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Automated network generation and analysis of biochemical reaction pathways using RING
- Source :
- Metabolic Engineering. 49:84-93
- Publication Year :
- 2018
- Publisher :
- Elsevier BV, 2018.
-
Abstract
- This paper describes how Rule Input Network Generator (RING), a network generation computational tool, can be adopted to generate a variety of complex biochemical reaction networks. The reaction language incorporated in RING allows representation of chemical compounds in biological systems with various structural complexity. Complex molecules such as oligosaccharides in glycosylation pathways can be described using a simplified representation of their monosaccharide building blocks and glycosidic bonds. The automated generation and topological network analysis features in RING also allow for: (1) constructing biochemical reaction networks in a rule-based manner, (2) generating graphical representations of the networks, (3) querying molecules containing a particular structural pattern, (4) finding the shortest synthetic pathways to a user-specified species, and (5) performing enzyme knockout to study their effect on the reaction network. Case studies involving three biochemical reaction systems: (1) Synthesis of 2-ketoglutarate from xylose in bacterial cells, (2) N-glycosylation in mammalian cells, and (3) O-glycosylation in mammalian cells are presented to demonstrate the capabilities of RING for robust and exhaustive network generation and the advantages of its post-processing features.
- Subjects :
- 0301 basic medicine
Glycosylation
Computer science
Bioengineering
Ring (chemistry)
01 natural sciences
Applied Microbiology and Biotechnology
03 medical and health sciences
chemistry.chemical_compound
Animals
Humans
Molecule
Representation (mathematics)
chemistry.chemical_classification
Bacteria
010405 organic chemistry
Network generation
Glycosidic bond
0104 chemical sciences
Metabolism
030104 developmental biology
chemistry
Biological system
Software
Biotechnology
Generator (mathematics)
Network analysis
Subjects
Details
- ISSN :
- 10967176
- Volume :
- 49
- Database :
- OpenAIRE
- Journal :
- Metabolic Engineering
- Accession number :
- edsair.doi.dedup.....de8805df5051506f4c084ba0946c05e7
- Full Text :
- https://doi.org/10.1016/j.ymben.2018.07.009