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Parallel Optimization of Synthetic Pathways within the Network of Organic Chemistry
Author(s) -
Kowalik Mikołaj,
Gothard Chris M.,
Drews Aaron M.,
Gothard Nosheen A.,
Weckiewicz Alex,
Fuller Patrick E.,
Grzybowski Bartosz A.,
Bishop Kyle J. M.
Publication year - 2012
Publication title -
angewandte chemie international edition
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 5.831
H-Index - 550
eISSN - 1521-3773
pISSN - 1433-7851
DOI - 10.1002/anie.201202209
Subject(s) - haystack , computer science , synthetic data , synthetic biology , information retrieval , data science , artificial intelligence , computational biology , biology
Finding a needle in a haystack : The number of possible synthetic pathways leading to the desired target of a synthesis can be astronomical (10 19 within five synthetic steps). Algorithms are described that navigate through the entire known chemical‐synthetic knowledge to identify optimal synthetic pathways. Examples are provided to illustrate single‐target optimization and parallel optimization of syntheses leading to multiple targets.