{ "types" : { "Bookmark" : { "pluralLabel" : "Bookmarks" }, "Publication" : { "pluralLabel" : "Publications" }, "GoldStandardPublication" : { "pluralLabel" : "GoldStandardPublications" }, "GoldStandardBookmark" : { "pluralLabel" : "GoldStandardBookmarks" }, "Tag" : { "pluralLabel" : "Tags" }, "User" : { "pluralLabel" : "Users" }, "Group" : { "pluralLabel" : "Groups" }, "Sphere" : { "pluralLabel" : "Spheres" } }, "properties" : { "count" : { "valueType" : "number" }, "date" : { "valueType" : "date" }, "changeDate" : { "valueType" : "date" }, "url" : { "valueType" : "url" }, "id" : { "valueType" : "url" }, "tags" : { "valueType" : "item" }, "user" : { "valueType" : "item" } }, "items" : [ { "type" : "Publication", "id" : "https://puma.ub.uni-stuttgart.de/bibtex/2914b28984ce3968cdbc7ec5dd537b16f/simtech", "tags" : [ "EXC2075","PN2","PN2-9","curated" ], "intraHash" : "914b28984ce3968cdbc7ec5dd537b16f", "interHash" : "e28d46677fd5e50b334e2cc620cd3c5c", "label" : "Marginal Percentile Intervals in Bayesian Inference are Overconfident", "user" : "simtech", "description" : "", "date" : "2024-07-17 11:38:30", "changeDate" : "2024-07-19 15:09:42", "count" : 9, "pub-type": "article", "journal": "IFAC-PapersOnLine", "year": "2024", "url": "", "author": [ "Sebastian Höpfl","Hans-Michael Tautenhahn","Vincent Wagner","Nicole Erika Radde" ], "authors": [ {"first" : "Sebastian", "last" : "Höpfl"}, {"first" : "Hans-Michael", "last" : "Tautenhahn"}, {"first" : "Vincent", "last" : "Wagner"}, {"first" : "Nicole Erika", "last" : "Radde"} ], "bibtexKey": "Hoepfl2024FOSBE" } , { "type" : "Publication", "id" : "https://puma.ub.uni-stuttgart.de/bibtex/22b0d6952a32448eb9fa75cc34c4501bd/simtech", "tags" : [ "EXC2075","PN2","PN2-1B","PN2-9","PN4","PN4-2(II)","curated" ], "intraHash" : "2b0d6952a32448eb9fa75cc34c4501bd", "interHash" : "b962c410c4ef09d96fa6fc22ed1e81f9", "label" : "A provably convergent control closure scheme for the Method of Moments of the Chemical Master Equation", "user" : "simtech", "description" : "", "date" : "2024-01-10 08:47:36", "changeDate" : "2024-07-17 11:35:27", "count" : 6, "pub-type": "article", "journal": "Journal of Chemical Theory and Computation","publisher":"ACS Publications", "year": "2023", "url": "https://pubs.acs.org/doi/full/10.1021/acs.jctc.3c00548", "author": [ "Vincent Wagner","Robin Strässer","Frank Allgöwer","Nicole Erika Radde" ], "authors": [ {"first" : "Vincent", "last" : "Wagner"}, {"first" : "Robin", "last" : "Strässer"}, {"first" : "Frank", "last" : "Allgöwer"}, {"first" : "Nicole Erika", "last" : "Radde"} ], "volume": "19","number": "24","pages": "9049\u20139059","abstract": "In this article, we introduce a novel moment closure scheme based on concepts from Model Predictive Control (MPC) to accurately describe the time evolution of the statistical moments of the solution of the Chemical Master Equation (CME). The Method of Moments, a set of ordinary differential equations frequently used to consider the first nm moments, is generally not closed since lower-order moments depend on higher-order moments. To overcome this limitation, we interpret the moment equations as a nonlinear dynamical system, where the first nm moments serve as states and the closing moments serve as control input. We demonstrate the efficacy of our approach using two example systems and show that it outperforms existing closure schemes. For polynomial systems, which encompass all mass-action systems, we provide probability bounds for the error between true and estimated moment trajectories. We achieve this by combining convergence properties of a priori moment estimates from stochastic simulations with guarantees for nonlinear reference tracking MPC. Our proposed method offers an effective solution to accurately predict the time evolution of moments of the CME, which has wide-ranging implications for many fields, including biology, chemistry, and engineering.Competing Interest StatementThe authors have declared no competing interest.", "elocation-id" : "2023.05.03.539185", "eprint" : "https://www.biorxiv.org/content/early/2023/05/03/2023.05.03.539185.full.pdf", "preprinturl" : "https://www.biorxiv.org/content/10.1101/2023.05.03.539185v2", "doi" : "https://doi.org/10.1021/acs.jctc.3c00548", "bibtexKey": "Wagner23b" } , { "type" : "Publication", "id" : "https://puma.ub.uni-stuttgart.de/bibtex/2d9f50320acfea6c088804d94af731c83/simtech", "tags" : [ "EXC2075","PN2","PN2-1B","PN2-9","curated" ], "intraHash" : "d9f50320acfea6c088804d94af731c83", "interHash" : "61d8f0a594585ba150702cb0b6fc9537", "label" : "The impossible challenge of estimating non-existent moments of the Chemical Master Equation", "user" : "simtech", "description" : "", "date" : "2023-11-24 10:02:54", "changeDate" : "2023-12-06 08:55:18", "count" : 7, "pub-type": "article", "journal": "Bioinformatics", "year": "2023", "url": "https://doi.org/10.1093/bioinformatics/btad205", "author": [ "Vincent Wagner","Nicole Radde" ], "authors": [ {"first" : "Vincent", "last" : "Wagner"}, {"first" : "Nicole", "last" : "Radde"} ], "volume": "39","number": "Supplement_1","pages": "i440-i447","abstract": "The Chemical Master Equation (CME) is a set of linear differential equations that describes the evolution of the probability distribution on all possible configurations of a (bio-)chemical reaction system. Since the number of configurations and therefore the dimension of the CME rapidly increases with the number of molecules, its applicability is restricted to small systems. A widely applied remedy for this challenge is moment-based approaches which consider the evolution of the first few moments of the distribution as summary statistics for the complete distribution. Here, we investigate the performance of two moment-estimation methods for reaction systems whose equilibrium distributions encounter fat-tailedness and do not possess statistical moments.We show that estimation via stochastic simulation algorithm (SSA) trajectories lose consistency over time and estimated moment values span a wide range of values even for large sample sizes. In comparison, the method of moments returns smooth moment estimates but is not able to indicate the non-existence of the allegedly predicted moments. We furthermore analyze the negative effect of a CME solution\u2019s fat-tailedness on SSA run times and explain inherent difficulties. While moment-estimation techniques are a commonly applied tool in the simulation of (bio-)chemical reaction networks, we conclude that they should be used with care, as neither the system definition nor the moment-estimation techniques themselves reliably indicate the potential fat-tailedness of the CME\u2019s solution.", "eprint" : "https://academic.oup.com/bioinformatics/article-pdf/39/Supplement\\_1/i440/50741574/btad205.pdf", "issn" : "1367-4811", "doi" : "10.1093/bioinformatics/btad205", "bibtexKey": "10.1093/bioinformatics/btad205" } , { "type" : "Publication", "id" : "https://puma.ub.uni-stuttgart.de/bibtex/27403c5cb23934cb023a093a112159e33/simtech", "tags" : [ "EXC2075","PN2","PN2-1B","PN2-9","PN5","PN5-10","curated","merged" ], "intraHash" : "7403c5cb23934cb023a093a112159e33", "interHash" : "fe90285268ac4259ff314c0a96bc7c1e", "label" : "Quasi-Entropy Closure: A Fast and Reliable Approach to Close the Moment Equations of the Chemical Master Equation", "user" : "simtech", "description" : "", "date" : "2023-07-18 10:12:52", "changeDate" : "2024-02-26 18:00:29", "count" : 10, "pub-type": "article", "journal": "Bioinformatics","publisher":"Oxford University Press", "year": "2022", "url": "", "author": [ "Vincent Wagner","Benjamin Castellaz","Marco Oesting","Nicole Radde" ], "authors": [ {"first" : "Vincent", "last" : "Wagner"}, {"first" : "Benjamin", "last" : "Castellaz"}, {"first" : "Marco", "last" : "Oesting"}, {"first" : "Nicole", "last" : "Radde"} ], "volume": "38","number": "18","pages": "4352-4359", "research-areas" : "Biochemistry & Molecular Biology; Biotechnology & Applied\r\n Microbiology; Computer Science; Mathematical & Computational Biology;\r\n Mathematics", "language" : "eng", "issn" : "1367-4803 and 1460-2059", "affiliation" : "Radde, N (Corresponding Author), Univ Stuttgart, Inst Syst Theory & Automat Control, D-70569 Stuttgart, Germany.\r\n Radde, N (Corresponding Author), Univ Stuttgart, Stuttgart Ctr Simulat Sci, D-70569 Stuttgart, Germany.\r\n Wagner, Vincent; Castellaz, Benjamin; Radde, Nicole, Univ Stuttgart, Inst Syst Theory & Automat Control, D-70569 Stuttgart, Germany.\r\n Oesting, Marco; Radde, Nicole, Univ Stuttgart, Stuttgart Ctr Simulat Sci, D-70569 Stuttgart, Germany.\r\n Oesting, Marco, Univ Stuttgart, Inst Stochast & Applicat, D-70569 Stuttgart, Germany.", "orcid-numbers" : "Radde, Nicole/0000-0002-5145-0058", "unique-id" : "WOS:000835769300001", "doi" : "10.1093/bioinformatics/btac501", "bibtexKey": "wagner2022quasientropy" } , { "type" : "Publication", "id" : "https://puma.ub.uni-stuttgart.de/bibtex/272685ada0a757dc05ab1b5fa58b99618/simtech", "tags" : [ "PN2","PN2-9","curated","EXC2075","PN2-1B" ], "intraHash" : "72685ada0a757dc05ab1b5fa58b99618", "interHash" : "197f90c0c0bb391aa2620bd0a1d81f0f", "label" : "An inverse transformation algorithm to infer parameter distributions from population snapshot data", "user" : "simtech", "description" : "", "date" : "2023-02-10 16:05:03", "changeDate" : "2024-07-17 10:24:15", "count" : 7, "pub-type": "article", "journal": "IFAC-PapersOnLine", "year": "2022", "url": "https://www.sciencedirect.com/science/article/pii/S240589632300023X", "author": [ "Vincent Wagner","Sebastian Höpfl","Viviane Klingel","Maria C. Pop","Nicole E. Radde" ], "authors": [ {"first" : "Vincent", "last" : "Wagner"}, {"first" : "Sebastian", "last" : "Höpfl"}, {"first" : "Viviane", "last" : "Klingel"}, {"first" : "Maria C.", "last" : "Pop"}, {"first" : "Nicole E.", "last" : "Radde"} ], "editor": [ "Ioannis P. Androulakis Maria Klapa, Daniel P. Howsmon" ], "editors": [ {"first" : "Ioannis P. Androulakis", "last" : "Maria Klapa, Daniel P. Howsmon"} ], "volume": "55","number": "23","pages": "86-91","note": "9th IFAC Conference on Foundations of Systems Biology in Engineering FOSBE 2022","abstract": "Population snapshot data can be used to study heterogeneity in cell populations. Various approaches to integrating such data into computational models have been published, which enable new treatment strategies for cancer therapy, by exploiting the intra-tumor heterogeneity. A precision medicine approach for the cure of cancer could benefit from the combination of single-cell data and respective analytical methods. Here, we introduce the inverse transformation algorithm, which transforms population snapshot data to parameter distributions that are consistent with the underlying data given a dynamic model with distributed parameters. Therefore, it enables the assessment of the heterogeneity in and behavior of the whole underlying cell population. In contrast to the frequently used Approximate Bayesian Computation methods for population matching, our algorithm is a non-parametric likelihood-free approach. It directly computes a density function value for a single parameter based on density transformation methods. If the model can be described as a one-to-one map that invertibly maps parameters to measurable outputs, the inverse transformation algorithm asymptotically returns the true underlying parameter distribution. The inverse transformation algorithm is applied to snapshot data simulated via standard differential equation models for biochemical reaction networks. In particular, we evaluate our algorithm on two small test-bed models and discuss advantages and limitations in comparison to other existing approaches.", "issn" : "2405-8963", "doi" : "https://doi.org/10.1016/j.ifacol.2023.01.020", "bibtexKey": "wagner22b" } , { "type" : "Publication", "id" : "https://puma.ub.uni-stuttgart.de/bibtex/25e45f9dc6df58c3b0f6d032cf7df8256/simtech", "tags" : [ "EXC2075","PN2","PN2-1B","PN2-9","curated" ], "intraHash" : "5e45f9dc6df58c3b0f6d032cf7df8256", "interHash" : "5320c9003ba9ed050866adf74c57590d", "label" : "DNA sequence-dependent activity and base flipping mechanisms of DNMT1 regulate genome-wide DNA methylation", "user" : "simtech", "description" : "", "date" : "2021-12-02 15:44:10", "changeDate" : "2023-12-06 08:55:18", "count" : 11, "pub-type": "article", "journal": "Nat. Communications","publisher":"Springer Science and Business Media LLC", "year": "2020", "url": "", "author": [ "S. Adam","H. Anteneh","M. Hornisch","V. Wagner","J. Lu","N. Radde","P. Bashtrykov","J. Song","A. Jeltsch" ], "authors": [ {"first" : "S.", "last" : "Adam"}, {"first" : "H.", "last" : "Anteneh"}, {"first" : "M.", "last" : "Hornisch"}, {"first" : "V.", "last" : "Wagner"}, {"first" : "J.", "last" : "Lu"}, {"first" : "N.", "last" : "Radde"}, {"first" : "P.", "last" : "Bashtrykov"}, {"first" : "J.", "last" : "Song"}, {"first" : "A.", "last" : "Jeltsch"} ], "volume": "11","number": "1","pages": "1-15", "doi" : "10.1038/s41467-020-17531-8", "bibtexKey": "ist:wagner20a" } , { "type" : "Publication", "id" : "https://puma.ub.uni-stuttgart.de/bibtex/2e515ca746bbec0fca63811eff6251f82/simtech", "tags" : [ "EXC2075","PN2","PN2-1B","PN2-9","curated" ], "intraHash" : "e515ca746bbec0fca63811eff6251f82", "interHash" : "8a58a544fbc3bed778460782291015f5", "label" : "SiCaSMA: An Alternative Stochastic Description via Concatenation of Markov Processes for a Class of Catalytic Systems", "user" : "simtech", "description" : "", "date" : "2021-12-02 15:10:43", "changeDate" : "2023-12-06 08:55:18", "count" : 9, "pub-type": "article", "journal": "Mathematics","publisher":"MDPI", "year": "2021", "url": "", "author": [ "V. Wagner","N. Radde" ], "authors": [ {"first" : "V.", "last" : "Wagner"}, {"first" : "N.", "last" : "Radde"} ], "volume": "9","pages": "1074", "doi" : "10.3390/math9101074", "bibtexKey": "ist:wagner21a" } ] }