Whereas gene expression is influenced by epigenetic factors and/or transcription factor (TF) binding, protein synthesis can be regulated by microRNAs (miRNAs). Regulation of gene expression, protein synthesis and activity occurs at different levels. These processes contain genes, proteins and/or metabolites, their molecular interactions and reactions, but little regulatory information is present. Many known biological processes are represented in various online repositories, like WikiPathways and Reactome. It still remains a challenge to combine the new insights with existing knowledge and to understand the regulation of biological processes in detail. Recently, the ENCODE project, whose main goal was to identify all the functional elements in the human genome sequence, revealed novel insights in genetic regulation. However, understanding of the regulation of gene expression, protein synthesis and activity is far from complete. Approximately 25,000 gene coding regions were defined. In the Cytoscape BioGateway App these unbound values are called “Sets”, as they represent the set of all values qualifying their part of the query.Completion of the human genome project in 2003 generated a wealth of information about the human genetic code. In BioGateway, the subjects and objects can either be bound to a specific value, like the node representing “Pet” or “Walking” in the animation above, or they can represent any value satisfying the conditions of the query. In BioGateway, these edges are also called relation types, because they represent a type of relation between two entities. Subjects and objects are always nodes, while predicates are edges. We construct a query by step-wise specifying the nodes we want, and the relationships / type of edges between them.Įach new line represents an additional part of the query, consisting of a subject, predicate and object. The BioGateway database is powered by Virtuoso, and queryable through SPARQL, a graph query language based on the same principle as above. Note that even though “Mouse” is not an animal satisfying all the conditions of the query, it is included because it is part of the relevant network for the query. And by further constraining the results to those pets that also are “Chasing” mice, we end up with a final query that results in the network shown in the last part of the animation. The second line in the query restricts the pets to those that are “Walking”, eliminating the Parrot from the results. This returns a subset of the network containing the nodes representing “Pet”, and the animals with edges of the type “Kept as” pointing to the “Pet” node.īy adding more question parts to the query, we can further specify the search. The first question (part of a final query) selects for the animals that have the property of being “kept as” a “Pet”. In the animation to the right, we see a representation of a mock network in a (very small) graph database of animals and some of their properties. In this context, the “graph” is a network of nodes – shown as circles – and edges – the arrows connecting the nodes (see Example Graph Database, animation, to the right). BioGateway is an RDF Graph Database or ‘triple store’, and can be searched by building a query consisting of a set of questions that together specify what you are looking for.
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