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Causal biological network database: a comprehensive platform of causal biological network models focused on the pulmonary and vascular systems.

Boué S, Talikka M, Westra JW, Hayes W, Di Fabio A, Park J, Schlage WK, Sewer A, Fields B, Ansari S, Martin F, Veljkovic E, Kenney R, Peitsch MC, Hoeng J - Database (Oxford) (2015)

Bottom Line: With the wealth of publications and data available, powerful and transparent computational approaches are required to represent measured data and scientific knowledge in a computable and searchable format.Nodes and edges can be filtered and all supporting evidence for the edges can be browsed and is linked to the original articles in PubMed.Moreover, networks may be downloaded for further visualization and evaluation.

View Article: PubMed Central - PubMed

Affiliation: Philip Morris International R&D, Philip Morris Products S.A. Quai Jeanrenaud 5, 2000 Neuchâtel, Switzerland, Selventa, One Alewife Center, Cambridge, MA 02140, USA and Applied Dynamic Solutions, LLC, 220 Davidson Avenue, Suite 100, Somerset, NJ 08873, USA.

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Database and website architecture. Knowledge is extracted from the scientific literature, scripted in BEL and stored in a knowledgebase. All networks are stored as JSON objects in a MongoDB repository with rich metadata (network title, description, version). Networks can be subjected to crowd verification in sbv IMPROVER and are accessible from the CBN database website. A smart search allows users to find relevant network models by searching, e.g. for keywords, molecular entities, biological processes in the nodes list, network title and network description. Networks returned in a search may be exported in different file formats or displayed in a network viewer powered by d3.js (a JavaScript library for manipulating documents based on data) from which additional functionalities are available, such as exporting specific network views as images. All underlying pieces of evidence can be browsed and are linked to the original scientific literature.
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bav030-F4: Database and website architecture. Knowledge is extracted from the scientific literature, scripted in BEL and stored in a knowledgebase. All networks are stored as JSON objects in a MongoDB repository with rich metadata (network title, description, version). Networks can be subjected to crowd verification in sbv IMPROVER and are accessible from the CBN database website. A smart search allows users to find relevant network models by searching, e.g. for keywords, molecular entities, biological processes in the nodes list, network title and network description. Networks returned in a search may be exported in different file formats or displayed in a network viewer powered by d3.js (a JavaScript library for manipulating documents based on data) from which additional functionalities are available, such as exporting specific network views as images. All underlying pieces of evidence can be browsed and are linked to the original scientific literature.

Mentions: The initial focus of the NVC revolved around mechanisms implicated in COPD disease pathophysiology. Therefore, before the start of the challenge, COPD-relevant mechanisms, including B-cell and T-cell activation, airway remodeling, extracellular matrix (ECM) degradation, efferocytosis, mucus hypersecretion and emphysema were added to the published ‘non-disease’ pulmonary networks. In addition, prior to deploying the COPD-enhanced biological networks on the NVC website on Bionet (http://bionet.sbvimprover.com) for verification by the scientific community, the set of ‘pulmonary’ networks were agglomerated to yield a more concise set of 50 networks that combined related/complementary cellular pathways. This set of 50 network models is also available in the CBN database as version 1.1 of the network models. The relationships between versions 1.0 and 1.1 are described in a network hierarchy figure (Figure 1) and in the Supplementary data describing all available network models of the CBN database (Supplementary Material). Improvements made to the network models during the NVC-included submission of new pieces of evidence, additional literature publications to support existing network edges, as well as submission of new biological edges with supporting evidence for relationships that were not represented in the original networks. When networks are refined, they are imported into the CBN database as new versions (Figure 3C). Thus, conceptually, Bionet and the CBN platform are linked intrinsically and were developed in parallel so that the CBN database constitutes a repository of all versions of the network models and Bionet contains a single version of the network that is open for crowd verification (Figure 4).Figure 4.


Causal biological network database: a comprehensive platform of causal biological network models focused on the pulmonary and vascular systems.

Boué S, Talikka M, Westra JW, Hayes W, Di Fabio A, Park J, Schlage WK, Sewer A, Fields B, Ansari S, Martin F, Veljkovic E, Kenney R, Peitsch MC, Hoeng J - Database (Oxford) (2015)

Database and website architecture. Knowledge is extracted from the scientific literature, scripted in BEL and stored in a knowledgebase. All networks are stored as JSON objects in a MongoDB repository with rich metadata (network title, description, version). Networks can be subjected to crowd verification in sbv IMPROVER and are accessible from the CBN database website. A smart search allows users to find relevant network models by searching, e.g. for keywords, molecular entities, biological processes in the nodes list, network title and network description. Networks returned in a search may be exported in different file formats or displayed in a network viewer powered by d3.js (a JavaScript library for manipulating documents based on data) from which additional functionalities are available, such as exporting specific network views as images. All underlying pieces of evidence can be browsed and are linked to the original scientific literature.
© Copyright Policy - creative-commons
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4401337&req=5

bav030-F4: Database and website architecture. Knowledge is extracted from the scientific literature, scripted in BEL and stored in a knowledgebase. All networks are stored as JSON objects in a MongoDB repository with rich metadata (network title, description, version). Networks can be subjected to crowd verification in sbv IMPROVER and are accessible from the CBN database website. A smart search allows users to find relevant network models by searching, e.g. for keywords, molecular entities, biological processes in the nodes list, network title and network description. Networks returned in a search may be exported in different file formats or displayed in a network viewer powered by d3.js (a JavaScript library for manipulating documents based on data) from which additional functionalities are available, such as exporting specific network views as images. All underlying pieces of evidence can be browsed and are linked to the original scientific literature.
Mentions: The initial focus of the NVC revolved around mechanisms implicated in COPD disease pathophysiology. Therefore, before the start of the challenge, COPD-relevant mechanisms, including B-cell and T-cell activation, airway remodeling, extracellular matrix (ECM) degradation, efferocytosis, mucus hypersecretion and emphysema were added to the published ‘non-disease’ pulmonary networks. In addition, prior to deploying the COPD-enhanced biological networks on the NVC website on Bionet (http://bionet.sbvimprover.com) for verification by the scientific community, the set of ‘pulmonary’ networks were agglomerated to yield a more concise set of 50 networks that combined related/complementary cellular pathways. This set of 50 network models is also available in the CBN database as version 1.1 of the network models. The relationships between versions 1.0 and 1.1 are described in a network hierarchy figure (Figure 1) and in the Supplementary data describing all available network models of the CBN database (Supplementary Material). Improvements made to the network models during the NVC-included submission of new pieces of evidence, additional literature publications to support existing network edges, as well as submission of new biological edges with supporting evidence for relationships that were not represented in the original networks. When networks are refined, they are imported into the CBN database as new versions (Figure 3C). Thus, conceptually, Bionet and the CBN platform are linked intrinsically and were developed in parallel so that the CBN database constitutes a repository of all versions of the network models and Bionet contains a single version of the network that is open for crowd verification (Figure 4).Figure 4.

Bottom Line: With the wealth of publications and data available, powerful and transparent computational approaches are required to represent measured data and scientific knowledge in a computable and searchable format.Nodes and edges can be filtered and all supporting evidence for the edges can be browsed and is linked to the original articles in PubMed.Moreover, networks may be downloaded for further visualization and evaluation.

View Article: PubMed Central - PubMed

Affiliation: Philip Morris International R&D, Philip Morris Products S.A. Quai Jeanrenaud 5, 2000 Neuchâtel, Switzerland, Selventa, One Alewife Center, Cambridge, MA 02140, USA and Applied Dynamic Solutions, LLC, 220 Davidson Avenue, Suite 100, Somerset, NJ 08873, USA.

Show MeSH
Related in: MedlinePlus