TY - JOUR AB - Our focus here is on the infinitesimal model. In this model, one or several quantitative traits are described as the sum of a genetic and a non-genetic component, the first being distributed within families as a normal random variable centred at the average of the parental genetic components, and with a variance independent of the parental traits. Thus, the variance that segregates within families is not perturbed by selection, and can be predicted from the variance components. This does not necessarily imply that the trait distribution across the whole population should be Gaussian, and indeed selection or population structure may have a substantial effect on the overall trait distribution. One of our main aims is to identify some general conditions on the allelic effects for the infinitesimal model to be accurate. We first review the long history of the infinitesimal model in quantitative genetics. Then we formulate the model at the phenotypic level in terms of individual trait values and relationships between individuals, but including different evolutionary processes: genetic drift, recombination, selection, mutation, population structure, …. We give a range of examples of its application to evolutionary questions related to stabilising selection, assortative mating, effective population size and response to selection, habitat preference and speciation. We provide a mathematical justification of the model as the limit as the number M of underlying loci tends to infinity of a model with Mendelian inheritance, mutation and environmental noise, when the genetic component of the trait is purely additive. We also show how the model generalises to include epistatic effects. We prove in particular that, within each family, the genetic components of the individual trait values in the current generation are indeed normally distributed with a variance independent of ancestral traits, up to an error of order 1∕M. Simulations suggest that in some cases the convergence may be as fast as 1∕M. AU - Barton, Nicholas H AU - Etheridge, Alison AU - Véber, Amandine ID - 626 JF - Theoretical Population Biology SN - 00405809 TI - The infinitesimal model: Definition derivation and implications VL - 118 ER - TY - CHAP AB - In the analysis of reactive systems a quantitative objective assigns a real value to every trace of the system. The value decision problem for a quantitative objective requires a trace whose value is at least a given threshold, and the exact value decision problem requires a trace whose value is exactly the threshold. We compare the computational complexity of the value and exact value decision problems for classical quantitative objectives, such as sum, discounted sum, energy, and mean-payoff for two standard models of reactive systems, namely, graphs and graph games. AU - Chatterjee, Krishnendu AU - Doyen, Laurent AU - Henzinger, Thomas A ED - Aceto, Luca ED - Bacci, Giorgio ED - Ingólfsdóttir, Anna ED - Legay, Axel ED - Mardare, Radu ID - 625 SN - 0302-9743 T2 - Models, Algorithms, Logics and Tools TI - The cost of exactness in quantitative reachability VL - 10460 ER - TY - JOUR AB - Bacteria adapt to adverse environmental conditions by altering gene expression patterns. Recently, a novel stress adaptation mechanism has been described that allows Escherichia coli to alter gene expression at the post-transcriptional level. The key player in this regulatory pathway is the endoribonuclease MazF, the toxin component of the toxin-antitoxin module mazEF that is triggered by various stressful conditions. In general, MazF degrades the majority of transcripts by cleaving at ACA sites, which results in the retardation of bacterial growth. Furthermore, MazF can process a small subset of mRNAs and render them leaderless by removing their ribosome binding site. MazF concomitantly modifies ribosomes, making them selective for the translation of leaderless mRNAs. In this study, we employed fluorescent reporter-systems to investigate mazEF expression during stressful conditions, and to infer consequences of the mRNA processing mediated by MazF on gene expression at the single-cell level. Our results suggest that mazEF transcription is maintained at low levels in single cells encountering adverse conditions, such as antibiotic stress or amino acid starvation. Moreover, using the grcA mRNA as a model for MazF-mediated mRNA processing, we found that MazF activation promotes heterogeneity in the grcA reporter expression, resulting in a subpopulation of cells with increased levels of GrcA reporter protein. AU - Nikolic, Nela AU - Didara, Zrinka AU - Moll, Isabella ID - 624 IS - 9 JF - PeerJ SN - 21678359 TI - MazF activation promotes translational heterogeneity of the grcA mRNA in Escherichia coli populations VL - 2017 ER - TY - CONF AB - We consider the problem of developing automated techniques for solving recurrence relations to aid the expected-runtime analysis of programs. The motivation is that several classical textbook algorithms have quite efficient expected-runtime complexity, whereas the corresponding worst-case bounds are either inefficient (e.g., Quick-Sort), or completely ineffective (e.g., Coupon-Collector). Since the main focus of expected-runtime analysis is to obtain efficient bounds, we consider bounds that are either logarithmic, linear or almost-linear (O(log n), O(n), O(n · log n), respectively, where n represents the input size). Our main contribution is an efficient (simple linear-time algorithm) sound approach for deriving such expected-runtime bounds for the analysis of recurrence relations induced by randomized algorithms. The experimental results show that our approach can efficiently derive asymptotically optimal expected-runtime bounds for recurrences of classical randomized algorithms, including Randomized-Search, Quick-Sort, Quick-Select, Coupon-Collector, where the worst-case bounds are either inefficient (such as linear as compared to logarithmic expected-runtime complexity, or quadratic as compared to linear or almost-linear expected-runtime complexity), or ineffective. AU - Chatterjee, Krishnendu AU - Fu, Hongfei AU - Murhekar, Aniket ED - Majumdar, Rupak ED - Kunčak, Viktor ID - 628 SN - 978-331963386-2 TI - Automated recurrence analysis for almost linear expected runtime bounds VL - 10426 ER - TY - CONF AB - Background: Standards have become available to share semantically encoded vital parameters from medical devices, as required for example by personal healthcare records. Standardised sharing of biosignal data largely remains open. Objectives: The goal of this work is to explore available biosignal file format and data exchange standards and profiles, and to conceptualise end-To-end solutions. Methods: The authors reviewed and discussed available biosignal file format standards with other members of international standards development organisations (SDOs). Results: A raw concept for standards based acquisition, storage, archiving and sharing of biosignals was developed. The GDF format may serve for storing biosignals. Signals can then be shared using FHIR resources and may be stored on FHIR servers or in DICOM archives, with DICOM waveforms as one possible format. Conclusion: Currently a group of international SDOs (e.g. HL7, IHE, DICOM, IEEE) is engaged in intensive discussions. This discussion extends existing work that already was adopted by large implementer communities. The concept presented here only reports the current status of the discussion in Austria. The discussion will continue internationally, with results to be expected over the coming years. AU - Sauermann, Stefan AU - David, Veronika AU - Schlögl, Alois AU - Egelkraut, Reinhard AU - Frohner, Matthias AU - Pohn, Birgit AU - Urbauer, Philipp AU - Mense, Alexander ID - 630 SN - 978-161499758-0 TI - Biosignals standards and FHIR: The way to go VL - 236 ER -