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Exploration of sequence space for protein engineering
Author(s) -
Gustafsson Claes,
Govindarajan Sridhar,
Emig Robin
Publication year - 2001
Publication title -
journal of molecular recognition
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.401
H-Index - 79
eISSN - 1099-1352
pISSN - 0952-3499
DOI - 10.1002/jmr.543
Subject(s) - sequence (biology) , sequence space , heuristic , function (biology) , field (mathematics) , characterization (materials science) , computer science , space (punctuation) , protein engineering , protein sequencing , artificial intelligence , mathematics , peptide sequence , biology , nanotechnology , genetics , materials science , biochemistry , gene , pure mathematics , banach space , enzyme , operating system
The process of protein engineering is currently evolving towards a heuristic understanding of the sequence–function relationship. Improved DNA sequencing capacity, efficient protein function characterization and improved quality of data points in conjunction with well‐established statistical tools from other industries are changing the protein engineering field. Algorithms capturing the heuristic sequence–function relationships will have a drastic impact on the field of protein engineering. In this review, several alternative approaches to quantitatively assess sequence space are discussed and the relatively few examples of wet‐lab validation of statistical sequence–function characterization/correlation are described. Copyright © 2001 John Wiley & Sons, Ltd.