Resource allocation in living organisms. (7th July 2017)
- Record Type:
- Journal Article
- Title:
- Resource allocation in living organisms. (7th July 2017)
- Main Title:
- Resource allocation in living organisms
- Authors:
- Goelzer, Anne
Fromion, Vincent - Abstract:
- Abstract : Quantitative prediction of resource allocation for living systems has been an intensive area of research in the field of biology. Resource allocation was initially investigated in higher organisms by using empirical mathematical models based on mass distribution. A challenge is now to go a step further by reconciling the cellular scale to the individual scale. In the present paper, we review the foundations of modelling of resource allocation, particularly at the cellular scale: from small macro-molecular models to genome-scale cellular models. We enlighten how the combination of omic measurements and computational advances together with systems biology has contributed to dramatic progresses in the current understanding and prediction of cellular resource allocation. Accurate genome-wide predictive methods of resource allocation based on the resource balance analysis (RBA) framework have been developed and ensure a good trade-off between the complexity/tractability and the prediction capability of the model. The RBA framework shows promise for a wide range of applications in metabolic engineering and synthetic biology, and for pursuing investigations of the design principles of cellular and multi-cellular organisms.
- Is Part Of:
- Biochemical Society transactions. Volume 45:Number 4(2017)
- Journal:
- Biochemical Society transactions
- Issue:
- Volume 45:Number 4(2017)
- Issue Display:
- Volume 45, Issue 4 (2017)
- Year:
- 2017
- Volume:
- 45
- Issue:
- 4
- Issue Sort Value:
- 2017-0045-0004-0000
- Page Start:
- 945
- Page End:
- 952
- Publication Date:
- 2017-07-07
- Subjects:
- constraint-based modelling -- optimality principle -- resource allocation
Biochemistry -- Congresses
572 - Journal URLs:
- https://portlandpress.com/biochemsoctrans ↗
- DOI:
- 10.1042/BST20160436 ↗
- Languages:
- English
- ISSNs:
- 0300-5127
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library HMNTS - ELD Digital store
- Ingest File:
- 11658.xml