CAVE: a cloud-based platform for analysis and visualization of metabolic pathways
Zhi-Tao Mao,Qianqian Yuan,Haoran Li,Ruoyu Wang,Yongfu Yang,Ya-lun Wu,Shihui Yang,Xiaoping Liao,Hong Ma +8 more
TL;DR: CAVE as mentioned in this paper is a cloud-based platform for the integrated calculation, visualization, examination and correction of metabolic pathways, which can be applied to a broader range of organisms for rational metabolic engineering.
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Abstract: Abstract Flux balance analysis (FBA) is an important method for calculating optimal pathways to produce industrially important chemicals in genome-scale metabolic models (GEMs). However, for biologists, the requirement of coding skills poses a significant obstacle to using FBA for pathway analysis and engineering target identification. Additionally, a time-consuming manual drawing process is often needed to illustrate the mass flow in an FBA-calculated pathway, making it challenging to detect errors or discover interesting metabolic features. To solve this problem, we developed CAVE, a cloud-based platform for the integrated calculation, visualization, examination and correction of metabolic pathways. CAVE can analyze and visualize pathways for over 100 published GEMs or user-uploaded GEMs, allowing for quicker examination and identification of special metabolic features in a particular GEM. Additionally, CAVE offers model modification functions, such as gene/reaction removal or addition, making it easy for users to correct errors found in pathway analysis and obtain more reliable pathways. With a focus on the design and analysis of optimal pathways for biochemicals, CAVE complements existing visualization tools based on manually drawn global maps and can be applied to a broader range of organisms for rational metabolic engineering. CAVE is available at https://cave.biodesign.ac.cn/.
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References
Cytoscape: A Software Environment for Integrated Models of Biomolecular Interaction Networks
Paul Shannon,Andrew Markiel,Owen Ozier,Nitin S. Baliga,Jonathan T. Wang,Daniel Ramage,Nada Amin,Benno Schwikowski,Trey Ideker +8 more
TL;DR: Several case studies of Cytoscape plug-ins are surveyed, including a search for interaction pathways correlating with changes in gene expression, a study of protein complexes involved in cellular recovery to DNA damage, inference of a combined physical/functional interaction network for Halobacterium, and an interface to detailed stochastic/kinetic gene regulatory models.
What is flux balance analysis
TL;DR: This primer covers the theoretical basis of the approach, several practical examples and a software toolbox for performing the calculations.
Quantitative prediction of cellular metabolism with constraint-based models: the COBRA Toolbox v2.0
Jan Schellenberger,Richard Que,Ronan M. T. Fleming,Ines Thiele,Jeffrey D. Orth,Adam M. Feist,Daniel C. Zielinski,Aarash Bordbar,Nathan E. Lewis,Sorena Rahmanian,Joseph Kang,Daniel R. Hyduke,Bernhard O. Palsson +12 more
TL;DR: The constraint-based reconstruction and analysis toolbox as discussed by the authors is a software package running in the Matlab environment, which allows for quantitative prediction of cellular behavior using a constraintbased approach and allows predictive computations of both steady-state and dynamic optimal growth behavior, the effects of gene deletions, comprehensive robustness analyses, sampling the range of possible cellular metabolic states and the determination of network modules.
What is flux balance analysis?
Jeffrey D. Orth,Ines Thiele,Bernhard O. Palsson +2 more
TL;DR: This primer covers the theoretical basis of the approach, several practical examples and a software toolbox for performing the calculations.
1.8K
Global reconstruction of the human metabolic network based on genomic and bibliomic data
Natalie C. Duarte,Scott A Becker,Neema Jamshidi,Ines Thiele,Monica L. Mo,Thuy D. Vo,Rohith Srivas,Bernhard O. Palsson +7 more
TL;DR: The reconstruction process is described and it is demonstrated how the resulting genome-scale (or global) network can be used for the discovery of missing information, for the formulation of an in silico model, and as a structured context for analyzing high-throughput biological data sets.
1.5K