Schlemmer, Alexander

[["dc.bibliographiccitation.journal","Frontiers in Physiology"],["dc.bibliographiccitation.volume","11"],["dc.contributor.author","Kottlarz, Inga"],["dc.contributor.author","Berg, Sebastian"],["dc.contributor.author","Toscano-Tejeida, Diana"],["dc.contributor.author","Steinmann, Iris"],["dc.contributor.author","Bähr, Mathias"],["dc.contributor.author","Luther, Stefan"],["dc.contributor.author","Wilke, Melanie"],["dc.contributor.author","Parlitz, Ulrich"],["dc.contributor.author","Schlemmer, Alexander"],["dc.date.accessioned","2021-04-14T08:29:50Z"],["dc.date.available","2021-04-14T08:29:50Z"],["dc.date.issued","2021"],["dc.description.abstract","In this study, ordinal pattern analysis and classical frequency-based EEG analysis methods are used to differentiate between EEGs of different age groups as well as individuals. As characteristic features, functional connectivity as well as single-channel measures in both the time and frequency domain are considered. We compare the separation power of each feature set after nonlinear dimensionality reduction using t-distributed stochastic neighbor embedding and demonstrate that ordinal pattern-based measures yield results comparable to frequency-based measures applied to preprocessed data, and outperform them if applied to raw data. Our analysis yields no significant differences in performance between single-channel features and functional connectivity features regarding the question of age group separation."],["dc.identifier.doi","10.3389/fphys.2020.614565"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/82999"],["dc.language.iso","en"],["dc.notes.intern","DOI Import GROB-399"],["dc.publisher","Frontiers Media S.A."],["dc.relation.eissn","1664-042X"],["dc.rights","http://creativecommons.org/licenses/by/4.0/"],["dc.title","Extracting Robust Biomarkers From Multichannel EEG Time Series Using Nonlinear Dimensionality Reduction Applied to Ordinal Pattern Statistics and Spectral Quantities"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.artnumber","21"],["dc.bibliographiccitation.issue","1"],["dc.bibliographiccitation.journal","The Astrophysical Journal Supplement Series"],["dc.bibliographiccitation.volume","199"],["dc.contributor.author","Wakelam, V."],["dc.contributor.author","Herbst, E."],["dc.contributor.author","Loison, J.-C."],["dc.contributor.author","Smith, I. W. M."],["dc.contributor.author","Chandrasekaran, V."],["dc.contributor.author","Pavone, B."],["dc.contributor.author","Adams, N. G."],["dc.contributor.author","Bacchus-Montabonel, M.-C."],["dc.contributor.author","Bergeat, A."],["dc.contributor.author","Beroff, K."],["dc.contributor.author","Bierbaum, Veronica M."],["dc.contributor.author","Chabot, M."],["dc.contributor.author","Dalgarno, A."],["dc.contributor.author","van Dishoeck, E. F."],["dc.contributor.author","Faure, A."],["dc.contributor.author","Geppert, W. D."],["dc.contributor.author","Gerlich, D."],["dc.contributor.author","Galli, Daniele"],["dc.contributor.author","Hebrard, E. M."],["dc.contributor.author","Hersant, F."],["dc.contributor.author","Hickson, K. M."],["dc.contributor.author","Honvault, P."],["dc.contributor.author","Klippenstein, S. J."],["dc.contributor.author","Le Picard, S."],["dc.contributor.author","Nyman, G."],["dc.contributor.author","Pernot, P."],["dc.contributor.author","Schlemmer, S."],["dc.contributor.author","Selsis, F."],["dc.contributor.author","Sims, I. R."],["dc.contributor.author","Talbi, D."],["dc.contributor.author","Tennyson, Jonathan"],["dc.contributor.author","Troe, Juergen"],["dc.contributor.author","Wester, R."],["dc.contributor.author","Wiesenfeld, L."],["dc.date.accessioned","2018-11-07T09:12:53Z"],["dc.date.available","2018-11-07T09:12:53Z"],["dc.date.issued","2012"],["dc.description.abstract","We present a novel chemical database for gas-phase astrochemistry. Named the KInetic Database for Astrochemistry (KIDA), this database consists of gas-phase reactions with rate coefficients and uncertainties that will be vetted to the greatest extent possible. Submissions of measured and calculated rate coefficients are welcome, and will be studied by experts before inclusion into the database. Besides providing kinetic information for the interstellar medium, KIDA is planned to contain such data for planetary atmospheres and for circumstellar envelopes. Each year, a subset of the reactions in the database (kida.uva) will be provided as a network for the simulation of the chemistry of dense interstellar clouds with temperatures between 10 K and 300 K. We also provide a code, named Nahoon, to study the time-dependent gas-phase chemistry of zero-dimensional and one-dimensional interstellar sources."],["dc.identifier.doi","10.1088/0067-0049/199/1/21"],["dc.identifier.isi","000301119800021"],["dc.identifier.purl","https://resolver.sub.uni-goettingen.de/purl?gs-1/9093"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/27049"],["dc.notes.intern","Merged from goescholar"],["dc.notes.status","zu prüfen"],["dc.notes.submitter","Najko"],["dc.publisher","Iop Publishing Ltd"],["dc.relation","info:eu-repo/grantAgreement/EC/FP7/239108/EU//VAMDC"],["dc.relation.issn","0067-0049"],["dc.relation.orgunit","Fakultät für Physik"],["dc.title","A KINETIC DATABASE FOR ASTROCHEMISTRY (KIDA)"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.peerReviewed","yes"],["dc.type.status","published"],["dc.type.version","published_version"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","83"],["dc.bibliographiccitation.issue","2"],["dc.bibliographiccitation.journal","Data"],["dc.bibliographiccitation.volume","4"],["dc.contributor.author","Fitschen, Timm"],["dc.contributor.author","Schlemmer, Alexander"],["dc.contributor.author","Hornung, Daniel"],["dc.contributor.author","tom Wörden, Henrik"],["dc.contributor.author","Parlitz, Ulrich"],["dc.contributor.author","Luther, Stefan"],["dc.date.accessioned","2020-12-10T18:47:01Z"],["dc.date.available","2020-12-10T18:47:01Z"],["dc.date.issued","2019"],["dc.description.abstract","Here we present CaosDB, a Research Data Management System (RDMS) designed to ensure seamless integration of inhomogeneous data sources and repositories of legacy data. Its primary purpose is the management of data from biomedical sciences, both from simulations and experiments during the complete research data lifecycle. An RDMS for this domain faces particular challenges: Research data arise in huge amounts, from a wide variety of sources, and traverse a highly branched path of further processing. To be accepted by its users, an RDMS must be built around workflows of the scientists and practices and thus support changes in workflow and data structure. Nevertheless it should encourage and support the development and observation of standards and furthermore facilitate the automation of data acquisition and processing with specialized software. The storage data model of an RDMS must reflect these complexities with appropriate semantics and ontologies while offering simple methods for finding, retrieving, and understanding relevant data. We show how CaosDB responds to these challenges and give an overview of the CaosDB Server, its data model and its easy-to-learn CaosDB Query Language. We briefly discuss the status of the implementation, how we currently use CaosDB, and how we plan to use and extend it."],["dc.identifier.doi","10.3390/data4020083"],["dc.identifier.purl","https://resolver.sub.uni-goettingen.de/purl?gs-1/16675"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/78611"],["dc.identifier.url","https://sfb1002.med.uni-goettingen.de/production/literature/publications/275"],["dc.language.iso","en"],["dc.notes","GRO-Red/ SW 8.5.2020: Geprüft. Keine Anpassung erforderlich, da Preprint im Volltext verfügbar."],["dc.notes.intern","DOI Import GROB-354"],["dc.notes.intern","Merged from goescholar"],["dc.notes.intern","Merged from goescholar"],["dc.notes.status","final"],["dc.relation","SFB 1002: Modulatorische Einheiten bei Herzinsuffizienz"],["dc.relation","SFB 1002 | C03: Erholung nach Herzinsuffizienz: Analyse der transmuralen mechano-elektrischen Funktionsstörung"],["dc.relation.eissn","2306-5729"],["dc.relation.orgunit","Fakultät für Physik"],["dc.relation.workinggroup","RG Luther (Biomedical Physics)"],["dc.rights","CC BY 4.0"],["dc.rights.uri","https://creativecommons.org/licenses/by/4.0/"],["dc.title","CaosDB—Research Data Management for Complex, Changing, and Automated Research Workflows"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.subtype","original_ja"],["dc.type.version","published_version"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.journal","Frontiers in Physics"],["dc.bibliographiccitation.volume","6"],["dc.contributor.author","Schlemmer, Alexander"],["dc.contributor.author","Berg, Sebastian"],["dc.contributor.author","Lilienkamp, Thomas"],["dc.contributor.author","Luther, Stefan"],["dc.contributor.author","Parlitz, Ulrich"],["dc.date.accessioned","2020-12-10T18:44:37Z"],["dc.date.available","2020-12-10T18:44:37Z"],["dc.date.issued","2018"],["dc.description.abstract","Permutation entropy (PE) is a robust quantity for measuring the complexity of time series. In the cardiac community it is predominantly used in the context of electrocardiogram (ECG) signal analysis for diagnoses and predictions with a major application found in heart rate variability parameters. In this article we are combining spatial and temporal PE to form a spatiotemporal PE that captures both, complexity of spatial structures and temporal complexity at the same time. We demonstrate that the spatiotemporal PE (STPE) quantifies complexity using two datasets from simulated cardiac arrhythmia and compare it to phase singularity analysis and spatial PE (SPE). These datasets simulate ventricular fibrillation (VF) on a two-dimensional and a three-dimensional medium using the Fenton-Karma model. We show that SPE and STPE are robust against noise and demonstrate its usefulness for extracting complexity features at different spatial scales."],["dc.identifier.doi","10.3389/fphy.2018.00039"],["dc.identifier.eissn","2296-424X"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/78528"],["dc.language.iso","en"],["dc.notes.intern","DOI Import GROB-354"],["dc.publisher","Frontiers Media S.A."],["dc.relation.eissn","2296-424X"],["dc.rights","http://creativecommons.org/licenses/by/4.0/"],["dc.title","Spatiotemporal Permutation Entropy as a Measure for Complexity of Cardiac Arrhythmia"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","950"],["dc.bibliographiccitation.issue","3"],["dc.bibliographiccitation.journal","Entropy"],["dc.bibliographiccitation.lastpage","967"],["dc.bibliographiccitation.volume","17"],["dc.contributor.author","Schlemmer, Alexander"],["dc.contributor.author","Berg, Sebastian"],["dc.contributor.author","Shajahan, T. K."],["dc.contributor.author","Luther, Stefan"],["dc.contributor.author","Parlitz, Ulrich"],["dc.date.accessioned","2018-11-07T10:00:06Z"],["dc.date.available","2018-11-07T10:00:06Z"],["dc.date.issued","2015"],["dc.description.abstract","The characterization of spatiotemporal complexity remains a challenging task. This holds in particular for the analysis of data from fluorescence imaging (optical mapping), which allows for the measurement of membrane potential and intracellular calcium at high spatial and temporal resolutions and, therefore, allows for an investigation of cardiac dynamics. Dominant frequency maps and the analysis of phase singularities are frequently used for this type of excitable media. These methods address some important aspects of cardiac dynamics; however, they only consider very specific properties of excitable media. To extend the scope of the analysis, we present a measure based on entropy rates for determining spatiotemporal complexity patterns of excitable media. Simulated data generated by the Aliev-Panfilov model and the cubic Barkley model are used to validate this method. Then, we apply it to optical mapping data from monolayers of cardiac cells from chicken embryos and compare our findings with dominant frequency maps and the analysis of phase singularities. The studies indicate that entropy rate maps provide additional information about local complexity, the origins of wave breakup and the development of patterns governing unstable wave propagation."],["dc.identifier.doi","10.3390/e17030950"],["dc.identifier.isi","000352612500003"],["dc.identifier.purl","https://resolver.sub.uni-goettingen.de/purl?gs-1/11891"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/37726"],["dc.identifier.url","https://sfb1002.med.uni-goettingen.de/production/literature/publications/83"],["dc.notes.intern","Merged from goescholar"],["dc.notes.status","zu prüfen"],["dc.notes.submitter","Najko"],["dc.relation","info:eu-repo/grantAgreement/EC/FP7/241526/EU//EUTRIGTREAT"],["dc.relation","SFB 1002: Modulatorische Einheiten bei Herzinsuffizienz"],["dc.relation","SFB 1002 | C03: Erholung nach Herzinsuffizienz: Analyse der transmuralen mechano-elektrischen Funktionsstörung"],["dc.relation.issn","1099-4300"],["dc.relation.orgunit","Fakultät für Physik"],["dc.relation.workinggroup","RG Luther (Biomedical Physics)"],["dc.rights","CC BY 4.0"],["dc.title","Entropy Rate Maps of Complex Excitable Dynamics in Cardiac Monolayers"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.peerReviewed","yes"],["dc.type.subtype","original_ja"],["dc.type.version","published_version"],["dspace.entity.type","Publication"]]