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Book Chapter: Targeted metabolic engineering guided by computational analysis of single-nucleotide polymorphisms (SNPs)

TitleTargeted metabolic engineering guided by computational analysis of single-nucleotide polymorphisms (SNPs)
Authors
KeywordsChromosome polymorphism.
Human genetics -- Variation.
Genetic markers.
Microbial genetic engineering.
Issue Date2013
PublisherSpringer
Citation
Targeted metabolic engineering guided by computational analysis of single-nucleotide polymorphisms (SNPs). In Alper, HS (Ed.), Systems metabolic engineering : methods and protocols , p. 409-428. Dordrecht: Springer, 2013 How to Cite?
AbstractThe non-synonymous SNPs, the so-called non-silent SNPs, which are single-nucleotide variations in the coding regions that give “birth” to amino acid mutations, are often involved in the modulation of protein function. Understanding the effect of individual amino acid mutations on a protein/enzyme function or stability is useful for altering its properties for a wide variety of engineering studies. Since measuring the effects of amino acid mutations experimentally is a laborious process, a variety of computational methods have been discussed here that aid to extract direct genotype to phenotype information.
Persistent Identifierhttp://hdl.handle.net/10722/191184
ISSN

 

DC FieldValueLanguage
dc.contributor.authorUdatha, DB-
dc.contributor.authorRasmussen, S-
dc.contributor.authorSicheritz-Pontén, T-
dc.contributor.authorPanagiotou, I-
dc.date.accessioned2013-09-30T07:07:48Z-
dc.date.available2013-09-30T07:07:48Z-
dc.date.issued2013-
dc.identifier.citationTargeted metabolic engineering guided by computational analysis of single-nucleotide polymorphisms (SNPs). In Alper, HS (Ed.), Systems metabolic engineering : methods and protocols , p. 409-428. Dordrecht: Springer, 2013-
dc.identifier.issn9781627032988-
dc.identifier.urihttp://hdl.handle.net/10722/191184-
dc.description.abstractThe non-synonymous SNPs, the so-called non-silent SNPs, which are single-nucleotide variations in the coding regions that give “birth” to amino acid mutations, are often involved in the modulation of protein function. Understanding the effect of individual amino acid mutations on a protein/enzyme function or stability is useful for altering its properties for a wide variety of engineering studies. Since measuring the effects of amino acid mutations experimentally is a laborious process, a variety of computational methods have been discussed here that aid to extract direct genotype to phenotype information.-
dc.languageeng-
dc.publisherSpringer-
dc.relation.ispartofSystems metabolic engineering : methods and protocols-
dc.rightsThe original publication is available at www.springerlink.com-
dc.subjectChromosome polymorphism.-
dc.subjectHuman genetics -- Variation.-
dc.subjectGenetic markers.-
dc.subjectMicrobial genetic engineering.-
dc.titleTargeted metabolic engineering guided by computational analysis of single-nucleotide polymorphisms (SNPs)en_US
dc.typeBook_Chapteren_US
dc.identifier.emailPanagiotou, G: gipa@hku.hk-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1007/978-1-62703-299-5_20-
dc.identifier.pmid23417815-
dc.identifier.hkuros221462-
dc.identifier.spage409-
dc.identifier.epage428-
dc.publisher.placeDordrecht-
dc.customcontrol.immutableyiu 130930-

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