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Åsmund Flobak - One of the best experts on this subject based on the ideXlab platform.

  • The Minimum Information about a Molecular Interaction Causal Statement (MI2CAST).
    Bioinformatics (Oxford England), 2020
    Co-Authors: Vasundra Touré, Steven Vercruysse, Marcio Luis Acencio, Ruth Lovering, Sandra Orchard, Glyn Bradley, Cristina Casals-casas, Claudine Chaouiya, Noemi Del-toro, Åsmund Flobak
    Abstract:

    Motivation A large variety of molecular interactions occurs between biomolecular components in cells. When a molecular interaction results in a regulatory effect, exerted by one component onto a downstream component, a so-called 'Causal interaction' takes place. Causal interactions constitute the building blocks in our understanding of larger regulatory networks in cells. These Causal interactions and the biological processes they enable (e.g., gene regulation) need to be described with a careful appreciation of the underlying molecular reactions. A proper description of this information enables archiving, sharing, and reuse by humans and for automated computational processing. Various representations of Causal relationships between biological components are currently used in a variety of resources. Results Here, we propose a checklist that accommodates current representations, called the Minimum Information about a Molecular Interaction Causal Statement (MI2CAST). This checklist defines both the required core information, as well as a comprehensive set of other contextual details valuable to the end user and relevant for reusing and reproducing Causal molecular interaction information. The MI2CAST checklist can be used as reporting guidelines when annotating and curating Causal Statements, while fostering uniformity and interoperability of the data across resources. Availability The checklist together with examples is accessible at https://github.com/MI2CAST/MI2CAST. Supplementary information Supplementary data are available at Bioinformatics online.

  • The Minimum Information about a Molecular Interaction Causal Statement (MI2CAST)
    2020
    Co-Authors: Vasundra Touré, Steven Vercruysse, Marcio Luis Acencio, Ruth Lovering, Sandra Orchard, Glyn Bradley, Cristina Casals-casas, Claudine Chaouiya, Noemi Del-toro, Åsmund Flobak
    Abstract:

    A large variety of molecular interactions occurs between biomolecular components in cells. When one or a cascade of molecular interactions results in a regulatory effect, by one component onto a downstream component, a so-called ‘Causal interaction’ takes place. Causal interactions constitute the building blocks in our understanding of larger regulatory networks in cells. These Causal interactions and the biological processes they enable (e.g., gene regulation) need to be described with a careful appreciation of molecular interactions that occur between entities. A proper description of this information enables archiving, sharing, and reuse by humans and for computational science. Various representations of Causal relationships between biological components are currently used in a variety of resources. Here, we propose a checklist that accommodates current representations, and call it the Minimum Information about a Molecular Interaction Causal Statement (MI2CAST). This checklist defines both the required core information, as well as a comprehensive set of other contextual details valuable to the end user and relevant for reusing and reproducing Causal molecular interaction information. The MI2CAST checklist can be used as reporting guidelines when annotating and curating Causal Statements, while assuring uniformity and interoperability of the data across resources.

Vasundra Touré - One of the best experts on this subject based on the ideXlab platform.

  • The Minimum Information about a Molecular Interaction Causal Statement (MI2CAST).
    Bioinformatics (Oxford England), 2020
    Co-Authors: Vasundra Touré, Steven Vercruysse, Marcio Luis Acencio, Ruth Lovering, Sandra Orchard, Glyn Bradley, Cristina Casals-casas, Claudine Chaouiya, Noemi Del-toro, Åsmund Flobak
    Abstract:

    Motivation A large variety of molecular interactions occurs between biomolecular components in cells. When a molecular interaction results in a regulatory effect, exerted by one component onto a downstream component, a so-called 'Causal interaction' takes place. Causal interactions constitute the building blocks in our understanding of larger regulatory networks in cells. These Causal interactions and the biological processes they enable (e.g., gene regulation) need to be described with a careful appreciation of the underlying molecular reactions. A proper description of this information enables archiving, sharing, and reuse by humans and for automated computational processing. Various representations of Causal relationships between biological components are currently used in a variety of resources. Results Here, we propose a checklist that accommodates current representations, called the Minimum Information about a Molecular Interaction Causal Statement (MI2CAST). This checklist defines both the required core information, as well as a comprehensive set of other contextual details valuable to the end user and relevant for reusing and reproducing Causal molecular interaction information. The MI2CAST checklist can be used as reporting guidelines when annotating and curating Causal Statements, while fostering uniformity and interoperability of the data across resources. Availability The checklist together with examples is accessible at https://github.com/MI2CAST/MI2CAST. Supplementary information Supplementary data are available at Bioinformatics online.

  • The Minimum Information about a Molecular Interaction Causal Statement (MI2CAST)
    2020
    Co-Authors: Vasundra Touré, Steven Vercruysse, Marcio Luis Acencio, Ruth Lovering, Sandra Orchard, Glyn Bradley, Cristina Casals-casas, Claudine Chaouiya, Noemi Del-toro, Åsmund Flobak
    Abstract:

    A large variety of molecular interactions occurs between biomolecular components in cells. When one or a cascade of molecular interactions results in a regulatory effect, by one component onto a downstream component, a so-called ‘Causal interaction’ takes place. Causal interactions constitute the building blocks in our understanding of larger regulatory networks in cells. These Causal interactions and the biological processes they enable (e.g., gene regulation) need to be described with a careful appreciation of molecular interactions that occur between entities. A proper description of this information enables archiving, sharing, and reuse by humans and for computational science. Various representations of Causal relationships between biological components are currently used in a variety of resources. Here, we propose a checklist that accommodates current representations, and call it the Minimum Information about a Molecular Interaction Causal Statement (MI2CAST). This checklist defines both the required core information, as well as a comprehensive set of other contextual details valuable to the end user and relevant for reusing and reproducing Causal molecular interaction information. The MI2CAST checklist can be used as reporting guidelines when annotating and curating Causal Statements, while assuring uniformity and interoperability of the data across resources.

Raymond Boudon - One of the best experts on this subject based on the ideXlab platform.

  • Social Mechanisms: Social mechanisms without black boxes
    Social Mechanisms, 1998
    Co-Authors: Raymond Boudon
    Abstract:

    Introduction “Explaining” means “finding the causes. ” Explaining a social phenomenon means identifying its cause(s). In most cases, the explanation takes the form of a more or less complicated set of Causal Statements. The relations between the elements of the set can be more or less complex; they can be linear, recursive, include feedback loops, and so on. The set is what we usually call a “social mechanism” (SM). A SM is, in other words, the well-articulated set of causes responsible for a given social phenomenon. With the exception of typical simple ones, SMs tend to be idiosyncratic and singular (Boudon 1986). I am essentially interested here in the discussion of a basic distinction – namely, that some explanations of social mechanisms give the impression of being “final, ” while others do not. Thus the Causal Statement “A legal limitation of rents provokes a degradation of housing” arouses the further question “Why is that so? ” In that sense, it is not “final. ” The answer to this question is that the owners, who have the exclusive capacity of repairing the houses, are not incited to do so when this cost exceeds the benefit that they draw from renting their house. With this answer, we have the impression that the explanation is final: It arouses in our mind no additional question. We have this impression because the causes of the social mechanism lie in a behavior of the owners that we easily perceive as understandable: We understand very easily why the owners do what they do.

Ruth Lovering - One of the best experts on this subject based on the ideXlab platform.

  • The Minimum Information about a Molecular Interaction Causal Statement (MI2CAST).
    Bioinformatics (Oxford England), 2020
    Co-Authors: Vasundra Touré, Steven Vercruysse, Marcio Luis Acencio, Ruth Lovering, Sandra Orchard, Glyn Bradley, Cristina Casals-casas, Claudine Chaouiya, Noemi Del-toro, Åsmund Flobak
    Abstract:

    Motivation A large variety of molecular interactions occurs between biomolecular components in cells. When a molecular interaction results in a regulatory effect, exerted by one component onto a downstream component, a so-called 'Causal interaction' takes place. Causal interactions constitute the building blocks in our understanding of larger regulatory networks in cells. These Causal interactions and the biological processes they enable (e.g., gene regulation) need to be described with a careful appreciation of the underlying molecular reactions. A proper description of this information enables archiving, sharing, and reuse by humans and for automated computational processing. Various representations of Causal relationships between biological components are currently used in a variety of resources. Results Here, we propose a checklist that accommodates current representations, called the Minimum Information about a Molecular Interaction Causal Statement (MI2CAST). This checklist defines both the required core information, as well as a comprehensive set of other contextual details valuable to the end user and relevant for reusing and reproducing Causal molecular interaction information. The MI2CAST checklist can be used as reporting guidelines when annotating and curating Causal Statements, while fostering uniformity and interoperability of the data across resources. Availability The checklist together with examples is accessible at https://github.com/MI2CAST/MI2CAST. Supplementary information Supplementary data are available at Bioinformatics online.

  • The Minimum Information about a Molecular Interaction Causal Statement (MI2CAST)
    2020
    Co-Authors: Vasundra Touré, Steven Vercruysse, Marcio Luis Acencio, Ruth Lovering, Sandra Orchard, Glyn Bradley, Cristina Casals-casas, Claudine Chaouiya, Noemi Del-toro, Åsmund Flobak
    Abstract:

    A large variety of molecular interactions occurs between biomolecular components in cells. When one or a cascade of molecular interactions results in a regulatory effect, by one component onto a downstream component, a so-called ‘Causal interaction’ takes place. Causal interactions constitute the building blocks in our understanding of larger regulatory networks in cells. These Causal interactions and the biological processes they enable (e.g., gene regulation) need to be described with a careful appreciation of molecular interactions that occur between entities. A proper description of this information enables archiving, sharing, and reuse by humans and for computational science. Various representations of Causal relationships between biological components are currently used in a variety of resources. Here, we propose a checklist that accommodates current representations, and call it the Minimum Information about a Molecular Interaction Causal Statement (MI2CAST). This checklist defines both the required core information, as well as a comprehensive set of other contextual details valuable to the end user and relevant for reusing and reproducing Causal molecular interaction information. The MI2CAST checklist can be used as reporting guidelines when annotating and curating Causal Statements, while assuring uniformity and interoperability of the data across resources.

Marcio Luis Acencio - One of the best experts on this subject based on the ideXlab platform.

  • The Minimum Information about a Molecular Interaction Causal Statement (MI2CAST).
    Bioinformatics (Oxford England), 2020
    Co-Authors: Vasundra Touré, Steven Vercruysse, Marcio Luis Acencio, Ruth Lovering, Sandra Orchard, Glyn Bradley, Cristina Casals-casas, Claudine Chaouiya, Noemi Del-toro, Åsmund Flobak
    Abstract:

    Motivation A large variety of molecular interactions occurs between biomolecular components in cells. When a molecular interaction results in a regulatory effect, exerted by one component onto a downstream component, a so-called 'Causal interaction' takes place. Causal interactions constitute the building blocks in our understanding of larger regulatory networks in cells. These Causal interactions and the biological processes they enable (e.g., gene regulation) need to be described with a careful appreciation of the underlying molecular reactions. A proper description of this information enables archiving, sharing, and reuse by humans and for automated computational processing. Various representations of Causal relationships between biological components are currently used in a variety of resources. Results Here, we propose a checklist that accommodates current representations, called the Minimum Information about a Molecular Interaction Causal Statement (MI2CAST). This checklist defines both the required core information, as well as a comprehensive set of other contextual details valuable to the end user and relevant for reusing and reproducing Causal molecular interaction information. The MI2CAST checklist can be used as reporting guidelines when annotating and curating Causal Statements, while fostering uniformity and interoperability of the data across resources. Availability The checklist together with examples is accessible at https://github.com/MI2CAST/MI2CAST. Supplementary information Supplementary data are available at Bioinformatics online.

  • The Minimum Information about a Molecular Interaction Causal Statement (MI2CAST)
    2020
    Co-Authors: Vasundra Touré, Steven Vercruysse, Marcio Luis Acencio, Ruth Lovering, Sandra Orchard, Glyn Bradley, Cristina Casals-casas, Claudine Chaouiya, Noemi Del-toro, Åsmund Flobak
    Abstract:

    A large variety of molecular interactions occurs between biomolecular components in cells. When one or a cascade of molecular interactions results in a regulatory effect, by one component onto a downstream component, a so-called ‘Causal interaction’ takes place. Causal interactions constitute the building blocks in our understanding of larger regulatory networks in cells. These Causal interactions and the biological processes they enable (e.g., gene regulation) need to be described with a careful appreciation of molecular interactions that occur between entities. A proper description of this information enables archiving, sharing, and reuse by humans and for computational science. Various representations of Causal relationships between biological components are currently used in a variety of resources. Here, we propose a checklist that accommodates current representations, and call it the Minimum Information about a Molecular Interaction Causal Statement (MI2CAST). This checklist defines both the required core information, as well as a comprehensive set of other contextual details valuable to the end user and relevant for reusing and reproducing Causal molecular interaction information. The MI2CAST checklist can be used as reporting guidelines when annotating and curating Causal Statements, while assuring uniformity and interoperability of the data across resources.