Reconstruction of metabolic networks using incomplete information.
This paper describes an approach that uses methods for automated sequence analysis (Gaasterland et al. August 1994) and multiple databases accessed through an object+attribute view of the data (Baehr et al. 1992), together with metabolic pathways, reaction equations, and compounds parsed into a logical representation from the Enzyme and Metabolic Pathway Database (Selkov, Yunus, & et.al. 1994), as the sources of data for automatically reconstructing a weighted partial metabolic network for a prokaryotic organism. Additional information can be provided interactively by the expert user to guide reconstruction.
Gaasterland
T
T
Mathematics and Computer Science Division, Argonne National Laboratory, IL 60432, USA.
Selkov
E
E
D000465:Algorithms; D001331:Automation; D016208:Databases, Factual; D004798:Enzymes / Q000378:metabolism*; D008660:Metabolism; D009174:Mycoplasma / Q000145:classification / Q000235:genetics; D016571:Neural Networks, Computer; D010427:Pentose Phosphate Pathway; D010802:Phylogeny; D011387:Prokaryotic Cells / Q000378:metabolism; D012329:RNA, Bacterial / Q000235:genetics; D012335:RNA, Ribosomal / Q000235:genetics*; D012984:Software; D013149:Spiroplasma / Q000145:classification / Q000235:genetics
D004798:Enzymes; D012329:RNA, Bacterial; D012335:RNA, Ribosomal