{ "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/2cfc101b70f797a96aef3f0d7590c1dbb/karstenkuritz", "tags" : [ "myown","Papers" ], "intraHash" : "cfc101b70f797a96aef3f0d7590c1dbb", "interHash" : "359271097c2635cb087fddaaa4cc30b0", "label" : "Reconstructing temporal and spatial dynamics in single-cell experiments", "user" : "karstenkuritz", "description" : "", "date" : "2019-07-10 13:47:02", "changeDate" : "2019-07-10 11:52:15", "count" : 1, "pub-type": "article", "journal": "bioRxiv","publisher":"Cold Spring Harbor Laboratory", "year": "2019", "url": "https://www.biorxiv.org/content/early/2019/07/09/697151", "author": [ "Karsten Kuritz","Daniela Stöhr","Daniela Maichl","Nadine Pollak","Markus Rehm","Frank Allgöwer" ], "authors": [ {"first" : "Karsten", "last" : "Kuritz"}, {"first" : "Daniela", "last" : "Stöhr"}, {"first" : "Daniela", "last" : "Maichl"}, {"first" : "Nadine", "last" : "Pollak"}, {"first" : "Markus", "last" : "Rehm"}, {"first" : "Frank", "last" : "Allgöwer"} ], "abstract": "Modern cytometry methods allow collecting complex, multi-dimensional data sets from heterogeneous cell populations at single-cell resolution. While methods exist to describe the progression and order of cellular processes from snapshots of such populations, these descriptions are limited to arbitrary pseudotime scales. Here we describe MAPiT, an universal transformation method that recovers real-time dynamics of cellular processes from pseudotime scales. As use cases, we applied MAPiT to two prominent problems in the flow-cytometric analysis of heterogeneous cell populations: (1) recovering the kinetics of cell cycle progression in unsynchronized and thus unperturbed cell populations, and (2) recovering the spatial arrangement of cells within multi-cellular spheroids prior to spheroid dissociation for cytometric analysis. Since MAPiT provides a theoretic basis for the relation of pseudotime values to real temporal and spatial scales, it can be used broadly in the analysis of cellular processes with snapshot data from heterogeneous cell populations.", "elocation-id" : "697151", "eprint" : "https://www.biorxiv.org/content/early/2019/07/09/697151.full.pdf", "doi" : "10.1101/697151", "bibtexKey": "Kuritz2019b" } , { "type" : "Publication", "id" : "https://puma.ub.uni-stuttgart.de/bibtex/2dc6668329bf0fa54dc4e8967e248209f/karstenkuritz", "tags" : [ "phase","cycle,","multi-agent","response","Papers","control,","ensemble","passivity,","systems,","cell" ], "intraHash" : "dc6668329bf0fa54dc4e8967e248209f", "interHash" : "e3f1dab84bb431dda8dd596a6f7091bc", "label" : "Ensemble control for cell cycle synchronization of heterogeneous cell populations", "user" : "karstenkuritz", "description" : "", "date" : "2019-02-07 21:34:03", "changeDate" : "2019-02-07 20:34:03", "count" : 4, "pub-type": "article", "journal": "IFAC-PapersOnLine", "year": "2018", "url": "http://www.sciencedirect.com/science/article/pii/S2405896318316938", "author": [ "K. Kuritz","D. Imig","M. Dyck","F. Allgöwer" ], "authors": [ {"first" : "K.", "last" : "Kuritz"}, {"first" : "D.", "last" : "Imig"}, {"first" : "M.", "last" : "Dyck"}, {"first" : "F.", "last" : "Allgöwer"} ], "volume": "51","number": "19","pages": "44 - 47","note": "7th Conference on Foundation of Systems Biology in Engineering FOSBE 2018", "issn" : "2405-8963", "doi" : "https://doi.org/10.1016/j.ifacol.2018.09.034", "bibtexKey": "Kuritz2018b" } , { "type" : "Publication", "id" : "https://puma.ub.uni-stuttgart.de/bibtex/2ca1a885c7cad3774b2e6fdae34f98e8d/karstenkuritz", "tags" : [ "Papers","Journal" ], "intraHash" : "ca1a885c7cad3774b2e6fdae34f98e8d", "interHash" : "086e0ae6d353fd2153f1ed5a5a905e94", "label" : "On the relationship between cell cycle analysis with ergodic principles\n and age-structured cell population models", "user" : "karstenkuritz", "description" : "", "date" : "2019-02-07 21:34:03", "changeDate" : "2019-02-07 20:34:03", "count" : 7, "pub-type": "article", "journal": "J. Theor. Biol.", "year": "2017", "url": "http://www.sciencedirect.com/science/article/pii/S0022519316304040", "author": [ "K. Kuritz","D. Stöhr","N. Pollak","F. Allgöwer" ], "authors": [ {"first" : "K.", "last" : "Kuritz"}, {"first" : "D.", "last" : "Stöhr"}, {"first" : "N.", "last" : "Pollak"}, {"first" : "F.", "last" : "Allgöwer"} ], "volume": "414","pages": "91-102","abstract": "Cyclic processes, in particular the cell cycle, are of great importance\n in cell biology. Continued improvement in cell population analysis\n methods like fluorescence microscopy, flow cytometry, CyTOF or single-cell\n omics made mathematical methods based on ergodic principles a powerful\n tool in studying these processes. In this paper, we establish the\n relationship between cell cycle analysis with ergodic principles\n and age structured population models. To this end, we describe the\n progression of a single cell through the cell cycle by a stochastic\n differential equation on a one dimensional manifold in the high dimensional\n dataspace of cell cycle markers. Given the assumption that the cell\n population is in a steady state, we derive transformation rules which\n transform the number density on the manifold to the steady state\n number density of age structured population models. Our theory facilitates\n the study of cell cycle dependent processes including local molecular\n events, cell death and cell division from high dimensional \"snapshot\"\n data. Ergodic analysis can in general be applied to every process\n that exhibits a steady state distribution. By combining ergodic analysis\n with age structured population models we furthermore provide the\n theoretic basis for extensions of ergodic principles to distribution\n that deviate from their steady state.", "issn" : "0022-5193", "pubtype" : "journal", "doi" : "10.1016/j.jtbi.2016.11.024", "bibtexKey": "ist:kuritz17a" } , { "type" : "Publication", "id" : "https://puma.ub.uni-stuttgart.de/bibtex/20840584cb921bda8eb4ed6c9f8e556b9/karstenkuritz", "tags" : [ "Book","Papers" ], "intraHash" : "0840584cb921bda8eb4ed6c9f8e556b9", "interHash" : "8ed270242da3970eb5f213886a225787", "label" : "Passivity-based ensemble control for cell cycle synchronization", "user" : "karstenkuritz", "description" : "", "date" : "2019-02-07 21:34:03", "changeDate" : "2019-02-07 20:42:05", "count" : 4, "pub-type": "incollection", "booktitle": "Emerg. Appl. Control Syst. Theory","publisher":"Springer International Publishing", "year": "2018", "url": "http://www.springer.com/de/book/9783319670676", "author": [ "Karsten Kuritz","Wolfgang Halter","Frank Allgöwer" ], "authors": [ {"first" : "Karsten", "last" : "Kuritz"}, {"first" : "Wolfgang", "last" : "Halter"}, {"first" : "Frank", "last" : "Allgöwer"} ], "editor": [ "Roberto Tempo","Stephen Yurkovich","Pradeep Misra" ], "editors": [ {"first" : "Roberto", "last" : "Tempo"}, {"first" : "Stephen", "last" : "Yurkovich"}, {"first" : "Pradeep", "last" : "Misra"} ], "abstract": "We investigate the problem of synchronizing a population of cellular os- cillators in their cell cycle. Restrictions on the observability and controllability of the population imposed by the nature of cell biology give rise to an ensemble control problem specified by finding a broadcast input based on the distribution of the popu- lation. We solve the problem by a passivity based control law which we derive from the reduced phase model representation of the population and the aim of sending the norm of the first circular moment to one. Furthermore, we present conditions on the phase response curve and circular moments of the population which are sufficient for synchronizing a population of cellular oscillators.", "isbn" : "978-3-319-67067-6", "bibtexKey": "Kuritz2018" } , { "type" : "Publication", "id" : "https://puma.ub.uni-stuttgart.de/bibtex/231e40685ab6fc28d6b46d7d20ede7d22/karstenkuritz", "tags" : [ "Papers","Journal" ], "intraHash" : "31e40685ab6fc28d6b46d7d20ede7d22", "interHash" : "524776986c183f3700da60a15adb5e50", "label" : "The circuit-breaking algorithm for monotone systems", "user" : "karstenkuritz", "description" : "", "date" : "2019-02-07 21:34:03", "changeDate" : "2019-02-07 20:34:03", "count" : 1, "pub-type": "article", "journal": "Math. Biosci.","publisher":"Elsevier Inc.", "year": "2017", "url": "http://dx.doi.org/10.1016/j.mbs.2016.09.002 http://linkinghub.elsevier.com/retrieve/pii/S002555641630147X", "author": [ "Caterina Thomaseth","Karsten Kuritz","Frank Allgöwer","Nicole Radde" ], "authors": [ {"first" : "Caterina", "last" : "Thomaseth"}, {"first" : "Karsten", "last" : "Kuritz"}, {"first" : "Frank", "last" : "Allgöwer"}, {"first" : "Nicole", "last" : "Radde"} ], "volume": "284","pages": "80--91", "file" : ":home/kk/MendelyBib/WatchFolder/1-s2.0-S002555641630147X-main.pdf:pdf", "issn" : "00255564", "doi" : "10.1016/j.mbs.2016.09.002", "bibtexKey": "Thomaseth2016" } , { "type" : "Publication", "id" : "https://puma.ub.uni-stuttgart.de/bibtex/2ee24311f62b2704e33bf0feb7bb2069a/karstenkuritz", "tags" : [ "law;ensemble","oscillators;Parkinson's","dynamics;biological","curve;phase","control","formulation;cellular","rhythms;feedback;neurophysiology;oscillations;oscillators;physiological","disease;cancer;heart","states;phase","distribution;Fourier","biology;emerging","response","system;regulatory","behavior;oscillatory","populations;phase","models;healthy","models;ensemble","controllability;cellular","Papers","distributions;population-level","mechanism;Oscillators;Sociology;Statistics;Controllability;Limit-cycles;Diseases;Orbits;Systems","diseases;phase","cancer;cellular","feedback","systems","systems;cellular","parameter","biophysics;circadian","applications;distributed","coefficients;oscillating" ], "intraHash" : "ee24311f62b2704e33bf0feb7bb2069a", "interHash" : "214a67cf1ccf0a66b1cdf33f6cd3a3c3", "label" : "Ensemble Controllability of Cellular Oscillators", "user" : "karstenkuritz", "description" : "", "date" : "2019-02-07 21:34:03", "changeDate" : "2019-02-07 20:34:03", "count" : 1, "pub-type": "article", "journal": "IEEE Control Systems Letters", "year": "2019", "url": "", "author": [ "K. Kuritz","S. Zeng","F. Allgöwer" ], "authors": [ {"first" : "K.", "last" : "Kuritz"}, {"first" : "S.", "last" : "Zeng"}, {"first" : "F.", "last" : "Allgöwer"} ], "volume": "3","number": "2","pages": "296-301", "issn" : "2475-1456", "doi" : "10.1109/LCSYS.2018.2870967", "bibtexKey": "kuritz18e" } ] }