Abstract: A method for determining an optimized nucleotide sequence encoding a predetermined amino acid sequence, wherein the nucleotide sequence is optimized for expression in a host cell, and wherein the method comprises the steps of: (a) generating a plurality of candidate nucleotide sequences encoding the predetermined amino acid sequence; (b) obtaining a sequence score based on a scoring function based on a plurality of sequence features that influence protein expression in the host cell using a statistical machine learning algorithm, wherein the plurality of sequence features comprises one or more sequence features selected from the group consisting of protein per time, average elongation rate and accuracy for each of the plurality of candidate nucleotide sequences of step (a); and (c) determining the candidate nucleotide sequence with optimized protein expression in the host cell as the optimized nucleotide sequence.

Abstract: A method for determining an optimized nucleotide sequence encoding a predetermined amino acid sequence, wherein the nucleotide sequence is optimized for expression in a host cell, and wherein the method comprises the steps of: (a) generating a plurality of candidate nucleotide sequences encoding the predetermined amino acid sequence; (b) obtaining a sequence score based on a scoring function based on a plurality of sequence features that influence protein expression in the host cell using a statistical machine learning algorithm, wherein the plurality of sequence features comprises one or more sequence features selected from the group consisting of protein per time, average elongation rate and accuracy for each of the plurality of candidate nucleotide sequences of step (a); and (c) determining the candidate nucleotide sequence with optimized protein expression in the host cell as the optimized nucleotide sequence.