scholarly journals Standards and ontologies in computational systems biology

2008 ◽  
Vol 45 ◽  
pp. 211-222 ◽  
Author(s):  
Herbert M. Sauro ◽  
Frank T. Bergmann
Keyword(s):  
Systems Biology ◽  
Computational Models ◽  
Software Tools ◽  
Computational Systems Biology ◽  
Modelling Languages ◽  
Systems Biology Markup Language ◽  
Visualization Tools ◽  
Computational Systems ◽  
Model Interchange ◽  
Model Annotation

With the growing importance of computational models in systems biology there has been much interest in recent years to develop standard model interchange languages that permit biologists to easily exchange models between different software tools. In the present chapter two chief model exchange standards, SBML (Systems Biology Markup Language) and CellML are described. In addition, other related features including visual layout initiatives, ontologies and best practices for model annotation are discussed. Software tools such as developer libraries and basic editing tools are also introduced, together with a discussion on the future of modelling languages and visualization tools in systems biology.

6. Simulators

2020 ◽  
pp. 79-107
Author(s):  
Eberhard O. Voit
Keyword(s):  
Metabolic Engineering ◽  
Systems Biology ◽  
Organic Compounds ◽  
Computational Models ◽  
Computational Systems Biology ◽  
Bulk Materials ◽  
Growth Simulation ◽  
Practical Applications ◽  
Crop Development ◽  
Computational Systems

Computational models can serve many purposes, but a particularly powerful application of a model is its use as a system simulator. An emerging branch of computational systems biology strives to develop simulators for complex systems in biology and medicine, the premier example being a disease simulator. ‘Simulators’ discusses the nascent efforts towards the development of simulators for practical applications. Disease simulators will deepen our understanding of the physiology of human diseases and their treatment. Simulators in metabolic engineering have the goal of improving the microbial production of bulk materials and of valuable organic compounds. Relatively simple simulators for the production of biofuels and for crop development, such as the Soybean Growth Simulation Model (SoySim), are already in use.

scholarly journals Metabolic Reprogramming of Fibroblasts as Therapeutic Target in Rheumatoid Arthritis and Cancer: Deciphering Key Mechanisms Using Computational Systems Biology Approaches

Cancers ◽  
2020 ◽  
Vol 13 (1) ◽  
pp. 35
Author(s):  
Sahar Aghakhani ◽  
Naouel Zerrouk ◽  
Anna Niarakis
Keyword(s):  
Rheumatoid Arthritis ◽  
Extracellular Matrix ◽  
Systems Biology ◽  
Healing Process ◽  
Metabolic Reprogramming ◽  
Critical Event ◽  
Wound Healing Process ◽  
Computational Systems Biology ◽  
Structural Framework ◽  
Computational Systems

Fibroblasts, the most abundant cells in the connective tissue, are key modulators of the extracellular matrix (ECM) composition. These spindle-shaped cells are capable of synthesizing various extracellular matrix proteins and collagen. They also provide the structural framework (stroma) for tissues and play a pivotal role in the wound healing process. While they are maintainers of the ECM turnover and regulate several physiological processes, they can also undergo transformations responding to certain stimuli and display aggressive phenotypes that contribute to disease pathophysiology. In this review, we focus on the metabolic pathways of glucose and highlight metabolic reprogramming as a critical event that contributes to the transition of fibroblasts from quiescent to activated and aggressive cells. We also cover the emerging evidence that allows us to draw parallels between fibroblasts in autoimmune disorders and more specifically in rheumatoid arthritis and cancer. We link the metabolic changes of fibroblasts to the toxic environment created by the disease condition and discuss how targeting of metabolic reprogramming could be employed in the treatment of such diseases. Lastly, we discuss Systems Biology approaches, and more specifically, computational modeling, as a means to elucidate pathogenetic mechanisms and accelerate the identification of novel therapeutic targets.

Systems biology markup language: Level 2 and beyond

2003 ◽  
Vol 31 (6) ◽  
pp. 1472-1473 ◽  
Author(s):  
A. Finney ◽  
M. Hucka
Keyword(s):  
Systems Biology ◽  
Computational Models ◽  
Chemical Species ◽  
Biochemical Networks ◽  
Markup Language ◽  
Exchange Format ◽  
Systems Biology Markup Language ◽  
Level 3 ◽  
Level 1 ◽  
Level 2

The SBML (systems biology markup language) is a standard exchange format for computational models of biochemical networks. We continue developing SBML collaboratively with the modelling community to meet their evolving needs. The recently introduced SBML Level 2 includes several enhancements to the original Level 1, and features under development for SBML Level 3 include model composition, multistate chemical species and diagrams.

scholarly journals A standard-enabled workflow for synthetic biology

2017 ◽  
Vol 45 (3) ◽  
pp. 793-803 ◽  
Author(s):  
Chris J. Myers ◽  
Jacob Beal ◽  
Thomas E. Gorochowski ◽  
Hiroyuki Kuwahara ◽  
Curtis Madsen ◽  
...  
Keyword(s):  
Systems Biology ◽  
Synthetic Biology ◽  
Markup Language ◽  
Design Tools ◽  
Data Standards ◽  
Data Repositories ◽  
Simulation Tools ◽  
Systems Biology Markup Language ◽  
Visualization Tools ◽  
Synthetic Biology Open Language

A synthetic biology workflow is composed of data repositories that provide information about genetic parts, sequence-level design tools to compose these parts into circuits, visualization tools to depict these designs, genetic design tools to select parts to create systems, and modeling and simulation tools to evaluate alternative design choices. Data standards enable the ready exchange of information within such a workflow, allowing repositories and tools to be connected from a diversity of sources. The present paper describes one such workflow that utilizes, among others, the Synthetic Biology Open Language (SBOL) to describe genetic designs, the Systems Biology Markup Language to model these designs, and SBOL Visual to visualize these designs. We describe how a standard-enabled workflow can be used to produce types of design information, including multiple repositories and software tools exchanging information using a variety of data standards. Recently, the ACS Synthetic Biology journal has recommended the use of SBOL in their publications.

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