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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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Biological Expression Language (BEL). (A) Elements of BEL: BEL functions, namespace identifiers, and entity definitions compose each node name that can be either subject or object in the relationship. (B) Example of a BEL semantic triplet composed of a subject (abundance of LPS), a relationship or predicate (directly increases) and an object (catalytic function of TLR4). (C) Detailed information on one of the underlying pieces of evidences and a link to the original article and context in which the relationship was demonstrated in the article.
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bav030-F2: Biological Expression Language (BEL). (A) Elements of BEL: BEL functions, namespace identifiers, and entity definitions compose each node name that can be either subject or object in the relationship. (B) Example of a BEL semantic triplet composed of a subject (abundance of LPS), a relationship or predicate (directly increases) and an object (catalytic function of TLR4). (C) Detailed information on one of the underlying pieces of evidences and a link to the original article and context in which the relationship was demonstrated in the article.

Mentions: Knowledge is expressed as BEL statements and subsequently stored in BEL documents. BEL statements are defined as semantic triplets: subject–predicate–object, where the subject and object are BEL terms and the predicate is one of the BEL relationship types (e.g. increases, decreases) that can also be represented by a symbol (Figure 2A). Currently, several types of biological entities are represented as BEL terms, which can include abundances (e.g. abundance of protein, RNA, complexes), modifications (e.g. phosphorylation) and activities (e.g. transcriptional activity, kinase activity), and processes (e.g. gene ontology biological process, phenotype). The BEL term for a protein is usually composed of the protein name acronym and a namespace identifier that indicates the database or ontology where the acronym was defined. In addition to the precise description of the terms and relationship, each BEL statement can be annotated to express knowledge about context of the statement such as information about the biological system, experimental method and/or appropriate literature citation. An example of a BEL statement is shown in Figure 2B. In this example, the statement ‘a(CHEBI:lipopolysaccharide) directlyIncreases cat(p(HGNC:TLR4)’ encodes information about the subject, namely the abundance of the lipopolysaccharide (LPS), which is identified by its namespace identifier from the Chemical Entities of Biological Interest (ChEBI) database (20). The relationship (the predicate of the triplet) scripted in this example is a direct increase, implying that LPS directly interacts with TLR4 to increase its activity. The object for this example is the catalytic activity of the protein identified in the HGNC namespace by its abbreviation toll-like receptor 4 (TLR4). The BEL document encoding this statement was annotated with eight pieces of evidence text from peer-reviewed articles that are maintained with the BEL statement and are viewable on the web-based platform.Figure 2.


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)

Biological Expression Language (BEL). (A) Elements of BEL: BEL functions, namespace identifiers, and entity definitions compose each node name that can be either subject or object in the relationship. (B) Example of a BEL semantic triplet composed of a subject (abundance of LPS), a relationship or predicate (directly increases) and an object (catalytic function of TLR4). (C) Detailed information on one of the underlying pieces of evidences and a link to the original article and context in which the relationship was demonstrated in the article.
© Copyright Policy - creative-commons
Related In: Results  -  Collection

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

bav030-F2: Biological Expression Language (BEL). (A) Elements of BEL: BEL functions, namespace identifiers, and entity definitions compose each node name that can be either subject or object in the relationship. (B) Example of a BEL semantic triplet composed of a subject (abundance of LPS), a relationship or predicate (directly increases) and an object (catalytic function of TLR4). (C) Detailed information on one of the underlying pieces of evidences and a link to the original article and context in which the relationship was demonstrated in the article.
Mentions: Knowledge is expressed as BEL statements and subsequently stored in BEL documents. BEL statements are defined as semantic triplets: subject–predicate–object, where the subject and object are BEL terms and the predicate is one of the BEL relationship types (e.g. increases, decreases) that can also be represented by a symbol (Figure 2A). Currently, several types of biological entities are represented as BEL terms, which can include abundances (e.g. abundance of protein, RNA, complexes), modifications (e.g. phosphorylation) and activities (e.g. transcriptional activity, kinase activity), and processes (e.g. gene ontology biological process, phenotype). The BEL term for a protein is usually composed of the protein name acronym and a namespace identifier that indicates the database or ontology where the acronym was defined. In addition to the precise description of the terms and relationship, each BEL statement can be annotated to express knowledge about context of the statement such as information about the biological system, experimental method and/or appropriate literature citation. An example of a BEL statement is shown in Figure 2B. In this example, the statement ‘a(CHEBI:lipopolysaccharide) directlyIncreases cat(p(HGNC:TLR4)’ encodes information about the subject, namely the abundance of the lipopolysaccharide (LPS), which is identified by its namespace identifier from the Chemical Entities of Biological Interest (ChEBI) database (20). The relationship (the predicate of the triplet) scripted in this example is a direct increase, implying that LPS directly interacts with TLR4 to increase its activity. The object for this example is the catalytic activity of the protein identified in the HGNC namespace by its abbreviation toll-like receptor 4 (TLR4). The BEL document encoding this statement was annotated with eight pieces of evidence text from peer-reviewed articles that are maintained with the BEL statement and are viewable on the web-based platform.Figure 2.

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