Original article | published - EPub | peer reviewed | Open Access
SBGN Bricks Ontology as a tool to describe recurring concepts in molecular networks
BRIEFINGS IN BIOINFORMATICS
2021 ;
Authors
Rougny A*, Touré V, Albanese J, Waltemath D1, Shirshov D, Sorokin A, Bader G, Blinov M, Mazein A
Abstract
A comprehensible representation of a molecular network is key to communicating and understanding scientific results in systems biology. The Systems Biology Graphical Notation (SBGN) has emerged as the main standard to represent such networks graphically. It has been implemented by different software tools, and is now largely used to communicate maps in scientific publications. However, learning the standard, and using it to build large maps, can be tedious. Moreover, SBGN maps are not grounded on a formal semantic layer and therefore do not enable formal analysis. Here, we introduce a new set of patterns representing recurring concepts encountered in molecular networks, called SBGN bricks. The bricks are structured in a new ontology, the BricKs Ontology (BKO), to define clear semantics for each of the biological concepts they represent. We show the usefulness of the bricks and BKO for both the template-based construction and the semantic annotation of molecular networks. The SBGN bricks and BKO can be freely explored and downloaded at sbgnbricks.org.
Published in
BRIEFINGS IN BIOINFORMATICS
| Year | 2021 |
| Impact Factor (2021) | 13.994 |
| Volume | |
| Issue | |
| Pages | - |
| Open Access | ja |
| Peer reviewed | ja |
| Article type | Original article |
| Article state | published - EPub |
| DOI | https://doi.org/10.1093/bib/bbab049 |
Common journal data
Short name: BRIEF BIOINFORM
ISSN: 1467-5463
eISSN: 1477-4054
Country: ENGLAND
Language: English
Categories:
Impact factor trend
ISSN: 1467-5463
eISSN: 1477-4054
Country: ENGLAND
Language: English
Categories:
- MATHEMATICAL & COMPUTATIONAL BIOLOGY
- BIOCHEMICAL RESEARCH METHODS
Impact factor trend
| Year | Impact Factor |
|---|---|
| 2008 | 4.627 |
| 2009 | 7.329 |
| 2010 | 9.283 |
| 2011 | 5.202 |
| 2012 | 5.298 |
| 2013 | 5.919 |
| 2014 | 9.617 |
| 2015 | 8.399 |
| 2016 | 5.134 |
| 2017 | 6.302 |
| 2018 | 9.101 |
| 2019 | 8.99 |
| 2020 | 11.622 |
| 2021 | 13.994 |
| 2022 | 9.5 |
| 2023 | 6.8 |
| 2024 | 7.7 |
Key field of research at the University
Key topics
Departments
Data Science

