DSpace Repository

ARIADNE: Pattern-Directed Inference and Hierarchical Abstraction in Protein Structure Recognition

Show simple item record

dc.creator Lathrop, Richard H.
dc.creator Webster, Teresa A.
dc.creator Smith, Temple F.
dc.date 2004-10-04T14:56:57Z
dc.date 2004-10-04T14:56:57Z
dc.date 1987-05-01
dc.date.accessioned 2013-10-09T02:45:31Z
dc.date.available 2013-10-09T02:45:31Z
dc.date.issued 2013-10-09
dc.identifier AIM-902
dc.identifier http://hdl.handle.net/1721.1/6452
dc.identifier.uri http://koha.mediu.edu.my:8181/xmlui/handle/1721
dc.description There are many situations in which a very detailed low-level description encodes, through a hierarchical organization, a recognizable higher-order pattern. The macro-molecular structural conformations of proteins exhibit higher order regularities whose recognition is complicated by many factors. ARIADNE searches for similarities between structural descriptors and hypothesized protein structure at levels more abstract than the primary sequence, based on differential similarity to rule antecedents and the controlled use of tentative higher-order structural hypotheses. Inference is grounded solely in knowledge derivable from the primary sequence, and exploits secondary structure predictions. A novel proposed alignment and functional domain identification of the aminoacyl-tRNA synthetases was found using this system.
dc.format 3199888 bytes
dc.format 1268341 bytes
dc.format application/postscript
dc.format application/pdf
dc.language en_US
dc.relation AIM-902
dc.title ARIADNE: Pattern-Directed Inference and Hierarchical Abstraction in Protein Structure Recognition


Files in this item

Files Size Format View

There are no files associated with this item.

This item appears in the following Collection(s)

Show simple item record

Search DSpace


Advanced Search

Browse

My Account