Book chapter · Journal article
Targeted Metabolic Engineering Guided by Computational Analysis of Single-Nucleotide Polymorphisms (SNPs)
Chalmers University of Technology1
Center for Biological Sequence Analysis, Department of Systems Biology, Technical University of Denmark2
Department of Systems Biology, Technical University of Denmark3
Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark4
CFB - Metagenomic Systems Biology, Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark5
The University of Hong Kong6
The 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.
Language: | English |
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Publisher: | Springer |
Year: | 2013 |
Pages: | 409-428 |
Series: | Methods in Molecular Biology |
ISBN: | 1627032983 , 1627032991 , 9781627032988 and 9781627032995 |
ISSN: | 10643745 and 19406029 |
Types: | Book chapter and Journal article |
DOI: | 10.1007/978-1-62703-299-5_20 |
ORCIDs: | Rasmussen, Simon |
Amino Acid Substitution Amino acid substitution Computational Biology Genome Genome sequencing Genotyping Techniques Metabolic Engineering Metabolic engineering Microbial cell factories Models, Biological Polymorphism, Single Nucleotide Protein Stability Protein stability Saccharomyces cerevisiae Saccharomyces cerevisiae Proteins Sequence Alignment Sequence Analysis, DNA Single-nucleotide polymorphism