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pathway interaction database (pid)  (Broad Institute Inc)

 
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    Broad Institute Inc pathway interaction database (pid)
    Pathway Interaction Database (Pid), supplied by Broad Institute 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/pathway+interaction+database++pid+/pm38133364-154-14-4
    Average 90 stars, based on 1 article reviews
    pathway interaction database (pid) - by Bioz Stars, 2026-09
    90/100 stars

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    Control:

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

    Article Title: Cancer-related marketing centrality motifs acting as pivot units in the human signaling network and mediating cross-talk between biological pathways
    Article Snippet: Network motifs in central positions are considered to not only have more in-coming and out-going connections but are also localized in an area where more paths reach the networks.. These central motifs have been extensively investigated to determine their consistent functions or associations with specific function categories.. However, their functional potentials in the maintenance of cross-talk between different functional communities are unclear.



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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