TY - GEN
AB - We consider probabilistic automata on infinite words with acceptance defined by parity conditions. We consider three qualitative decision problems: (i) the positive decision problem asks whether there is a word that is accepted with positive probability; (ii) the almost decision problem asks whether there is a word that is accepted with probability 1; and (iii) the limit decision problem asks whether for every ε > 0 there is a word that is accepted with probability at least 1 − ε. We unify and generalize several decidability results for probabilistic automata over infinite words, and identify a robust (closed under union and intersection) subclass of probabilistic automata for which all the qualitative decision problems are decidable for parity conditions. We also show that if the input words are restricted to lasso shape words, then the positive and almost problems are decidable for all probabilistic automata with parity conditions.
AU - Chatterjee, Krishnendu
AU - Tracol, Mathieu
ID - 5384
SN - 2664-1690
TI - Decidable problems for probabilistic automata on infinite words
ER -
TY - GEN
AB - We introduce TopoCut: a new way to integrate knowledge about topological properties (TPs) into random field image segmentation model. Instead of including TPs as additional constraints during minimization of the energy function, we devise an efficient algorithm for modifying the unary potentials such that the resulting segmentation is guaranteed with the desired properties. Our method is more flexible in the sense that it handles more topology constraints than previous methods, which were only able to enforce pairwise or global connectivity. In particular, our method is very fast, making it for the first time possible to enforce global topological properties in practical image segmentation tasks.
AU - Chen, Chao
AU - Freedman, Daniel
AU - Lampert, Christoph
ID - 5386
SN - 2664-1690
TI - Enforcing topological constraints in random field image segmentation
ER -
TY - CONF
AB - We present an algorithmic method for the quantitative, performance-aware synthesis of concurrent programs. The input consists of a nondeterministic partial program and of a parametric performance model. The nondeterminism allows the programmer to omit which (if any) synchronization construct is used at a particular program location. The performance model, specified as a weighted automaton, can capture system architectures by assigning different costs to actions such as locking, context switching, and memory and cache accesses. The quantitative synthesis problem is to automatically resolve the nondeterminism of the partial program so that both correctness is guaranteed and performance is optimal. As is standard for shared memory concurrency, correctness is formalized "specification free", in particular as race freedom or deadlock freedom. For worst-case (average-case) performance, we show that the problem can be reduced to 2-player graph games (with probabilistic transitions) with quantitative objectives. While we show, using game-theoretic methods, that the synthesis problem is Nexp-complete, we present an algorithmic method and an implementation that works efficiently for concurrent programs and performance models of practical interest. We have implemented a prototype tool and used it to synthesize finite-state concurrent programs that exhibit different programming patterns, for several performance models representing different architectures.
AU - Cerny, Pavol
AU - Chatterjee, Krishnendu
AU - Henzinger, Thomas A
AU - Radhakrishna, Arjun
AU - Singh, Rohit
ED - Gopalakrishnan, Ganesh
ED - Qadeer, Shaz
ID - 3366
TI - Quantitative synthesis for concurrent programs
VL - 6806
ER -
TY - JOUR
AB - We report the switching behavior of the full bacterial flagellum system that includes the filament and the motor in wild-type Escherichia coli cells. In sorting the motor behavior by the clockwise bias, we find that the distributions of the clockwise (CW) and counterclockwise (CCW) intervals are either exponential or nonexponential with long tails. At low bias, CW intervals are exponentially distributed and CCW intervals exhibit long tails. At intermediate CW bias (0.5) both CW and CCW intervals are mainly exponentially distributed. A simple model suggests that these two distinct switching behaviors are governed by the presence of signaling noise within the chemotaxis network. Low noise yields exponentially distributed intervals, whereas large noise yields nonexponential behavior with long tails. These drastically different motor statistics may play a role in optimizing bacterial behavior for a wide range of environmental conditions.
AU - Park, Heungwon
AU - Oikonomou, Panos
AU - Guet, Calin C
AU - Cluzel, Philippe
ID - 6496
IS - 10
JF - Biophysical Journal
SN - 0006-3495
TI - Noise underlies switching behavior of the bacterial flagellum
VL - 101
ER -
TY - JOUR
AB - Background: The availability of many gene alignments with overlapping taxon sets raises the question of which strategy is the best to infer species phylogenies from multiple gene information. Methods and programs abound that use the gene alignment in different ways to reconstruct the species tree. In particular, different methods combine the original data at different points along the way from the underlying sequences to the final tree. Accordingly, they are classified into superalignment, supertree and medium-level approaches. Here, we present a simulation study to compare different methods from each of these three approaches.
Results: We observe that superalignment methods usually outperform the other approaches over a wide range of parameters including sparse data and gene-specific evolutionary parameters. In the presence of high incongruency among gene trees, however, other combination methods show better performance than the superalignment approach. Surprisingly, some supertree and medium-level methods exhibit, on average, worse results than a single gene phylogeny with complete taxon information.
Conclusions: For some methods, using the reconstructed gene tree as an estimation of the species tree is superior to the combination of incomplete information. Superalignment usually performs best since it is less susceptible to stochastic error. Supertree methods can outperform superalignment in the presence of gene-tree conflict.
AU - Kupczok, Anne
AU - Schmidt, Heiko
AU - Von Haeseler, Arndt
ID - 2409
IS - 1
JF - Algorithms for Molecular Biology
TI - Accuracy of phylogeny reconstruction methods combining overlapping gene data sets
VL - 5
ER -
TY - JOUR
AB - Biological traits result in part from interactions between different genetic loci. This can lead to sign epistasis, in which a beneficial adaptation involves a combination of individually deleterious or neutral mutations; in this case, a population must cross a “fitness valley” to adapt. Recombination can assist this process by combining mutations from different individuals or retard it by breaking up the adaptive combination. Here, we analyze the simplest fitness valley, in which an adaptation requires one mutation at each of two loci to provide a fitness benefit. We present a theoretical analysis of the effect of recombination on the valley-crossing process across the full spectrum of possible parameter regimes. We find that low recombination rates can speed up valley crossing relative to the asexual case, while higher recombination rates slow down valley crossing, with the transition between the two regimes occurring when the recombination rate between the loci is approximately equal to the selective advantage provided by the adaptation. In large populations, if the recombination rate is high and selection against single mutants is substantial, the time to cross the valley grows exponentially with population size, effectively meaning that the population cannot acquire the adaptation. Recombination at the optimal (low) rate can reduce the valley-crossing time by up to several orders of magnitude relative to that in an asexual population.
AU - Weissman, Daniel
AU - Feldman, Marcus
AU - Fisher, Daniel
ID - 3303
IS - 4
JF - Genetics
TI - The rate of fitness-valley crossing in sexual populations
VL - 186
ER -
TY - JOUR
AB - Weighted automata are nondeterministic automata with numerical weights on transitions. They can define quantitative languages L that assign to each word w a real number L(w). In the case of infinite words, the value of a run is naturally computed as the maximum, limsup, liminf, limit-average, or discounted-sum of the transition weights. The value of a word w is the supremum of the values of the runs over w. We study expressiveness and closure questions about these quantitative languages. We first show that the set of words with value greater than a threshold can be omega-regular for deterministic limit-average and discounted-sum automata, while this set is always omega-regular when the threshold is isolated (i.e., some neighborhood around the threshold contains no word). In the latter case, we prove that the omega-regular language is robust against small perturbations of the transition weights. We next consider automata with transition weights 0 or 1 and show that they are as expressive as general weighted automata in the limit-average case, but not in the discounted-sum case. Third, for quantitative languages L-1 and L-2, we consider the operations max(L-1, L-2), min(L-1, L-2), and 1 - L-1, which generalize the boolean operations on languages, as well as the sum L-1 + L-2. We establish the closure properties of all classes of quantitative languages with respect to these four operations.
AU - Chatterjee, Krishnendu
AU - Doyen, Laurent
AU - Henzinger, Thomas A
ID - 3867
IS - 3
JF - Logical Methods in Computer Science
TI - Expressiveness and closure properties for quantitative languages
VL - 6
ER -
TY - CONF
AB - The induction of a signaling pathway is characterized by transient complex formation and mutual posttranslational modification of proteins. To faithfully capture this combinatorial process in a math- ematical model is an important challenge in systems biology. Exploiting the limited context on which most binding and modification events are conditioned, attempts have been made to reduce the com- binatorial complexity by quotienting the reachable set of molecular species, into species aggregates while preserving the deterministic semantics of the thermodynamic limit. Recently we proposed a quotienting that also preserves the stochastic semantics and that is complete in the sense that the semantics of individual species can be recovered from the aggregate semantics. In this paper we prove that this quotienting yields a sufficient condition for weak lumpability and that it gives rise to a backward Markov bisimulation between the original and aggregated transition system. We illustrate the framework on a case study of the EGF/insulin receptor crosstalk.
AU - Feret, Jérôme
AU - Henzinger, Thomas A
AU - Koeppl, Heinz
AU - Petrov, Tatjana
ID - 3719
TI - Lumpability abstractions of rule-based systems
VL - 40
ER -
TY - JOUR
AU - Barton, Nicholas H
ID - 3772
IS - 6
JF - PLoS Genetics
TI - Understanding adaptation in large populations
VL - 6
ER -
TY - JOUR
AB - If distinct biological species are to coexist in sympatry, they must be reproductively isolated and must exploit different limiting resources. A two-niche Levene model is analysed, in which habitat preference and survival depend on underlying additive traits. The population genetics of preference and viability are equivalent. However, there is a linear trade-off between the chances of settling in either niche, whereas viabilities may be constrained arbitrarily. With a convex trade-off, a sexual population evolves a single generalist genotype, whereas with a concave trade-off, disruptive selection favours maximal variance. A pure habitat preference evolves to global linkage equilibrium if mating occurs in a single pool, but remarkably, evolves to pairwise linkage equilibrium within niches if mating is within those niches--independent of the genetics. With a concave trade-off, the population shifts sharply between a unimodal distribution with high gene flow and a bimodal distribution with strong isolation, as the underlying genetic variance increases. However, these alternative states are only simultaneously stable for a narrow parameter range. A sharp threshold is only seen if survival in the 'wrong' niche is low; otherwise, strong isolation is impossible. Gene flow from divergent demes makes speciation much easier in parapatry than in sympatry.
AU - Barton, Nicholas H
ID - 3773
IS - 1547
JF - Philosophical Transactions of the Royal Society of London. Series B, Biological Sciences
TI - What role does natural selection play in speciation?
VL - 365
ER -