Data/hora: 08/06/2024 01:28:42

Provedor de dados: | Nature Precedings
País: | United Kingdom
Título: | Systems Biology Graphical Notation: Process Diagram Level 1
Autores: | Nicolas Le Novere; Stuart Moodie; Anatoly Sorokin; Michael Hucka; Falk Schreiber; Emek Demir; Huaiyu Mi; Yukiko Matsuoka; Katja Wegner; Hiroaki Kitano.
Data: | 2008-09-22
Ano: | 2008
Palavras-chave: | Biotechnology; Bioinformatics.
Resumo: | Standard graphical representations have played a crucial role in science and engineering throughout the last century. Without electrical symbolism, it is very likely that our industrial society would not have evolved at the same pace. Similarly, specialised notations such as the Feynmann notation or the process flow diagrams did a lot for the adoption of concepts in their own fields. With the advent of Systems Biology, and more recently of Synthetic Biology, the need for precise and unambiguous descriptions of biochemical interactions has become more pressing. While some ideas have been advanced over the last decade, with a few detailed proposals, no actual community standard has emerged. The Systems Biology Graphical Notation (SBGN) is a graphical representation crafted over several years by a community of biochemists, modellers and computer scientists. Three orthogonal and complementary languages have been created, the Process Diagrams, the Entity Relationship Diagrams and the Activity Flow Diagrams. Using these three idioms a scientist can represent any network of biochemical interactions, which can then be interpreted in an unambiguous way. The set of symbols used is limited, and the grammar quite simple, to allow its usage in textbooks and its teaching directly in high schools. The first level of the SBGN Process Diagram has been publicly released. Software support for SBGN Process Diagram was developed concurrently with its specification in order to speed-up public adoption. Shared by the communities of biochemists, genomicians, theoreticians and computational biologists, SBGN languages will foster efficient storage, exchange and reuse of information on signalling pathways, metabolic networks and gene regulatory maps.
Tipo: | Manuscript

Identificador:

http://precedings.nature.com/documents/2320/version/1

oai:nature.com:10101/npre.2008.2320.1

http://hdl.handle.net/10101/npre.2008.2320.1

Fonte: | Nature Precedings
Fonte: | Creative Commons Attribution 3.0 License