactions between these mutations. Here, we tested the effects of single and double mutants in two cis binding sites involved in the transcriptional regulation of the Escherichia coli araBAD operon, a component of arabinose metabolism, using a synthetic system. This system decouples transcriptional control from any posttranslational effects on fitness, allowing a precise estimate of the effect of single and double mutations, and hence epistasis, on gene expression. We found that epistatic interactions between mutations in the araBAD cis-regulatory element are common, and that the predominant form of epistasis is negative. The magnitude of the interactions depended on whether the mutations are located in the same or in different operator sites. Importantly, these epistatic interactions were dependent on the presence of arabinose, a native inducer of the araBAD operon in vivo, with some interactions changing in sign (e.g., from negative to positive) in its presence. This study thus reveals that mutations in even relatively simple cis-regulatory elements interact in complex ways such that selection on the level of gene expression in one environment might perturb regulation in the other environment in an unpredictable and uncorrelated manner.},
  author       = {Lagator, Mato and Igler, Claudia and Moreno, Anaisa and Guet, Calin C and Bollback, Jonathan P},
  journal      = {Molecular Biology and Evolution},
  number       = {3},
  pages        = {761 -- 769},
  publisher    = {Oxford University Press},
  title        = {{Epistatic interactions in the arabinose cis-regulatory element}},
  doi          = {10.1093/molbev/msv269},
  volume       = {33},
  year         = {2016},
}

@inproceedings{1524,
  abstract     = {When designing genetic circuits, the typical primitives used in major existing modelling formalisms are gene interaction graphs, where edges between genes denote either an activation or inhibition relation. However, when designing experiments, it is important to be precise about the low-level mechanistic details as to how each such relation is implemented. The rule-based modelling language Kappa allows to unambiguously specify mechanistic details such as DNA binding sites, dimerisation of transcription factors, or co-operative interactions. Such a detailed description comes with complexity and computationally costly executions. We propose a general method for automatically transforming a rule-based program, by eliminating intermediate species and adjusting the rate constants accordingly. To the best of our knowledge, we show the first automated reduction of rule-based models based on equilibrium approximations.
Our algorithm is an adaptation of an existing algorithm, which was designed for reducing reaction-based programs; our version of the algorithm scans the rule-based Kappa model in search for those interaction patterns known to be amenable to equilibrium approximations (e.g. Michaelis-Menten scheme). Additional checks are then performed in order to verify if the reduction is meaningful in the context of the full model. The reduced model is efficiently obtained by static inspection over the rule-set. The tool is tested on a detailed rule-based model of a λ-phage switch, which lists 92 rules and 13 agents. The reduced model has 11 rules and 5 agents, and provides a dramatic reduction in simulation time of several orders of magnitude.},
  author       = {Beica, Andreea and Guet, Calin C and Petrov, Tatjana},
  location     = {Madrid, Spain},
  pages        = {173 -- 191},
  publisher    = {Springer},
  title        = {{Efficient reduction of kappa models by static inspection of the rule-set}},
  doi          = {10.1007/978-3-319-26916-0_10},
  volume       = {9271},
  year         = {2016},
}

@article{5749,
  abstract     = {Parasitism creates selection for resistance mechanisms in host populations and is hypothesized to promote increased host evolvability. However, the influence of these traits on host evolution when parasites are no longer present is unclear. We used experimental evolution and whole-genome sequencing of Escherichia coli to determine the effects of past and present exposure to parasitic viruses (phages) on the spread of mutator alleles, resistance, and bacterial competitive fitness. We found that mutator alleles spread rapidly during adaptation to any of four different phage species, and this pattern was even more pronounced with multiple phages present simultaneously. However, hypermutability did not detectably accelerate adaptation in the absence of phages and recovery of fitness costs associated with resistance. Several lineages evolved phage resistance through elevated mucoidy, and during subsequent evolution in phage-free conditions they rapidly reverted to nonmucoid, phage-susceptible phenotypes. Genome sequencing revealed that this phenotypic reversion was achieved by additional genetic changes rather than by genotypic reversion of the initial resistance mutations. Insertion sequence (IS) elements played a key role in both the acquisition of resistance and adaptation in the absence of parasites; unlike single nucleotide polymorphisms, IS insertions were not more frequent in mutator lineages. Our results provide a genetic explanation for rapid reversion of mucoidy, a phenotype observed in other bacterial species including human pathogens. Moreover, this demonstrates that the types of genetic change underlying adaptation to fitness costs, and consequently the impact of evolvability mechanisms such as increased point-mutation rates, depend critically on the mechanism of resistance.},
  author       = {Wielgoss, Sébastien and Bergmiller, Tobias and Bischofberger, Anna M. and Hall, Alex R.},
  issn         = {1537-1719},
  journal      = {Molecular Biology and Evolution},
  number       = {3},
  pages        = {770--782},
  publisher    = {Oxford University Press},
  title        = {{Adaptation to parasites and costs of parasite resistance in mutator and nonmutator bacteria}},
  doi          = {10.1093/molbev/msv270},
  volume       = {33},
  year         = {2016},
}

@article{1008,
  abstract     = {Feedback loops in biological networks, among others, enable differentiation and cell cycle progression, and increase robustness in signal transduction. In natural networks, feedback loops are often complex and intertwined, making it challenging to identify which loops are mainly responsible for an observed behavior. However, minimal synthetic replicas could allow for such identification. Here, we engineered a synthetic permease-inducer-repressor system in Saccharomyces cerevisiae to analyze if a transport-mediated positive feedback loop could be a core mechanism for the switch-like behavior in the regulation of metabolic gene networks such as the S. cerevisiae GAL system or the Escherichia coli lac operon. We characterized the synthetic circuit using deterministic and stochastic mathematical models. Similar to its natural counterparts, our synthetic system shows bistable and hysteretic behavior, and the inducer concentration range for bistability as well as the switching rates between the two stable states depend on the repressor concentration. Our results indicate that a generic permease–inducer–repressor circuit with a single feedback loop is sufficient to explain the experimentally observed bistable behavior of the natural systems. We anticipate that the approach of reimplementing natural systems with orthogonal parts to identify crucial network components is applicable to other natural systems such as signaling pathways.},
  author       = {Gnügge, Robert and Dharmarajan, Lekshmi and Lang, Moritz and Stelling, Jörg},
  journal      = {ACS Synthetic Biology},
  number       = {10},
  pages        = {1098 -- 1107},
  publisher    = {American Chemical Society},
  title        = {{An orthogonal permease–inducer–repressor feedback loop shows bistability}},
  doi          = {10.1021/acssynbio.6b00013},
  volume       = {5},
  year         = {2016},
}

@misc{9873,
  author       = {Boehm, Alex and Arnoldini, Markus and Bergmiller, Tobias and Röösli, Thomas and Bigosch, Colette and Ackermann, Martin},
  publisher    = {Public Library of Science},
  title        = {{Quantification of the growth rate reduction as a consequence of age-specific mortality}},
  doi          = {10.1371/journal.pgen.1005974.s015},
  year         = {2016},
}

@article{1170,
  abstract     = {The increasing complexity of dynamic models in systems and synthetic biology poses computational challenges especially for the identification of model parameters. While modularization of the corresponding optimization problems could help reduce the “curse of dimensionality,” abundant feedback and crosstalk mechanisms prohibit a simple decomposition of most biomolecular networks into subnetworks, or modules. Drawing on ideas from network modularization and multiple-shooting optimization, we present here a modular parameter identification approach that explicitly allows for such interdependencies. Interfaces between our modules are given by the experimentally measured molecular species. This definition allows deriving good (initial) estimates for the inter-module communication directly from the experimental data. Given these estimates, the states and parameter sensitivities of different modules can be integrated independently. To achieve consistency between modules, we iteratively adjust the estimates for inter-module communication while optimizing the parameters. After convergence to an optimal parameter set---but not during earlier iterations---the intermodule communication as well as the individual modules\' state dynamics agree with the dynamics of the nonmodularized network. Our modular parameter identification approach allows for easy parallelization; it can reduce the computational complexity for larger networks and decrease the probability to converge to suboptimal local minima. We demonstrate the algorithm\'s performance in parameter estimation for two biomolecular networks, a synthetic genetic oscillator and a mammalian signaling pathway.},
  author       = {Lang, Moritz and Stelling, Jörg},
  journal      = {SIAM Journal on Scientific Computing},
  number       = {6},
  pages        = {B988 -- B1008},
  publisher    = {Society for Industrial and Applied Mathematics},
  title        = {{Modular parameter identification of biomolecular networks}},
  doi          = {10.1137/15M103306X},
  volume       = {38},
  year         = {2016},
}

@inproceedings{1430,
  abstract     = {Evolutionary algorithms (EAs) form a popular optimisation paradigm inspired by natural evolution. In recent years the field of evolutionary computation has developed a rigorous analytical theory to analyse their runtime on many illustrative problems. Here we apply this theory to a simple model of natural evolution. In the Strong Selection Weak Mutation (SSWM) evolutionary regime the time between occurrence of new mutations is much longer than the time it takes for a new beneficial mutation to take over the population. In this situation, the population only contains copies of one genotype and evolution can be modelled as a (1+1)-type process where the probability of accepting a new genotype (improvements or worsenings) depends on the change in fitness. We present an initial runtime analysis of SSWM, quantifying its performance for various parameters and investigating differences to the (1+1) EA. We show that SSWM can have a moderate advantage over the (1+1) EA at crossing fitness valleys and study an example where SSWM outperforms the (1+1) EA by taking advantage of information on the fitness gradient.},
  author       = {Paixao, Tiago and Sudholt, Dirk and Heredia, Jorge and Trubenova, Barbora},
  booktitle    = {Proceedings of the 2015 Annual Conference on Genetic and Evolutionary Computation},
  location     = {Madrid, Spain},
  pages        = {1455 -- 1462},
  publisher    = {ACM},
  title        = {{First steps towards a runtime comparison of natural and artificial evolution}},
  doi          = {10.1145/2739480.2754758},
  year         = {2015},
}

@misc{9712,
  author       = {Tugrul, Murat and Paixao, Tiago and Barton, Nicholas H and Tkačik, Gašper},
  publisher    = {Public Library of Science},
  title        = {{Other fitness models for comparison & for interacting TFBSs}},
  doi          = {10.1371/journal.pgen.1005639.s001},
  year         = {2015},
}

@misc{9719,
  abstract     = {Parasitism creates selection for resistance mechanisms in host populations and is hypothesized to promote increased host evolvability. However, the influence of these traits on host evolution when parasites are no longer present is unclear. We used experimental evolution and whole-genome sequencing of Escherichia coli to determine the effects of past and present exposure to parasitic viruses (phages) on the spread of mutator alleles, resistance, and bacterial competitive fitness. We found that mutator alleles spread rapidly during adaptation to any of four different phage species, and this pattern was even more pronounced with multiple phages present simultaneously. However, hypermutability did not detectably accelerate adaptation in the absence of phages and recovery of fitness costs associated with resistance. Several lineages evolved phage resistance through elevated mucoidy, and during subsequent evolution in phage-free conditions they rapidly reverted to nonmucoid, phage-susceptible phenotypes. Genome sequencing revealed that this phenotypic reversion was achieved by additional genetic changes rather than by genotypic reversion of the initial resistance mutations. Insertion sequence (IS) elements played a key role in both the acquisition of resistance and adaptation in the absence of parasites; unlike single nucleotide polymorphisms, IS insertions were not more frequent in mutator lineages. Our results provide a genetic explanation for rapid reversion of mucoidy, a phenotype observed in other bacterial species including human pathogens. Moreover, this demonstrates that the types of genetic change underlying adaptation to fitness costs, and consequently the impact of evolvability mechanisms such as increased point-mutation rates, depend critically on the mechanism of resistance.},
  author       = {Wielgoss, Sébastien and Bergmiller, Tobias and Bischofberger, Anna M. and Hall, Alex R.},
  publisher    = {Dryad},
  title        = {{Data from: Adaptation to parasites and costs of parasite resistance in mutator and non-mutator bacteria}},
  doi          = {10.5061/dryad.cj910},
  year         = {2015},
}

@inproceedings{1835,
  abstract     = {The behaviour of gene regulatory networks (GRNs) is typically analysed using simulation-based statistical testing-like methods. In this paper, we demonstrate that we can replace this approach by a formal verification-like method that gives higher assurance and scalability. We focus on Wagner’s weighted GRN model with varying weights, which is used in evolutionary biology. In the model, weight parameters represent the gene interaction strength that may change due to genetic mutations. For a property of interest, we synthesise the constraints over the parameter space that represent the set of GRNs satisfying the property. We experimentally show that our parameter synthesis procedure computes the mutational robustness of GRNs –an important problem of interest in evolutionary biology– more efficiently than the classical simulation method. We specify the property in linear temporal logics. We employ symbolic bounded model checking and SMT solving to compute the space of GRNs that satisfy the property, which amounts to synthesizing a set of linear constraints on the weights.},
  author       = {Giacobbe, Mirco and Guet, Calin C and Gupta, Ashutosh and Henzinger, Thomas A and Paixao, Tiago and Petrov, Tatjana},
  location     = {London, United Kingdom},
  pages        = {469 -- 483},
  publisher    = {Springer},
  title        = {{Model checking gene regulatory networks}},
  doi          = {10.1007/978-3-662-46681-0_47},
  volume       = {9035},
  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},
}

@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{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{2083,
  abstract     = {Understanding the effects of sex and migration on adaptation to novel environments remains a key problem in evolutionary biology. Using a single-cell alga Chlamydomonas reinhardtii, we investigated how sex and migration affected rates of evolutionary rescue in a sink environment, and subsequent changes in fitness following evolutionary rescue. We show that sex and migration affect both the rate of evolutionary rescue and subsequent adaptation. However, their combined effects change as the populations adapt to a sink habitat. Both sex and migration independently increased rates of evolutionary rescue, but the effect of sex on subsequent fitness improvements, following initial rescue, changed with migration, as sex was beneficial in the absence of migration but constraining adaptation when combined with migration. These results suggest that sex and migration are beneficial during the initial stages of adaptation, but can become detrimental as the population adapts to its environment.},
  author       = {Lagator, Mato and Morgan, Andrew and Neve, Paul and Colegrave, Nick},
  journal      = {Evolution},
  number       = {8},
  pages        = {2296 -- 2305},
  publisher    = {Wiley},
  title        = {{Role of sex and migration in adaptation to sink environments}},
  doi          = {10.1111/evo.12440},
  volume       = {68},
  year         = {2014},
}

@article{1894,
  abstract     = {Background: Bacterial Dsb enzymes are involved in the oxidative folding of many proteins, through the formation of disulfide bonds between their cysteine residues. The Dsb protein network has been well characterized in cells of the model microorganism Escherichia coli. To gain insight into the functioning of the Dsb system in epsilon-Proteobacteria, where it plays an important role in the colonization process, we studied two homologs of the main Escherichia coli Dsb oxidase (EcDsbA) that are present in the cells of the enteric pathogen Campylobacter jejuni, the most frequently reported bacterial cause of human enteritis in the world. Methods and Results: Phylogenetic analysis suggests the horizontal transfer of the epsilon-Proteobacterial DsbAs from a common ancestor to gamma-Proteobacteria, which then gave rise to the DsbL lineage. Phenotype and enzymatic assays suggest that the two C. jejuni DsbAs play different roles in bacterial cells and have divergent substrate spectra. CjDsbA1 is essential for the motility and autoagglutination phenotypes, while CjDsbA2 has no impact on those processes. CjDsbA1 plays a critical role in the oxidative folding that ensures the activity of alkaline phosphatase CjPhoX, whereas CjDsbA2 is crucial for the activity of arylsulfotransferase CjAstA, encoded within the dsbA2-dsbB-astA operon. Conclusions: Our results show that CjDsbA1 is the primary thiol-oxidoreductase affecting life processes associated with bacterial spread and host colonization, as well as ensuring the oxidative folding of particular protein substrates. In contrast, CjDsbA2 activity does not affect the same processes and so far its oxidative folding activity has been demonstrated for one substrate, arylsulfotransferase CjAstA. The results suggest the cooperation between CjDsbA2 and CjDsbB. In the case of the CjDsbA1, this cooperation is not exclusive and there is probably another protein to be identified in C. jejuni cells that acts to re-oxidize CjDsbA1. Altogether the data presented here constitute the considerable insight to the Epsilonproteobacterial Dsb systems, which have been poorly understood so far.},
  author       = {Grabowska, Anna and Wywiał, Ewa and Dunin Horkawicz, Stanislaw and Łasica, Anna and Wösten, Marc and Nagy-Staron, Anna A and Godlewska, Renata and Bocian Ostrzycka, Katarzyna and Pieńkowska, Katarzyna and Łaniewski, Paweł and Bujnicki, Janusz and Van Putten, Jos and Jagusztyn Krynicka, Elzbieta},
  journal      = {PLoS One},
  number       = {9},
  publisher    = {Public Library of Science},
  title        = {{Functional and bioinformatics analysis of two Campylobacter jejuni homologs of the thiol-disulfide oxidoreductase, DsbA}},
  doi          = {10.1371/journal.pone.0106247},
  volume       = {9},
  year         = {2014},
}

@article{1913,
  abstract     = {Deposits of phosphorylated tau protein and convergence of pathology in the hippocampus are the hallmarks of neurodegenerative tauopathies. Thus we aimed to evaluate whether regional and cellular vulnerability patterns in the hippocampus distinguish tauopathies or are influenced by their concomitant presence. Methods: We created a heat map of phospho-tau (AT8) immunoreactivity patterns in 24 hippocampal subregions/layers in individuals with Alzheimer's disease (AD)-related neurofibrillary degeneration (n = 40), Pick's disease (n = 8), progressive supranuclear palsy (n = 7), corticobasal degeneration (n = 6), argyrophilic grain disease (AGD, n = 18), globular glial tauopathy (n = 5), and tau-astrogliopathy of the elderly (n = 10). AT8 immunoreactivity patterns were compared by mathematical analysis. Results: Our study reveals disease-specific hot spots and regional selective vulnerability for these disorders. The pattern of hippocampal AD-related tau pathology is strongly influenced by concomitant AGD. Mathematical analysis reveals that hippocampal involvement in primary tauopathies is distinguishable from early-stage AD-related neurofibrillary degeneration. Conclusion: Our data demonstrate disease-specific AT8 immunoreactivity patterns and hot spots in the hippocampus even in tauopathies, which primarily do not affect the hippocampus. These hot spots can be shifted to other regions by the co-occurrence of tauopathies like AGD. Our observations support the notion that globular glial tauopathies and tau-astrogliopathy of the elderly are distinct entities.},
  author       = {Milenković, Ivan and Petrov, Tatjana and Kovács, Gábor},
  issn         = {1420-8008},
  journal      = {Dementia and Geriatric Cognitive Disorders},
  number       = {5-6},
  pages        = {375 -- 388},
  publisher    = {Karger Publishers},
  title        = {{Patterns of hippocampal tau pathology differentiate neurodegenerative dementias}},
  doi          = {10.1159/000365548},
  volume       = {38},
  year         = {2014},
}

@article{2056,
  abstract     = {We consider a continuous-time Markov chain (CTMC) whose state space is partitioned into aggregates, and each aggregate is assigned a probability measure. A sufficient condition for defining a CTMC over the aggregates is presented as a variant of weak lumpability, which also characterizes that the measure over the original process can be recovered from that of the aggregated one. We show how the applicability of de-aggregation depends on the initial distribution. The application section is devoted to illustrate how the developed theory aids in reducing CTMC models of biochemical systems particularly in connection to protein-protein interactions. We assume that the model is written by a biologist in form of site-graph-rewrite rules. Site-graph-rewrite rules compactly express that, often, only a local context of a protein (instead of a full molecular species) needs to be in a certain configuration in order to trigger a reaction event. This observation leads to suitable aggregate Markov chains with smaller state spaces, thereby providing sufficient reduction in computational complexity. This is further exemplified in two case studies: simple unbounded polymerization and early EGFR/insulin crosstalk.},
  author       = {Ganguly, Arnab and Petrov, Tatjana and Koeppl, Heinz},
  journal      = {Journal of Mathematical Biology},
  number       = {3},
  pages        = {767 -- 797},
  publisher    = {Springer},
  title        = {{Markov chain aggregation and its applications to combinatorial reaction networks}},
  doi          = {10.1007/s00285-013-0738-7},
  volume       = {69},
  year         = {2014},
}

@misc{9747,
  abstract     = {Understanding the effects of sex and migration on adaptation to novel environments remains a key problem in evolutionary biology. Using a single-cell alga Chlamydomonas reinhardtii, we investigated how sex and migration affected rates of evolutionary rescue in a sink environment, and subsequent changes in fitness following evolutionary rescue. We show that sex and migration affect both the rate of evolutionary rescue and subsequent adaptation. However, their combined effects change as the populations adapt to a sink habitat. Both sex and migration independently increased rates of evolutionary rescue, but the effect of sex on subsequent fitness improvements, following initial rescue, changed with migration, as sex was beneficial in the absence of migration but constraining adaptation when combined with migration. These results suggest that sex and migration are beneficial during the initial stages of adaptation, but can become detrimental as the population adapts to its environment.},
  author       = {Lagator, Mato and Morgan, Andrew and Neve, Paul and Colegrave, Nick},
  publisher    = {Dryad},
  title        = {{Data from: Role of sex and migration in adaptation to sink environments}},
  doi          = {10.5061/dryad.s42n1},
  year         = {2014},
}

