The Experts below are selected from a list of 23280 Experts worldwide ranked by ideXlab platform

Yohanns Bellaiche - One of the best experts on this subject based on the ideXlab platform.

  • mitotic spindle orientation in asymmetric and symmetric Cell divisions during animal development
    2011
    Co-Authors: Xavier Morin, Yohanns Bellaiche
    Abstract:

    The orientation of the mitotic spindle has been proposed to Control Cell Fate choices, tissue architecture, and tissue morphogenesis. Here, we review the mechanisms regulating the orientation of the axis of division and Cell Fate choices in classical models of asymmetric Cell division. We then discuss the mechanisms of mitotic spindle orientation in symmetric Cell divisions and its possible implications in tissue morphogenesis. Many recent studies show that future advances in the field of mitotic spindle orientation will arise from combinations of physical perturbation and modeling with classical genetics and developmental biology approaches.

Xavier Morin - One of the best experts on this subject based on the ideXlab platform.

  • mitotic spindle orientation in asymmetric and symmetric Cell divisions during animal development
    2011
    Co-Authors: Xavier Morin, Yohanns Bellaiche
    Abstract:

    The orientation of the mitotic spindle has been proposed to Control Cell Fate choices, tissue architecture, and tissue morphogenesis. Here, we review the mechanisms regulating the orientation of the axis of division and Cell Fate choices in classical models of asymmetric Cell division. We then discuss the mechanisms of mitotic spindle orientation in symmetric Cell divisions and its possible implications in tissue morphogenesis. Many recent studies show that future advances in the field of mitotic spindle orientation will arise from combinations of physical perturbation and modeling with classical genetics and developmental biology approaches.

Peter K Sorger - One of the best experts on this subject based on the ideXlab platform.

  • inferring reaction network structure from single Cell multiplex data using toric systems theory
    2019
    Co-Authors: Shu Wang, Eduardo D Sontag, Peter K Sorger
    Abstract:

    The goal of many single-Cell studies on eukaryotic Cells is to gain insight into the biochemical reactions that Control Cell Fate and state. In this paper we introduce the concept of Effective Stoichiometric Spaces (ESS) to guide the reconstruction of biochemical networks from multiplexed, fixed time-point, single-Cell data. In contrast to methods based solely on statistical models of data, the ESS method leverages the power of the geometric theory of toric varieties to begin unraveling the structure of chemical reaction networks (CRN). This application of toric theory enables a data-driven mapping of covariance relationships in single-Cell measurements into stoichiometric information, one in which each Cell subpopulation has its associated ESS interpreted in terms of CRN theory. In the development of ESS we reframe certain aspects of the theory of CRN to better match data analysis. As an application of our approach we process cytomery- and image-based single-Cell datasets and identify differences in Cells treated with kinase inhibitors. Our approach is directly applicable to data acquired using readily accessible experimental methods such as Fluorescence Activated Cell Sorting (FACS) and multiplex immunofluorescence.

  • inferring reaction network structure from single Cell multiplex data using toric systems theory
    2019
    Co-Authors: Shu Wang, Eduardo D Sontag, Peter K Sorger
    Abstract:

    Abstract The goal of many single-Cell studies on eukaryotic Cells is to gain insight into the biochemical reactions that Control Cell Fate and state. In this paper we introduce the concept of effective stoichiometric space (ESS) to guide the reconstruction of biochemical networks from multiplexed, fixed time-point, single-Cell data. In contrast to methods based solely on statistical models of data, the ESS method leverages the power of the geometric theory of toric varieties to begin unraveling the structure of chemical reaction networks (CRN). This application of toric theory enables a data-driven mapping of covariance relationships in single Cell measurements into stoichiometric information, one in which each Cell subpopulation has its associated ESS interpreted in terms of CRN theory. In the development of ESS we reframe certain aspects of the theory of CRN to better match data analysis. As an application of our approach we process cytomery- and image-based single-Cell datasets and identify differences in Cells treated with kinase inhibitors. Our approach is directly applicable to data acquired using readily accessible experimental methods such as Fluorescence Activated Cell Sorting (FACS) and multiplex immunofluorescence. Author summary We introduce a new notion, which we call the effective stoichiometric space (ESS), that elucidates network structure from the covariances of single-Cell multiplexed data. The ESS approach differs from methods that are based on purely statistical models of data: it allows a completely new and data-driven translation of the theory of toric varieties in geometry and specifically their role in chemical reaction networks (CRN). In the process, we reframe certain aspects of the theory of CRN. As illustrations of our approach, we find stoichiometry in different single-Cell datasets, and pinpoint dose-dependence of network perturbations in drug-treated Cells.

Eduardo D Sontag - One of the best experts on this subject based on the ideXlab platform.

  • inferring reaction network structure from single Cell multiplex data using toric systems theory
    2019
    Co-Authors: Shu Wang, Eduardo D Sontag, Peter K Sorger
    Abstract:

    The goal of many single-Cell studies on eukaryotic Cells is to gain insight into the biochemical reactions that Control Cell Fate and state. In this paper we introduce the concept of Effective Stoichiometric Spaces (ESS) to guide the reconstruction of biochemical networks from multiplexed, fixed time-point, single-Cell data. In contrast to methods based solely on statistical models of data, the ESS method leverages the power of the geometric theory of toric varieties to begin unraveling the structure of chemical reaction networks (CRN). This application of toric theory enables a data-driven mapping of covariance relationships in single-Cell measurements into stoichiometric information, one in which each Cell subpopulation has its associated ESS interpreted in terms of CRN theory. In the development of ESS we reframe certain aspects of the theory of CRN to better match data analysis. As an application of our approach we process cytomery- and image-based single-Cell datasets and identify differences in Cells treated with kinase inhibitors. Our approach is directly applicable to data acquired using readily accessible experimental methods such as Fluorescence Activated Cell Sorting (FACS) and multiplex immunofluorescence.

  • inferring reaction network structure from single Cell multiplex data using toric systems theory
    2019
    Co-Authors: Shu Wang, Eduardo D Sontag, Peter K Sorger
    Abstract:

    Abstract The goal of many single-Cell studies on eukaryotic Cells is to gain insight into the biochemical reactions that Control Cell Fate and state. In this paper we introduce the concept of effective stoichiometric space (ESS) to guide the reconstruction of biochemical networks from multiplexed, fixed time-point, single-Cell data. In contrast to methods based solely on statistical models of data, the ESS method leverages the power of the geometric theory of toric varieties to begin unraveling the structure of chemical reaction networks (CRN). This application of toric theory enables a data-driven mapping of covariance relationships in single Cell measurements into stoichiometric information, one in which each Cell subpopulation has its associated ESS interpreted in terms of CRN theory. In the development of ESS we reframe certain aspects of the theory of CRN to better match data analysis. As an application of our approach we process cytomery- and image-based single-Cell datasets and identify differences in Cells treated with kinase inhibitors. Our approach is directly applicable to data acquired using readily accessible experimental methods such as Fluorescence Activated Cell Sorting (FACS) and multiplex immunofluorescence. Author summary We introduce a new notion, which we call the effective stoichiometric space (ESS), that elucidates network structure from the covariances of single-Cell multiplexed data. The ESS approach differs from methods that are based on purely statistical models of data: it allows a completely new and data-driven translation of the theory of toric varieties in geometry and specifically their role in chemical reaction networks (CRN). In the process, we reframe certain aspects of the theory of CRN. As illustrations of our approach, we find stoichiometry in different single-Cell datasets, and pinpoint dose-dependence of network perturbations in drug-treated Cells.

Jeffrey L Wrana - One of the best experts on this subject based on the ideXlab platform.

  • switch enhancers interpret tgf β and hippo signaling to Control Cell Fate in human embryonic stem Cells
    2013
    Co-Authors: Tobias A Beyer, Alexander Weiss, Yuliya Khomchuk, Kui Huang, Abiodun A Ogunjimi, Xaralabos Varelas, Jeffrey L Wrana
    Abstract:

    Summary A small toolkit of morphogens is used repeatedly to direct development, raising the question of how context dictates interpretation of the same cue. One example is the transforming growth factor β (TGF-β) pathway that in human embryonic stem Cells fulfills two opposite functions: pluripotency maintenance and mesendoderm (ME) specification. Using proteomics coupled to analysis of genome occupancy, we uncover a regulatory complex composed of transcriptional effectors of the Hippo pathway (TAZ/YAP/ T EAD), the TGF-β pathway ( S MAD2/3), and the pluripotency regulator O CT4 (TSO). TSO collaborates with NuRD repressor complexes to buffer pluripotency gene expression while suppressing ME genes. Importantly, the SMAD DNA binding partner FOXH1, a major specifier of ME, is found near TSO elements, and upon Fate specification we show that TSO is disrupted with subsequent SMAD-FOXH1 induction of ME. These studies define switch-enhancer elements and provide a framework to understand how Cellular context dictates interpretation of the same morphogen signal in development.