scholarly journals First steps in computational systems biology: A practical session in metabolic modeling and simulation

2009 ◽  
Vol 37 (3) ◽  
pp. 178-181 ◽  
Author(s):  
Armando Reyes-Palomares ◽  
Francisca Sánchez-Jiménez ◽  
Miguel Ángel Medina
Keyword(s):  
Systems Biology ◽  
Modeling And Simulation ◽  
Metabolic Modeling ◽  
Computational Systems Biology ◽  
Practical Session ◽  
Computational Systems

scholarly journals Community standards to facilitate development and address challenges in metabolic modeling

2019 ◽  
Author(s):  
Maureen A. Carey ◽  
Andreas Dräger ◽  
Jason A. Papin ◽  
James T. Yurkovich
Keyword(s):  
Systems Biology ◽  
Metabolic Network ◽  
Gold Standard ◽  
Metabolic Modeling ◽  
Computational Systems Biology ◽  
High Quality ◽  
Metabolic Network Reconstruction ◽  
Computational Systems ◽  
Content Annotation

ABSTRACTStandardization of data and models facilitates effective communication, especially in computational systems biology. However, both the development and consistent use of standards and resources remains challenging. As a result, the amount, quality, and format of the information contained within systems biology models are not consistent and therefore present challenges for widespread use and communication. Here, we focused on these standards, resources, and challenges in the field of metabolic modeling by conducting a community-wide survey. We used this feedback to (1) outline the major challenges that our field faces and to propose solutions and (2) identify a set of features that defines what a “gold standard” metabolic network reconstruction looks like concerning content, annotation, and simulation capabilities. We anticipate that this community-driven outline will help the long-term development of community-inspired resources as well as produce high-quality, accessible models. More broadly, we hope that these efforts can serve as blueprints for other computational modeling communities to ensure continued development of both practical, usable standards and reproducible, knowledge-rich models.

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.

The Biodegradation Network, a New Scenario for Computational Systems Biology Research

2005 ◽  
pp. 252-256
Author(s):  
Florencio Pazos ◽  
David Guijas ◽  
Manuel J. Gomez ◽  
Almudena Trigo ◽  
Victor de Lorenzo ◽  
...  
Keyword(s):  
Systems Biology ◽  
Computational Systems Biology ◽  
Computational Systems ◽  
Biology Research
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