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NICEpath: Finding metabolic pathways in large networks through atom-conserving substrate–product pairs
Author(s) -
Jasmin Hafner,
Vassily Hatzimanikatis
Publication year - 2021
Publication title -
bioinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.599
H-Index - 390
eISSN - 1367-4811
pISSN - 1367-4803
DOI - 10.1093/bioinformatics/btab368
Subject(s) - metabolic pathway , metabolic network , bioproduction , metabolic engineering , computer science , graph , computational biology , biological network , identification (biology) , theoretical computer science , chemistry , biology , biochemistry , gene , botany
Finding biosynthetic pathways is essential for metabolic engineering of organisms to produce chemicals, biodegradation prediction of pollutants and drugs, and for the elucidation of bioproduction pathways of secondary metabolites. A key step in biosynthetic pathway design is the extraction of novel metabolic pathways from big networks that integrate known biological, as well as novel, predicted biotransformations. However, the efficient analysis and the navigation of big biochemical networks remain a challenge.

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