scholarly journals Quick tips for creating effective and impactful biological pathways using the Systems Biology Graphical Notation

2018 ◽  
Vol 14 (2) ◽  
pp. e1005740 ◽  
Author(s):  
Vasundra Touré ◽  
Nicolas Le Novère ◽  
Dagmar Waltemath ◽  
Olaf Wolkenhauer
Keyword(s):  
Systems Biology ◽  
Biological Pathways ◽  
Graphical Notation

Beacon Editor: Capturing Signal Transduction Pathways Using the Systems Biology Graphical Notation Activity Flow Language

2017 ◽  
Vol 24 (12) ◽  
pp. 1226-1229 ◽  
Author(s):  
Haitham Elmarakeby ◽  
Mostafa Arefiyan ◽  
Elijah Myers ◽  
Song Li ◽  
Ruth Grene ◽  
...  
Keyword(s):  
Signal Transduction ◽  
Systems Biology ◽  
Signal Transduction Pathways ◽  
Graphical Notation

scholarly journals Systems Biology Graphical Notation: Process Description language Level 1

2010 ◽  
Author(s):  
Stuart Moodie ◽  
Nicolas Le Novere ◽  
Emek Demir ◽  
Huaiyu Mi ◽  
Falk Schreiber
Keyword(s):  
Systems Biology ◽  
Description Language ◽  
Graphical Notation ◽  
Language Level ◽  
Level 1

Creating interactive, web-based and data-enriched maps with the Systems Biology Graphical Notation

2012 ◽  
Vol 7 (3) ◽  
pp. 579-593 ◽  
Author(s):  
Astrid Junker ◽  
Hendrik Rohn ◽  
Tobias Czauderna ◽  
Christian Klukas ◽  
Anja Hartmann ◽  
...  
Keyword(s):  
Systems Biology ◽  
Web Based ◽  
Graphical Notation

scholarly journals Systems Biology Graphical Notation: Entity Relationship language Level 1 (Version 1.2)

2011 ◽  
Author(s):  
Nicolas Le Novere ◽  
Emek Demir ◽  
Huaiyu Mi ◽  
Stuart Moodie ◽  
Alice Villeger
Keyword(s):  
Systems Biology ◽  
Graphical Notation ◽  
Language Level ◽  
Level 1 ◽  
Entity Relationship

scholarly journals Systems Biology Graphical Notation: Activity Flow language Level 1 Version 1.2

2015 ◽  
Vol 12 (2) ◽  
pp. 340-381 ◽  
Author(s):  
Huaiyu Mi ◽  
Falk Schreiber ◽  
Stuart Moodie ◽  
Tobias Czauderna ◽  
Emek Demir ◽  
...  
Keyword(s):  
Systems Biology ◽  
Biological Activities ◽  
Negative Influence ◽  
Positive Influence ◽  
Binding Activity ◽  
Biological Knowledge ◽  
Protein Kinase Activity ◽  
Graphical Notation ◽  
Biochemical Systems ◽  
Entity Relationship

Summary The Systems Biological Graphical Notation (SBGN) is an international community effort for standardized graphical representations of biological pathways and networks. The goal of SBGN is to provide unambiguous pathway and network maps for readers with different scientific backgrounds as well as to support efficient and accurate exchange of biological knowledge between different research communities, industry, and other players in systems biology. Three SBGN languages, Process Description (PD), Entity Relationship (ER) and Activity Flow (AF), allow for the representation of different aspects of biological and biochemical systems at different levels of detail.The SBGN Activity Flow language represents the influences of activities among various entities within a network. Unlike SBGN PD and ER that focus on the entities and their relationships with others, SBGN AF puts the emphasis on the functions (or activities) performed by the entities, and their effects to the functions of the same or other entities. The nodes (elements) describe the biological activities of the entities, such as protein kinase activity, binding activity or receptor activity, which can be easily mapped to Gene Ontology molecular function terms. The edges (connections) provide descriptions of relationships (or influences) between the activities, e.g., positive influence and negative influence. Among all three languages of SBGN, AF is the closest to signaling pathways in biological literature and textbooks, but its well-defined semantics offer a superior precision in expressing biological knowledge.

scholarly journals Systems Biology Graphical Notation: Process Diagram Level 1

2008 ◽  
Author(s):  
Nicolas Le Novere ◽  
Stuart Moodie ◽  
Anatoly Sorokin ◽  
Michael Hucka ◽  
Falk Schreiber ◽  
...  
Keyword(s):  
Systems Biology ◽  
Graphical Notation ◽  
Level 1

scholarly journals Systems Biology Graphical Notation: Process Description language Level 1

2011 ◽  
Author(s):  
Stuart Moodie ◽  
Nicolas Le Novere ◽  
Emek Demir ◽  
Huaiyu Mi ◽  
Alice Villeger
Keyword(s):  
Systems Biology ◽  
Description Language ◽  
Graphical Notation ◽  
Language Level ◽  
Level 1

Biochemical modeling with Systems Biology Graphical Notation

2010 ◽  
Vol 15 (9-10) ◽  
pp. 365-370 ◽  
Author(s):  
Andreas Jansson ◽  
Mats Jirstrand
Keyword(s):  
Systems Biology ◽  
Graphical Notation ◽  
Biochemical Modeling

scholarly journals SBGN Bricks Ontology as a tool to describe recurring concepts in molecular networks

2021 ◽  
Author(s):  
Adrien Rougny ◽  
Vasundra Touré ◽  
John Albanese ◽  
Dagmar Waltemath ◽  
Denis Shirshov ◽  
...  
Keyword(s):  
Systems Biology ◽  
Semantic Annotation ◽  
Formal Analysis ◽  
Molecular Network ◽  
Molecular Networks ◽  
Scientific Publications ◽  
Graphical Notation ◽  
Biological Concepts ◽  
Scientific Results ◽  
Semantic Layer

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.

scholarly journals Transcriptomic Systems Biology Analyses with Buparlisib (BKM120) Pan PI3K Inhibition in Canine B Cell Lymphoma (BCL): Leveraging Comparative Oncology for Cancer Therapeutics and Biomarker Discovery

Blood ◽  
2018 ◽  
Vol 132 (Supplement 1) ◽  
pp. 4114-4114
Author(s):  
Ravi Dashnamoorthy ◽  
Afshin Beheshti ◽  
Sarah Cass ◽  
Athena Kritharis ◽  
Kristine Burgess ◽  
...  
Keyword(s):  
Clinical Study ◽  
Systems Biology ◽  
Cancer Risk ◽  
Board Of Directors ◽  
Differentially Expressed Genes ◽  
Research Funding ◽  
Biological Pathways ◽  
Differentially Expressed ◽  
Advisory Committees ◽  
Key Genes

Abstract Background: The canine is a highly appealing model for cancer research and discovery in part due to comparable histopathological features with humans, a fully intact immune system, similar clinicopathologic features, a more comparable body size and pharmacokinetic properties than the mouse, varied breed-specific incidence rates as well as a shared environment with humans. We and others have shown prominent transcriptomic overlap of human and canine NHL (cNHL) (McDonald T et al. Onctogarget, 2018). PI3K/Akt signaling plays an important role in lymphomagenesis, which is also a promising therapeutic target. However, identification of predictive genetic aberrations of therapeutic efficacy remains elusive. We evaluated the clinical activity of the pan-PI3K inhibitor, buparlisib, in a pilot clinical study in cNHL. Methods :We enrolled and treated 10 dogs with buparlisibwho were diagnosed with BCL in an IRB and IACUC approved clinical study. Cases included 2 treatment naïve and 8 dogs with relapsed disease that had relapsed s/p CHOP (6), L' asparaginase (1) and VELCAP (1) treatment. Pet owners were consented and the study subjects received buparlisib9mg/kg orally for 28 consecutive days. Analysis for tumor response were evaluated on weekly basis through direct tumor measurement or use of x-rays. Post-therapy fine needle aspirates (FNA) were collected on Days 0, 7 and 21 to examine predictors of response to BKM120. RNA from fine need aspirate cells were isolated and the transcriptomic changes were evaluated using Canine Genome 2.0 Affymetrix Array, followed by unbiased systems biology assessment for biological pathways using Gene Set Enrichment Analysis (GSEA) and Ingenuity Pathway Analysis (IPA). We performed unbiased assessment to determine pertinent biological pathways associated with treatment response. The overall impact was used to determine the global effect on tumor progression and cancer risk based on the specific regulation of each gene. A Carcinogenic Risk Score (CRS) was calculated based on these values to determine if there is a promoted risk for cancer (positive value) or inhibitory risk for cancer (negative value) by summing the log2 fold-change values of key genes and subtracting this from the sum of log2 fold-change values of the tumor suppressors when comparing pre-treated to BKM120 treated dogs. Results: Following four weeks of BKM120 treatment, the overall response rate was 30% with 1 complete response lasting 42 days; 2 partial responses lasting 55 and 72 days; 3 stable disease; and 4 progressive disease. Mild treatment related toxicities such elevated blood glucose, thrombocytopenia and anemia, fever, nausea and lethargic symptoms, with no treatment related toxicities in 2 cases were noted. Principal Component Analysis (PCA) and hierrachical clustering analysis of differentially expressed genes show that differentially expressed genes to cluster together in all dogs during post 2 week, indicating a consistent biological activity by BKM120 in all dogs regardless of breed, prior treatment or disease status. Pathway network analysis based on differentially expressed genes predicted activation of upstream regulators associated with tumor suppression including SOX1, SOX3 and GMNN (Week 1) and CEBPA (Week 2). Analysis of "key genes" involved in multiple biological processes appeared to be associated with response of PI3K inhibitortreatment. This included down regulation of CREBBP with a Cancer Risk Score (CRS) of -0.97 and downregulation of VIM, CDH3, WNT3, WNT5B and FGFR2 with a CRS of -2.98 (Fig 1). Conclusion: Results from our pilot study in cNHL showed encouraging clinical responses with a pan-PI3K inhibitor in 3 of 10 dogs. Furthermore, our unbiased characterization of biological pathways revealed that the observed GEP changes associated with tumor suppression and they reduced the risk for cancer progression. Overall, the canine model appears to be particularly attractive model that may be leveraged for the study of clinical and biological responses to novel therapeutic oncologic agents. Disclosures Evens: Bayer: Consultancy; Novartis: Consultancy, Membership on an entity's Board of Directors or advisory committees; Abbvie: Consultancy; Novartis: Consultancy; Acerta: Consultancy; Seattle Genetics, Inc.: Membership on an entity's Board of Directors or advisory committees, Research Funding; Pharmacyclics International DMC: Membership on an entity's Board of Directors or advisory committees; Tesaro: Research Funding; Janssen: Consultancy; Affimed: Consultancy.

Sign in / Sign up

Export Citation Format

Share Document