A Novel Method to Predict Highly Expressed Genes Based on Radius Clustering and Relative Synonymous Codon Usage

摘要

Abstract Recombinant proteins play an important role in many aspects of life and have generated a huge income, notably in the industrial enzyme business. A gene is introduced into a vector and expressed in a host organism—for example, E. coli—to obtain a high productivity of target protein. However, transferred genes from particular organisms are not usually compatible with the host's expression system because of various reasons, for example, codon usage bias, GC content, repetitive sequences, and secondary structure. The solution is developing programs to optimize for designing a nucleotide sequence whose origin is from peptide sequences using properties of highly expressed genes (HEGs) of the host organism. Existing data of HEGs determined by practical and computer-based methods do not satisfy for qualifying and quantifying. Therefore, the demand for developing a new HEG prediction method is critical. We proposed a new method for predicting HEGs and criteria to evaluate gene optimization. Codon usage bi..." /> rel="meta" type="application/atom+xml" href="http://dx.doi.org/10.1089%2Fcmb.2015.0121" /> rel="meta" type="application/rdf+json" href="http://dx.doi.org/10.1089%2Fcmb.2015.0121" /> rel="meta" type="application/unixref+xml" href="http://dx.doi.org/10.1089%2Fcmb.2015.0121" /> 展开▼