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pid database  (Cell Signaling Technology Inc)


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    Cell Signaling Technology Inc pid database
    Makeup of the BioPAX models from three resources <t> (PID, </t> <t> KEGG, </t> ACSN). The BioPAX files of the three resources were parsed in order to identify Physical Entities, Controls ( Catalysis and TemplateReactionRegulation ) and Reactions ( Conversion and TemplateReaction ). For the ACSN resources, Physical Entities were curated in order to reanotate their types when possible. The curation processes focused on compressing duplicate entities and creating controls (with the type catalysis) for reactions where a reactant is also a product.
    Pid Database, supplied by Cell Signaling Technology Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/pid+database/pmc09232147-164-13-14?v=Cell+Signaling+Technology+Inc
    Average 90 stars, based on 1 article reviews
    pid database - by Bioz Stars, 2026-06
    90/100 stars

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    1) Product Images from "Discrete modeling for integration and analysis of large-scale signaling networks"

    Article Title: Discrete modeling for integration and analysis of large-scale signaling networks

    Journal: PLoS Computational Biology

    doi: 10.1371/journal.pcbi.1010175

    Makeup of the BioPAX models from three resources (PID, KEGG, ACSN). The BioPAX files of the three resources were parsed in order to identify Physical Entities, Controls ( Catalysis and TemplateReactionRegulation ) and Reactions ( Conversion and TemplateReaction ). For the ACSN resources, Physical Entities were curated in order to reanotate their types when possible. The curation processes focused on compressing duplicate entities and creating controls (with the type catalysis) for reactions where a reactant is also a product.
    Figure Legend Snippet: Makeup of the BioPAX models from three resources (PID, KEGG, ACSN). The BioPAX files of the three resources were parsed in order to identify Physical Entities, Controls ( Catalysis and TemplateReactionRegulation ) and Reactions ( Conversion and TemplateReaction ). For the ACSN resources, Physical Entities were curated in order to reanotate their types when possible. The curation processes focused on compressing duplicate entities and creating controls (with the type catalysis) for reactions where a reactant is also a product.

    Techniques Used: Control

    Characteristics of the Cadbiom models obtained after the conversion of BioPAX sources into models with guarded transitions. The Cadbiom models are described by entities, events and transitions. They are compared to the numbers of entities and reactions in the BioPAX models. The boundary entities correspond to the peripherical entities of the model. They are described according to their type and their role in the cadbiom model.
    Figure Legend Snippet: Characteristics of the Cadbiom models obtained after the conversion of BioPAX sources into models with guarded transitions. The Cadbiom models are described by entities, events and transitions. They are compared to the numbers of entities and reactions in the BioPAX models. The boundary entities correspond to the peripherical entities of the model. They are described according to their type and their role in the cadbiom model.

    Techniques Used: Control



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    Image Search Results


    Makeup of the BioPAX models from three resources (PID, KEGG, ACSN). The BioPAX files of the three resources were parsed in order to identify Physical Entities, Controls ( Catalysis and TemplateReactionRegulation ) and Reactions ( Conversion and TemplateReaction ). For the ACSN resources, Physical Entities were curated in order to reanotate their types when possible. The curation processes focused on compressing duplicate entities and creating controls (with the type catalysis) for reactions where a reactant is also a product.

    Journal: PLoS Computational Biology

    Article Title: Discrete modeling for integration and analysis of large-scale signaling networks

    doi: 10.1371/journal.pcbi.1010175

    Figure Lengend Snippet: Makeup of the BioPAX models from three resources (PID, KEGG, ACSN). The BioPAX files of the three resources were parsed in order to identify Physical Entities, Controls ( Catalysis and TemplateReactionRegulation ) and Reactions ( Conversion and TemplateReaction ). For the ACSN resources, Physical Entities were curated in order to reanotate their types when possible. The curation processes focused on compressing duplicate entities and creating controls (with the type catalysis) for reactions where a reactant is also a product.

    Article Snippet: We performed a systematic content analysis of 2 databases available on Pathway Commons, PID (cell signaling) and KEGG (metabolism and signaling reactions), as well as the ACSN database (Cancer signaling network), which are the largest reaction databases available in the BioPAX format.

    Techniques: Control

    Characteristics of the Cadbiom models obtained after the conversion of BioPAX sources into models with guarded transitions. The Cadbiom models are described by entities, events and transitions. They are compared to the numbers of entities and reactions in the BioPAX models. The boundary entities correspond to the peripherical entities of the model. They are described according to their type and their role in the cadbiom model.

    Journal: PLoS Computational Biology

    Article Title: Discrete modeling for integration and analysis of large-scale signaling networks

    doi: 10.1371/journal.pcbi.1010175

    Figure Lengend Snippet: Characteristics of the Cadbiom models obtained after the conversion of BioPAX sources into models with guarded transitions. The Cadbiom models are described by entities, events and transitions. They are compared to the numbers of entities and reactions in the BioPAX models. The boundary entities correspond to the peripherical entities of the model. They are described according to their type and their role in the cadbiom model.

    Article Snippet: We performed a systematic content analysis of 2 databases available on Pathway Commons, PID (cell signaling) and KEGG (metabolism and signaling reactions), as well as the ACSN database (Cancer signaling network), which are the largest reaction databases available in the BioPAX format.

    Techniques: Control