No Electron Left Behind: A Rule-Based Expert System To Predict Chemical Reactions and Reaction Mechanisms.
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| Title: | No Electron Left Behind: A Rule-Based Expert System To Predict Chemical Reactions and Reaction Mechanisms. |
|---|---|
| Authors: | Jonathan H. Chen1, Pierre Baldi1 |
| Source: | Journal of Chemical Information & Modeling. Sep2009, Vol. 49 Issue 9, p2034-2043. 10p. |
| Subjects: | Chemical reactions, Organic reaction mechanisms, Electrons, Computer assisted research, Drug design, Drug development |
| Abstract: | Predicting the course and major products of arbitrary reactions is a fundamental problem in chemistry, one that chemists must address in a variety of tasks ranging from synthesis design to reaction discovery. Described here is an expert system to predict organic chemical reactions based on a knowledge base of over 1500 manually composed reaction transformation rules. Novel rule extensions are introduced to enable robust predictions and describe detailed reaction mechanisms at the level of electron flows in elementary reaction steps, ensuring that all reactions are properly balanced and atom-mapped. The core reaction prediction functionalities of this expert system are illustrated with applications including: (1) prediction of detailed reaction mechanisms; (2) computer-based learning in organic chemistry; (3) retrosynthetic analysis; and (4) combinatorial library design. Select applications are available via http://cdb.ics.uci.edu. [ABSTRACT FROM AUTHOR] |
| Copyright of Journal of Chemical Information & Modeling is the property of American Chemical Society and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
| FullText | Text: Availability: 0 |
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| Header | DbId: egs DbLabel: Engineering Source An: 44778990 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: No Electron Left Behind: A Rule-Based Expert System To Predict Chemical Reactions and Reaction Mechanisms. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Jonathan+H%2E+Chen%22">Jonathan H. Chen</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Pierre+Baldi%22">Pierre Baldi</searchLink><relatesTo>1</relatesTo> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Journal+of+Chemical+Information+%26+Modeling%22">Journal of Chemical Information & Modeling</searchLink>. Sep2009, Vol. 49 Issue 9, p2034-2043. 10p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Chemical+reactions%22">Chemical reactions</searchLink><br /><searchLink fieldCode="DE" term="%22Organic+reaction+mechanisms%22">Organic reaction mechanisms</searchLink><br /><searchLink fieldCode="DE" term="%22Electrons%22">Electrons</searchLink><br /><searchLink fieldCode="DE" term="%22Computer+assisted+research%22">Computer assisted research</searchLink><br /><searchLink fieldCode="DE" term="%22Drug+design%22">Drug design</searchLink><br /><searchLink fieldCode="DE" term="%22Drug+development%22">Drug development</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: Predicting the course and major products of arbitrary reactions is a fundamental problem in chemistry, one that chemists must address in a variety of tasks ranging from synthesis design to reaction discovery. Described here is an expert system to predict organic chemical reactions based on a knowledge base of over 1500 manually composed reaction transformation rules. Novel rule extensions are introduced to enable robust predictions and describe detailed reaction mechanisms at the level of electron flows in elementary reaction steps, ensuring that all reactions are properly balanced and atom-mapped. The core reaction prediction functionalities of this expert system are illustrated with applications including: (1) prediction of detailed reaction mechanisms; (2) computer-based learning in organic chemistry; (3) retrosynthetic analysis; and (4) combinatorial library design. Select applications are available via http://cdb.ics.uci.edu. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Journal of Chemical Information & Modeling is the property of American Chemical Society and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1021/ci900157k Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 10 StartPage: 2034 Subjects: – SubjectFull: Chemical reactions Type: general – SubjectFull: Organic reaction mechanisms Type: general – SubjectFull: Electrons Type: general – SubjectFull: Computer assisted research Type: general – SubjectFull: Drug design Type: general – SubjectFull: Drug development Type: general Titles: – TitleFull: No Electron Left Behind: A Rule-Based Expert System To Predict Chemical Reactions and Reaction Mechanisms. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Jonathan H. Chen – PersonEntity: Name: NameFull: Pierre Baldi IsPartOfRelationships: – BibEntity: Dates: – D: 28 M: 09 Text: Sep2009 Type: published Y: 2009 Identifiers: – Type: issn-print Value: 15499596 Numbering: – Type: volume Value: 49 – Type: issue Value: 9 Titles: – TitleFull: Journal of Chemical Information & Modeling Type: main |
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