Learning and Inference in Computational Systems Biology. Computational Molecular Biology. Edited by Neil D. Lawrence, Mark Girolami, Magnus Rattray, and Guido Sanguinetti. Cambridge (Massachusetts): MIT Press. $40.00. viii + 362 p.; ill.; index. ISBN: 978-0-262-01386-4. 2010.

2012 ◽  
Vol 87 (2) ◽  
pp. 143-143
Author(s):  
Terence P. Speed
Keyword(s):  
Systems Biology ◽  
Molecular Biology ◽  
Computational Systems Biology ◽  
Computational Molecular Biology ◽  
Computational Systems

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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