Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:dateCreated
1997-1-30
pubmed:abstractText
We present a methodology for predicting the metabolic pathways of an organism from its genomic sequence by reference to a knowledge base of known metabolic pathways. We applied these techniques to the genome of H. influenzae by reference to the EcoCyc knowledge base to predict which of 81 metabolic pathways of E. coli are found in H. influenzae. The resulting prediction is a complex hypothesis that is presented in computer form as HinCyc: an electronic encyclopedia of the genes and metabolic pathways of H. influenzae. HinCyc connects the predicted genes, enzymes, enzyme-catalyzed reactions, and biochemical pathways in a WWW-accessible knowledge base to allow scientists to explore this complex hypothesis.
pubmed:grant
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:issn
1553-0833
pubmed:author
pubmed:issnType
Print
pubmed:volume
4
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
116-24
pubmed:dateRevised
2007-11-14
pubmed:meshHeading
pubmed:year
1996
pubmed:articleTitle
HinCyc: a knowledge base of the complete genome and metabolic pathways of H. influenzae.
pubmed:affiliation
Artificial Intelligence Center, SRI International, Menlo Park, CA 94025, USA. pkarp@ai.sri.com
pubmed:publicationType
Journal Article, Research Support, U.S. Gov't, P.H.S., Research Support, Non-U.S. Gov't