Search Results - "Schaub, T"

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  1. 1

    Simplicial closure and higher-order link prediction by Benson, Austin R., Abebe, Rediet, Schaub, Michael T., Jadbabaie, Ali, Kleinberg, Jon

    “…Networks provide a powerful formalism for modeling complex systems by using a model of pairwise interactions. But much of the structure within these systems…”
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  2. 2

    Dirac signal processing of higher-order topological signals by Calmon, Lucille, Schaub, Michael T, Bianconi, Ginestra

    Published in New journal of physics (01-09-2023)
    “…Abstract Higher-order networks can sustain topological signals which are variables associated not only to the nodes, but also to the links, to the triangles…”
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  3. 3

    Markov dynamics as a zooming lens for multiscale community detection: non clique-like communities and the field-of-view limit by Schaub, Michael T, Delvenne, Jean-Charles, Yaliraki, Sophia N, Barahona, Mauricio

    Published in PloS one (27-02-2012)
    “…In recent years, there has been a surge of interest in community detection algorithms for complex networks. A variety of computational heuristics, some with a…”
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    Prediction of allosteric sites and mediating interactions through bond-to-bond propensities by Amor, B. R. C., Schaub, M. T., Yaliraki, S. N., Barahona, M.

    Published in Nature communications (26-08-2016)
    “…Allostery is a fundamental mechanism of biological regulation, in which binding of a molecule at a distant location affects the active site of a protein…”
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  6. 6

    Mapping the cardiac vascular niche in heart failure by Peisker, Fabian, Halder, Maurice, Nagai, James, Ziegler, Susanne, Kaesler, Nadine, Hoeft, Konrad, Li, Ronghui, Bindels, Eric M. J., Kuppe, Christoph, Moellmann, Julia, Lehrke, Michael, Stoppe, Christian, Schaub, Michael T., Schneider, Rebekka K., Costa, Ivan, Kramann, Rafael

    Published in Nature communications (31-05-2022)
    “…The cardiac vascular and perivascular niche are of major importance in homeostasis and during disease, but we lack a complete understanding of its cellular…”
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  7. 7

    The many facets of community detection in complex networks by Schaub, Michael T., Delvenne, Jean-Charles, Rosvall, Martin, Lambiotte, Renaud

    Published in Applied network science (2017)
    “…Community detection, the decomposition of a graph into essential building blocks, has been a core research topic in network science over the past years. Since…”
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  8. 8

    CrossTalkeR: analysis and visualization of ligand–receptorne tworks by Nagai, James S, Leimkühler, Nils B, Schaub, Michael T, Schneider, Rebekka K, Costa, Ivan G

    Published in Bioinformatics (Oxford, England) (18-11-2021)
    “…Abstract Motivation Ligand–receptor (LR) network analysis allows the characterization of cellular crosstalk based on single cell RNA-seq data. However, current…”
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  9. 9

    Encoding dynamics for multiscale community detection: Markov time sweeping for the map equation by Schaub, Michael T, Lambiotte, Renaud, Barahona, Mauricio

    “…The detection of community structure in networks is intimately related to finding a concise description of the network in terms of its modules. This notion has…”
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  10. 10

    Feasibility of organic micropollutant removal from municipal wastewaters by algal treatment vs. activated sludge treatment: Comparison based on non-targeted organic compound analysis by Delanka-Pedige, H.M.K., Ahmed, A., Schaub, T., Trainor, P., Nirmalakhandan, N.

    Published in Journal of environmental management (01-09-2024)
    “…Sustainability and life-cycle concerns about the conventional activated sludge (CAS) process for wastewater treatment have been driving the development of…”
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  11. 11

    Flow-Based Network Analysis of the Caenorhabditis elegans Connectome by Bacik, Karol A, Schaub, Michael T, Beguerisse-Díaz, Mariano, Billeh, Yazan N, Barahona, Mauricio

    Published in PLoS computational biology (01-08-2016)
    “…We exploit flow propagation on the directed neuronal network of the nematode C. elegans to reveal dynamically relevant features of its connectome. We find…”
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  12. 12

    Emergence of Slow-Switching Assemblies in Structured Neuronal Networks by Schaub, Michael T, Billeh, Yazan N, Anastassiou, Costas A, Koch, Christof, Barahona, Mauricio

    Published in PLoS computational biology (01-07-2015)
    “…Unraveling the interplay between connectivity and spatio-temporal dynamics in neuronal networks is a key step to advance our understanding of neuronal…”
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  13. 13

    Serum neurotrophins—A study on the time course and influencing factors in a large old age sample by Ziegenhorn, Andreas A, Schulte-Herbrüggen, Olaf, Danker-Hopfe, Heidi, Malbranc, Monique, Hartung, Heinz-Dieter, Anders, Dirk, Lang, Undine E, Steinhagen-Thiessen, Elisabeth, Schaub, Rainer T, Hellweg, Rainer

    Published in Neurobiology of aging (01-09-2007)
    “…Abstract The neurotrophins nerve growth factor (NGF) and brain-derived neurotrophic factor (BDNF) are important mediators of brain and neuronal development,…”
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  14. 14

    Improving the visibility of minorities through network growth interventions by Neuhäuser, Leonie, Karimi, Fariba, Bachmann, Jan, Strohmaier, Markus, Schaub, Michael T.

    Published in Communications physics (20-05-2023)
    “…Improving the position of minority groups in networks through interventions is a challenge of high theoretical and societal importance. However, a systematic…”
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  15. 15

    Boolean network identification from perturbation time series data combining dynamics abstraction and logic programming by Ostrowski, M., Paulevé, L., Schaub, T., Siegel, A., Guziolowski, C.

    Published in BioSystems (01-11-2016)
    “…Boolean networks (and more general logic models) are useful frameworks to study signal transduction across multiple pathways. Logic models can be learned from…”
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    Simulating systematic bias in attributed social networks and its effect on rankings of minority nodes by Neuhäuser, Leonie, Stamm, Felix I., Lemmerich, Florian, Schaub, Michael T., Strohmaier, Markus

    Published in Applied network science (02-11-2021)
    “…Network analysis provides powerful tools to learn about a variety of social systems. However, most analyses implicitly assume that the considered relational…”
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  18. 18

    SC3: consensus clustering of single-cell RNA-seq data by Kiselev, Vladimir Yu, Kirschner, Kristina, Schaub, Michael T, Andrews, Tallulah, Yiu, Andrew, Chandra, Tamir, Natarajan, Kedar N, Reik, Wolf, Barahona, Mauricio, Green, Anthony R, Hemberg, Martin

    Published in Nature methods (01-05-2017)
    “…Single-cell consensus clustering (SC3) provides user-friendly, robust and accurate cell clustering as well as downstream analysis for single-cell RNA-seq data…”
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  19. 19

    Urokinase Receptor uPAR Overexpression in Mouse Brain Stimulates the Migration of Neurons into the Cortex during Embryogenesis by Shmakova, A. A., Balatskiy, A. V., Kulebyakina, M. A., Schaub, T., Karagyaur, M. N., Kulebyakin, K. Yu, Rysenkova, K. D., Tarabykin, V. S., Tkachuk, V. A., Semina, E. V.

    “…The regulation of neuronal migration in the cerebral cortex during embryonic development is one of the most important but underinvestigated processes that…”
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  20. 20

    Simplicial Convolutional Filters by Yang, Maosheng, Isufi, Elvin, Schaub, Michael T., Leus, Geert

    “…We study linear filters for processing signals supported on abstract topological spaces modeled as simplicial complexes, which may be interpreted as…”
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