--- _id: '623' abstract: - lang: eng text: Genetic factors might be largely responsible for the development of autism spectrum disorder (ASD) that alone or in combination with specific environmental risk factors trigger the pathology. Multiple mutations identified in ASD patients that impair synaptic function in the central nervous system are well studied in animal models. How these mutations might interact with other risk factors is not fully understood though. Additionally, how systems outside of the brain are altered in the context of ASD is an emerging area of research. Extracerebral influences on the physiology could begin in utero and contribute to changes in the brain and in the development of other body systems and further lead to epigenetic changes. Therefore, multiple recent studies have aimed at elucidating the role of gene-environment interactions in ASD. Here we provide an overview on the extracerebral systems that might play an important associative role in ASD and review evidence regarding the potential roles of inflammation, trace metals, metabolism, genetic susceptibility, enteric nervous system function and the microbiota of the gastrointestinal (GI) tract on the development of endophenotypes in animal models of ASD. By influencing environmental conditions, it might be possible to reduce or limit the severity of ASD pathology. alternative_title: - ADVSANAT author: - first_name: Elisa full_name: Hill Yardin, Elisa last_name: Hill Yardin - first_name: Sonja full_name: Mckeown, Sonja last_name: Mckeown - first_name: Gaia full_name: Novarino, Gaia id: 3E57A680-F248-11E8-B48F-1D18A9856A87 last_name: Novarino orcid: 0000-0002-7673-7178 - first_name: Andreas full_name: Grabrucker, Andreas last_name: Grabrucker citation: ama: 'Hill Yardin E, Mckeown S, Novarino G, Grabrucker A. Extracerebral dysfunction in animal models of autism spectrum disorder. In: Schmeisser M, Boekers T, eds. Translational Anatomy and Cell Biology of Autism Spectrum Disorder. Vol 224. Advances in Anatomy Embryology and Cell Biology. Springer; 2017:159-187. doi:10.1007/978-3-319-52498-6_9' apa: Hill Yardin, E., Mckeown, S., Novarino, G., & Grabrucker, A. (2017). Extracerebral dysfunction in animal models of autism spectrum disorder. In M. Schmeisser & T. Boekers (Eds.), Translational Anatomy and Cell Biology of Autism Spectrum Disorder (Vol. 224, pp. 159–187). Springer. https://doi.org/10.1007/978-3-319-52498-6_9 chicago: Hill Yardin, Elisa, Sonja Mckeown, Gaia Novarino, and Andreas Grabrucker. “Extracerebral Dysfunction in Animal Models of Autism Spectrum Disorder.” In Translational Anatomy and Cell Biology of Autism Spectrum Disorder, edited by Michael Schmeisser and Tobias Boekers, 224:159–87. Advances in Anatomy Embryology and Cell Biology. Springer, 2017. https://doi.org/10.1007/978-3-319-52498-6_9. ieee: E. Hill Yardin, S. Mckeown, G. Novarino, and A. Grabrucker, “Extracerebral dysfunction in animal models of autism spectrum disorder,” in Translational Anatomy and Cell Biology of Autism Spectrum Disorder, vol. 224, M. Schmeisser and T. Boekers, Eds. Springer, 2017, pp. 159–187. ista: 'Hill Yardin E, Mckeown S, Novarino G, Grabrucker A. 2017.Extracerebral dysfunction in animal models of autism spectrum disorder. In: Translational Anatomy and Cell Biology of Autism Spectrum Disorder. ADVSANAT, vol. 224, 159–187.' mla: Hill Yardin, Elisa, et al. “Extracerebral Dysfunction in Animal Models of Autism Spectrum Disorder.” Translational Anatomy and Cell Biology of Autism Spectrum Disorder, edited by Michael Schmeisser and Tobias Boekers, vol. 224, Springer, 2017, pp. 159–87, doi:10.1007/978-3-319-52498-6_9. short: E. Hill Yardin, S. Mckeown, G. Novarino, A. Grabrucker, in:, M. Schmeisser, T. Boekers (Eds.), Translational Anatomy and Cell Biology of Autism Spectrum Disorder, Springer, 2017, pp. 159–187. date_created: 2018-12-11T11:47:33Z date_published: 2017-05-28T00:00:00Z date_updated: 2021-01-12T08:06:46Z day: '28' department: - _id: GaNo doi: 10.1007/978-3-319-52498-6_9 editor: - first_name: Michael full_name: Schmeisser, Michael last_name: Schmeisser - first_name: Tobias full_name: Boekers, Tobias last_name: Boekers intvolume: ' 224' language: - iso: eng month: '05' oa_version: None page: 159 - 187 publication: Translational Anatomy and Cell Biology of Autism Spectrum Disorder publication_identifier: isbn: - 978-3-319-52496-2 issn: - '03015556' publication_status: published publisher: Springer publist_id: '7177' quality_controlled: '1' scopus_import: 1 series_title: Advances in Anatomy Embryology and Cell Biology status: public title: Extracerebral dysfunction in animal models of autism spectrum disorder type: book_chapter user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 224 year: '2017' ... --- _id: '626' abstract: - lang: eng text: '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.' author: - first_name: Nicholas H full_name: Barton, Nicholas H id: 4880FE40-F248-11E8-B48F-1D18A9856A87 last_name: Barton orcid: 0000-0002-8548-5240 - first_name: Alison full_name: Etheridge, Alison last_name: Etheridge - first_name: Amandine full_name: Véber, Amandine last_name: Véber citation: ama: 'Barton NH, Etheridge A, Véber A. The infinitesimal model: Definition derivation and implications. Theoretical Population Biology. 2017;118:50-73. doi:10.1016/j.tpb.2017.06.001' apa: 'Barton, N. H., Etheridge, A., & Véber, A. (2017). The infinitesimal model: Definition derivation and implications. Theoretical Population Biology. Academic Press. https://doi.org/10.1016/j.tpb.2017.06.001' chicago: 'Barton, Nicholas H, Alison Etheridge, and Amandine Véber. “The Infinitesimal Model: Definition Derivation and Implications.” Theoretical Population Biology. Academic Press, 2017. https://doi.org/10.1016/j.tpb.2017.06.001.' ieee: 'N. H. Barton, A. Etheridge, and A. Véber, “The infinitesimal model: Definition derivation and implications,” Theoretical Population Biology, vol. 118. Academic Press, pp. 50–73, 2017.' ista: 'Barton NH, Etheridge A, Véber A. 2017. The infinitesimal model: Definition derivation and implications. Theoretical Population Biology. 118, 50–73.' mla: 'Barton, Nicholas H., et al. “The Infinitesimal Model: Definition Derivation and Implications.” Theoretical Population Biology, vol. 118, Academic Press, 2017, pp. 50–73, doi:10.1016/j.tpb.2017.06.001.' short: N.H. Barton, A. Etheridge, A. Véber, Theoretical Population Biology 118 (2017) 50–73. date_created: 2018-12-11T11:47:34Z date_published: 2017-12-01T00:00:00Z date_updated: 2021-01-12T08:06:50Z day: '01' ddc: - '576' department: - _id: NiBa doi: 10.1016/j.tpb.2017.06.001 ec_funded: 1 file: - access_level: open_access checksum: 7dd02bfcfe8f244f4a6c19091aedf2c8 content_type: application/pdf creator: system date_created: 2018-12-12T10:12:45Z date_updated: 2020-07-14T12:47:25Z file_id: '4964' file_name: IST-2017-908-v1+1_1-s2.0-S0040580917300886-main_1_.pdf file_size: 1133924 relation: main_file file_date_updated: 2020-07-14T12:47:25Z has_accepted_license: '1' intvolume: ' 118' language: - iso: eng month: '12' oa: 1 oa_version: Published Version page: 50 - 73 project: - _id: 25B07788-B435-11E9-9278-68D0E5697425 call_identifier: FP7 grant_number: '250152' name: Limits to selection in biology and in evolutionary computation publication: Theoretical Population Biology publication_identifier: issn: - '00405809' publication_status: published publisher: Academic Press publist_id: '7169' pubrep_id: '908' quality_controlled: '1' scopus_import: 1 status: public title: 'The infinitesimal model: Definition derivation and implications' tmp: image: /images/cc_by.png legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0) short: CC BY (4.0) type: journal_article user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 118 year: '2017' ... --- _id: '625' abstract: - lang: eng text: 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. acknowledgement: 'This research was supported in part by the Austrian Science Fund (FWF) under grants S11402-N23 and S11407-N23 (RiSE/SHiNE), and Z211-N23 (Wittgenstein Award), ERC Start grant (279307: Graph Games), Vienna Science and Technology Fund (WWTF) through project ICT15-003.' alternative_title: - LNCS article_processing_charge: No author: - first_name: Krishnendu full_name: Chatterjee, Krishnendu id: 2E5DCA20-F248-11E8-B48F-1D18A9856A87 last_name: Chatterjee orcid: 0000-0002-4561-241X - first_name: Laurent full_name: Doyen, Laurent last_name: Doyen - first_name: Thomas A full_name: Henzinger, Thomas A id: 40876CD8-F248-11E8-B48F-1D18A9856A87 last_name: Henzinger orcid: 0000−0002−2985−7724 citation: ama: 'Chatterjee K, Doyen L, Henzinger TA. The cost of exactness in quantitative reachability. In: Aceto L, Bacci G, Ingólfsdóttir A, Legay A, Mardare R, eds. Models, Algorithms, Logics and Tools. Vol 10460. Theoretical Computer Science and General Issues. Springer; 2017:367-381. doi:10.1007/978-3-319-63121-9_18' apa: Chatterjee, K., Doyen, L., & Henzinger, T. A. (2017). The cost of exactness in quantitative reachability. In L. Aceto, G. Bacci, A. Ingólfsdóttir, A. Legay, & R. Mardare (Eds.), Models, Algorithms, Logics and Tools (Vol. 10460, pp. 367–381). Springer. https://doi.org/10.1007/978-3-319-63121-9_18 chicago: Chatterjee, Krishnendu, Laurent Doyen, and Thomas A Henzinger. “The Cost of Exactness in Quantitative Reachability.” In Models, Algorithms, Logics and Tools, edited by Luca Aceto, Giorgio Bacci, Anna Ingólfsdóttir, Axel Legay, and Radu Mardare, 10460:367–81. Theoretical Computer Science and General Issues. Springer, 2017. https://doi.org/10.1007/978-3-319-63121-9_18. ieee: K. Chatterjee, L. Doyen, and T. A. Henzinger, “The cost of exactness in quantitative reachability,” in Models, Algorithms, Logics and Tools, vol. 10460, L. Aceto, G. Bacci, A. Ingólfsdóttir, A. Legay, and R. Mardare, Eds. Springer, 2017, pp. 367–381. ista: 'Chatterjee K, Doyen L, Henzinger TA. 2017.The cost of exactness in quantitative reachability. In: Models, Algorithms, Logics and Tools. LNCS, vol. 10460, 367–381.' mla: Chatterjee, Krishnendu, et al. “The Cost of Exactness in Quantitative Reachability.” Models, Algorithms, Logics and Tools, edited by Luca Aceto et al., vol. 10460, Springer, 2017, pp. 367–81, doi:10.1007/978-3-319-63121-9_18. short: K. Chatterjee, L. Doyen, T.A. Henzinger, in:, L. Aceto, G. Bacci, A. Ingólfsdóttir, A. Legay, R. Mardare (Eds.), Models, Algorithms, Logics and Tools, Springer, 2017, pp. 367–381. date_created: 2018-12-11T11:47:34Z date_published: 2017-07-25T00:00:00Z date_updated: 2022-05-23T08:54:02Z day: '25' ddc: - '000' department: - _id: KrCh - _id: ToHe doi: 10.1007/978-3-319-63121-9_18 ec_funded: 1 editor: - first_name: Luca full_name: Aceto, Luca last_name: Aceto - first_name: Giorgio full_name: Bacci, Giorgio last_name: Bacci - first_name: Anna full_name: Ingólfsdóttir, Anna last_name: Ingólfsdóttir - first_name: Axel full_name: Legay, Axel last_name: Legay - first_name: Radu full_name: Mardare, Radu last_name: Mardare file: - access_level: open_access checksum: b2402766ec02c79801aac634bd8f9f6c content_type: application/pdf creator: dernst date_created: 2019-11-19T08:06:50Z date_updated: 2020-07-14T12:47:25Z file_id: '7048' file_name: 2017_ModelsAlgorithms_Chatterjee.pdf file_size: 192826 relation: main_file file_date_updated: 2020-07-14T12:47:25Z has_accepted_license: '1' intvolume: ' 10460' language: - iso: eng month: '07' oa: 1 oa_version: Submitted Version page: 367 - 381 project: - _id: 25F5A88A-B435-11E9-9278-68D0E5697425 call_identifier: FWF grant_number: S11402-N23 name: Moderne Concurrency Paradigms - _id: 25863FF4-B435-11E9-9278-68D0E5697425 call_identifier: FWF grant_number: S11407 name: Game Theory - _id: 25F42A32-B435-11E9-9278-68D0E5697425 call_identifier: FWF grant_number: Z211 name: The Wittgenstein Prize - _id: 2581B60A-B435-11E9-9278-68D0E5697425 call_identifier: FP7 grant_number: '279307' name: 'Quantitative Graph Games: Theory and Applications' - _id: 25892FC0-B435-11E9-9278-68D0E5697425 grant_number: ICT15-003 name: Efficient Algorithms for Computer Aided Verification publication: Models, Algorithms, Logics and Tools publication_identifier: isbn: - 978-3-319-63120-2 issn: - 0302-9743 publication_status: published publisher: Springer publist_id: '7170' quality_controlled: '1' scopus_import: '1' series_title: Theoretical Computer Science and General Issues status: public title: The cost of exactness in quantitative reachability type: book_chapter user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 10460 year: '2017' ... --- _id: '624' abstract: - lang: eng text: 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. acknowledgement: 'Austrian Science Fund (FWF): M1697, P22249; Swiss National Science Foundation (SNF): 145706; European Commission;FWF Special Research Program: RNA-REG F43' article_number: '3830' author: - first_name: Nela full_name: Nikolic, Nela id: 42D9CABC-F248-11E8-B48F-1D18A9856A87 last_name: Nikolic orcid: 0000-0001-9068-6090 - first_name: Zrinka full_name: Didara, Zrinka last_name: Didara - first_name: Isabella full_name: Moll, Isabella last_name: Moll citation: ama: Nikolic N, Didara Z, Moll I. MazF activation promotes translational heterogeneity of the grcA mRNA in Escherichia coli populations. PeerJ. 2017;2017(9). doi:10.7717/peerj.3830 apa: Nikolic, N., Didara, Z., & Moll, I. (2017). MazF activation promotes translational heterogeneity of the grcA mRNA in Escherichia coli populations. PeerJ. PeerJ. https://doi.org/10.7717/peerj.3830 chicago: Nikolic, Nela, Zrinka Didara, and Isabella Moll. “MazF Activation Promotes Translational Heterogeneity of the GrcA MRNA in Escherichia Coli Populations.” PeerJ. PeerJ, 2017. https://doi.org/10.7717/peerj.3830. ieee: N. Nikolic, Z. Didara, and I. Moll, “MazF activation promotes translational heterogeneity of the grcA mRNA in Escherichia coli populations,” PeerJ, vol. 2017, no. 9. PeerJ, 2017. ista: Nikolic N, Didara Z, Moll I. 2017. MazF activation promotes translational heterogeneity of the grcA mRNA in Escherichia coli populations. PeerJ. 2017(9), 3830. mla: Nikolic, Nela, et al. “MazF Activation Promotes Translational Heterogeneity of the GrcA MRNA in Escherichia Coli Populations.” PeerJ, vol. 2017, no. 9, 3830, PeerJ, 2017, doi:10.7717/peerj.3830. short: N. Nikolic, Z. Didara, I. Moll, PeerJ 2017 (2017). date_created: 2018-12-11T11:47:33Z date_published: 2017-09-21T00:00:00Z date_updated: 2021-01-12T08:06:48Z day: '21' ddc: - '579' department: - _id: CaGu doi: 10.7717/peerj.3830 file: - access_level: open_access checksum: 3d79ae6b6eabc90b0eaaed82ff3493b0 content_type: application/pdf creator: system date_created: 2018-12-12T10:11:51Z date_updated: 2020-07-14T12:47:24Z file_id: '4908' file_name: IST-2017-909-v1+1_peerj-3830.pdf file_size: 682064 relation: main_file file_date_updated: 2020-07-14T12:47:24Z has_accepted_license: '1' intvolume: ' 2017' issue: '9' language: - iso: eng month: '09' oa: 1 oa_version: Published Version publication: PeerJ publication_identifier: issn: - '21678359' publication_status: published publisher: PeerJ publist_id: '7172' pubrep_id: '909' quality_controlled: '1' scopus_import: 1 status: public title: MazF activation promotes translational heterogeneity of the grcA mRNA in Escherichia coli populations tmp: image: /images/cc_by.png legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0) short: CC BY (4.0) type: journal_article user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 2017 year: '2017' ... --- _id: '628' abstract: - lang: eng text: 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. alternative_title: - LNCS author: - first_name: Krishnendu full_name: Chatterjee, Krishnendu id: 2E5DCA20-F248-11E8-B48F-1D18A9856A87 last_name: Chatterjee orcid: 0000-0002-4561-241X - first_name: Hongfei full_name: Fu, Hongfei last_name: Fu - first_name: Aniket full_name: Murhekar, Aniket last_name: Murhekar citation: ama: 'Chatterjee K, Fu H, Murhekar A. Automated recurrence analysis for almost linear expected runtime bounds. In: Majumdar R, Kunčak V, eds. Vol 10426. Springer; 2017:118-139. doi:10.1007/978-3-319-63387-9_6' apa: 'Chatterjee, K., Fu, H., & Murhekar, A. (2017). Automated recurrence analysis for almost linear expected runtime bounds. In R. Majumdar & V. Kunčak (Eds.) (Vol. 10426, pp. 118–139). Presented at the CAV: Computer Aided Verification, Heidelberg, Germany: Springer. https://doi.org/10.1007/978-3-319-63387-9_6' chicago: Chatterjee, Krishnendu, Hongfei Fu, and Aniket Murhekar. “Automated Recurrence Analysis for Almost Linear Expected Runtime Bounds.” edited by Rupak Majumdar and Viktor Kunčak, 10426:118–39. Springer, 2017. https://doi.org/10.1007/978-3-319-63387-9_6. ieee: 'K. Chatterjee, H. Fu, and A. Murhekar, “Automated recurrence analysis for almost linear expected runtime bounds,” presented at the CAV: Computer Aided Verification, Heidelberg, Germany, 2017, vol. 10426, pp. 118–139.' ista: 'Chatterjee K, Fu H, Murhekar A. 2017. Automated recurrence analysis for almost linear expected runtime bounds. CAV: Computer Aided Verification, LNCS, vol. 10426, 118–139.' mla: Chatterjee, Krishnendu, et al. Automated Recurrence Analysis for Almost Linear Expected Runtime Bounds. Edited by Rupak Majumdar and Viktor Kunčak, vol. 10426, Springer, 2017, pp. 118–39, doi:10.1007/978-3-319-63387-9_6. short: K. Chatterjee, H. Fu, A. Murhekar, in:, R. Majumdar, V. Kunčak (Eds.), Springer, 2017, pp. 118–139. conference: end_date: 2017-07-28 location: Heidelberg, Germany name: 'CAV: Computer Aided Verification' start_date: 2017-07-24 date_created: 2018-12-11T11:47:35Z date_published: 2017-01-01T00:00:00Z date_updated: 2021-01-12T08:06:55Z day: '01' department: - _id: KrCh doi: 10.1007/978-3-319-63387-9_6 ec_funded: 1 editor: - first_name: Rupak full_name: Majumdar, Rupak last_name: Majumdar - first_name: Viktor full_name: Kunčak, Viktor last_name: Kunčak intvolume: ' 10426' language: - iso: eng main_file_link: - open_access: '1' url: https://arxiv.org/abs/1705.00314 month: '01' oa: 1 oa_version: Submitted Version page: 118 - 139 project: - _id: 25892FC0-B435-11E9-9278-68D0E5697425 grant_number: ICT15-003 name: Efficient Algorithms for Computer Aided Verification - _id: 25863FF4-B435-11E9-9278-68D0E5697425 call_identifier: FWF grant_number: S11407 name: Game Theory - _id: 2581B60A-B435-11E9-9278-68D0E5697425 call_identifier: FP7 grant_number: '279307' name: 'Quantitative Graph Games: Theory and Applications' publication_identifier: isbn: - 978-331963386-2 publication_status: published publisher: Springer publist_id: '7166' quality_controlled: '1' scopus_import: 1 status: public title: Automated recurrence analysis for almost linear expected runtime bounds type: conference user_id: 4435EBFC-F248-11E8-B48F-1D18A9856A87 volume: 10426 year: '2017' ...