Duplicated item. See hdl.handle.net/2027.42/90875 for original.

Automated Extraction of Chemical Structure Information from Digital Raster Images

dc.contributor.authorPark, Jungkapen_US
dc.contributor.authorRosania, Gustavo R.en_US
dc.contributor.authorShedden, Kerby A.en_US
dc.contributor.authorNguyen, Mandeeen_US
dc.contributor.authorLyu, Naesung, Saitou, Kazuhiroen_US
dc.date.accessioned2011-11-14T16:31:34Z
dc.date.available2011-11-14T16:31:34Z
dc.date.issued2009-02-05en_US
dc.identifier.citationPark, J.; Rosania, G.; Shedden, K.; Nguyen, M.; Lyu, N.; Saitou, K. (2009). Automated Extraction of Chemical Structure Information from Digital Raster Images." Chemistry Central Journal 3(1-4). <http://hdl.handle.net/2027.42/87281>en_US
dc.identifier.issn1752-153Xen_US
dc.identifier.urihttps://hdl.handle.net/2027.42/87281
dc.description.abstractBackground To search for chemical structures in research articles, diagrams or text representing molecules need to be translated to a standard chemical file format compatible with cheminformatic search engines. Nevertheless, chemical information contained in research articles is often referenced as analog diagrams of chemical structures embedded in digital raster images. To automate analog-to-digital conversion of chemical structure diagrams in scientific research articles, several software systems have been developed. But their algorithmic performance and utility in cheminformatic research have not been investigated. Results This paper aims to provide critical reviews for these systems and also report our recent development of ChemReader - a fully automated tool for extracting chemical structure diagrams in research articles and converting them into standard, searchable chemical file formats. Basic algorithms for recognizing lines and letters representing bonds and atoms in chemical structure diagrams can be independently run in sequence from a graphical user interface-and the algorithm parameters can be readily changed-to facilitate additional development specifically tailored to a chemical database annotation scheme. Compared with existing software programs such as OSRA, Kekule, and CLiDE, our results indicate that ChemReader outperforms other software systems on several sets of sample images from diverse sources in terms of the rate of correct outputs and the accuracy on extracting molecular substructure patterns. Conclusion The availability of ChemReader as a cheminformatic tool for extracting chemical structure information from digital raster images allows research and development groups to enrich their chemical structure databases by annotating the entries with published research articles. Based on its stable performance and high accuracy, ChemReader may be sufficiently accurate for annotating the chemical database with links to scientific research articles.en_US
dc.publisherSpringeren_US
dc.titleAutomated Extraction of Chemical Structure Information from Digital Raster Imagesen_US
dc.typeArticleen_US
dc.subject.hlbsecondlevelMechanical Engineeringen_US
dc.subject.hlbtoplevelEngineeringen_US
dc.description.peerreviewedPeer Revieweden_US
dc.contributor.affiliationumMichigan Alliance for Cheminformatic Explorationen_US
dc.contributor.affiliationumDepartment of Mechanical Engineeringen_US
dc.contributor.affiliationumDepartment of Pharmaceutical Sciencesen_US
dc.contributor.affiliationumDepartment of Statisticsen_US
dc.contributor.affiliationotherFord Motor Company, 3104B, Advanced Engineering Center, 2400 Village Rd., Dearborn, MI 48121, USA.en_US
dc.identifier.pmid19196483en_US
dc.description.withdrawalreasonDuplicated item. See hdl.handle.net/2027.42/90875 for original.
dc.description.bitstreamurlhttp://deepblue.lib.umich.edu/bitstream/2027.42/87281/1/Saitou22.pdf
dc.identifier.doi10.1186/1752-153X-3-4en_US
dc.identifier.sourceChemistry Central Journalen_US
dc.owningcollnameMechanical Engineering, Department of


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