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From sbgnbricks

SBGN

The Systems Biology Graphical Notation (SBGN) standardizes the unambiguous graphical representation of biological networks. The three languages of SBGN allow the representation of all kinds of biological processes and networks, and at different levels of granularity, thereby contributing substantially to the gain and transfer of knowledge in all fields of biology.

PROCESS DESCRIPTIONS (PD

The PD language represents the transition of entities (species) from one state to another in a sequential order of processes. Processes basically consist of three parts: one or more source entities, the process node and one or more product entities. These are connected by connecting arcs (consumption; production); the influence of other entities (effectors) on a given process is represented by another connecting arc (catalysis, inhibition, stimulation). Within a PD map species might occur several times, which might contribute to combinatorial explosion as a disadvantage of PD. Multiple occurrences have to be marked using the clone marker. In general PD has the best applicability for the representation of different kinds of biological events. PD is able to distinguish between different knowledge levels which is important in two ways: firstly, when a high level of knowledge is available, for the purpose of clarity, it may be desired to only depict a low level of detail, secondly: when there is only a low level of knowledge due to methodical restrictions or low availability of data. PD is best applied to represent mechanistic and temporal aspects of biological events therefore being a good choice for the representation of biochemical reactions/pathways. For detailed descriptions of the PD glyphs the reader is referred to the PD technical specification.

ENTITY RELATIONSHIPS (ER)

The ER language focuses on interactions between entities and their influences on other entities. Relationships between entities can have different results such as another interaction, the existence of another entity or the assignment of variable values to entities which determine their location or status. Entities must not occur more than once in a map. ER does not consider temporal aspects and only ambiguously describes underlying mechanisms. This language is a good choice for representation of protein-protein-interaction networks. For detailed descriptions of the ER glyphs the reader is referred to the ER technical specification.

ACTIVITY FLOWS (AF)

The AF language is an abstract simplification of PD which, in contrast to PD and ER, is ambiguous with respect to mechanistic details. It represents the lowest level of detail, as it is most comparable to conventional arrow diagrams. AF focuses on biological activities which are represented by activity nodes. The influence between activities is shown using modulation arcs. The sequential influences between different activities are used to represent networks of functional genomics or signaling networks. For detailed descriptions of the AF glyphs the reader is referred to the AF technical specification.

Features	SBGN languages
	Process Descriptions	Entity Relationships	Activity Flows
Essence	change	influence	activity flow
Brief description	represents the transitions of entities from one form or state to another	represents the influences of entities upon the behaviour of others	represents the activity flow from one entity to another or within the same entity
Ambiguity	unambiguous	unambiguous	ambiguous
Sequence of events	sequential	non-sequential	sequential
Advantages	clear sequences of events	can deal with combinatorial explosion	compactness
Main limitations	cannot deal with combinatorial explosion	sequences of events cannot be shown	low detail, ambiguity
Applicability	metabolic networks, regulatory networks	protein-protein-interaction networks	networks of functional genomics, signaling networks

Map drawing tools with SBGN editor functionalities

Tool	PD	ER	AF	Reference
BiNOM	+	-	-	Zinovyev et al. 2008
BioUML	+	-	-	-
CellDesigner	+	-	-	Funahashi et al. 2008
Edinburgh Pathway Editor (EPE)	+	+	+	Sorokin et al. 2006
PathVisio	+	-	-	Van Iersel et al. 2008
PathwayLab	+	-	-	-
SBGN-ED	+	+	+	Czauderna et al. 2010

SBGN supporting web resources

Database	Description	Reference
BioModels Database	Computational model repository, supports SBGN PD	Li et al. 2010a, Li et al. 2010b
PANTHER Pathway	Protein analysis through evolutionary relationships covers mainly signaling pathways, supports SBGN PD/AF	Mi et al. 2007, Mi et al. 2010
Reactome	Biological pathway database, covers different kinds of pathways supports SBGN PD	Croft et al. 2011
MetaCrop	Metabolic database of crop plant primary metabolism, covers metabolic pathways, supports SBGN PD	Grafahrend-Belau et al. 2008 Schreiber et al. 2012
RIMAS	Regulatory interaction maps of Arabidopsis seed development covers gene regulatory pathways, supports SBGN PD	Junker et al. 2010

SBGN bricks - from patterns to networks

SBGN bricks are building blocks representing basic biological patterns. They can be used for assembly into different kinds of networks (metabolic, regulatory networks).

Advantages:

- SBGN bricks facilitate the expression of biological knowledge using SBGN

- show the applicability of the SBGN languages for certain kinds of networks

- the use of SBGN bricks speeds up the drawing of networks in SBGN style

- the use of SBGN bricks facilitates the re-use of common network patterns

- can be downloaded in the SBGN markup language (SBGN-ML)

SBGN bricks dictionary

Cellular events are based on a range of fundamental biological processes such as transcription, translation or metabolic reactions. Such processes built the basis for different kinds of networks which are characterized by their repeated representation. Such recurring biological patterns are represented in various SBGN bricks, which are listed in the SBGN bricks dictionary.

For the following biological patterns SBGN bricks are available:

Metabolic networks: catalysis (including different reaction types)

Gene regulatory networks: regulation of transcription, translation

Protein-protein-interaction networks: complex formation, complex dissociation, oligomerization/homodimerization

Networks of functional genomics: functional relationship

Signaling networks: phosphorylation

Others: compartmentation/transport

Use case

To illustrate the application of SBGN bricks for SBGN map assembly, the inducible nitric oxide synthase (iNOS) pathway map has been assembled using a number of bricks from the dictionary. The iNOS pathway comprises the following biological events: after the preassembly of the interferon gamma (IFNG) receptor complex, this complex is auto-activated by IFNG (Krause et al. 2006). The activated complex of IFNG, phosphorylated IFNGR1, IFNGR2, JAK1 and JAK2 stimulates the transfer of two phosphate groups from ATP to the STAT1alpha protein (Strassheim et al. 2009). After homodimerization of the phosphorylated STAT1alpha protein (Barnholt et al. 2009 and Horvath 2004), it activates transcription of the IRF1 gene by directly binding to the IRF1 promoter (Contursi et al. 2000). The IRF1 protein regulates the transcription of the NO-synthase (NOS) gene (Blair et al. 2002) and the corresponding NOS protein complexes with a Calmodulin-binding protein (McMurry et al. 2011,Wu et al. 2011,Spratt et al. 2007 and Venema et al. 1996). This complex is involved in nitric oxide metabolic pathways as NO synthesis during arginine degradation (Andrew and Mayer 1999).

The following SBGN map displays the assembled iNOS pathway using Process Descriptions.