PubMed:15044386 / 256-455 JSONTXT

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{"project":"GlyCosmos600-FMA","denotations":[{"id":"T3","span":{"begin":47,"end":54},"obj":"Body_part"},{"id":"T4","span":{"begin":79,"end":85},"obj":"Body_part"},{"id":"T5","span":{"begin":133,"end":143},"obj":"Body_part"}],"attributes":[{"id":"A3","pred":"fma_id","subj":"T3","obj":"http://purl.org/sig/ont/fma/fma67257"},{"id":"A4","pred":"fma_id","subj":"T4","obj":"http://purl.org/sig/ont/fma/fma84116"},{"id":"A5","pred":"fma_id","subj":"T5","obj":"http://purl.org/sig/ont/fma/fma82739"}],"text":"To effectively predict mucins from genomic and protein sequences obtained from genome projects, we developed a strategy based on the amino acid compositional bias characteristic of the mucin domains."}