@inproceedings{e58dc247a4d24306bcfd127c6c0b03da,
title = "Optimal codon pair bias design (extended abstract)",
abstract = "Codon pair bias is the species-specific phenomenon that pairs of adjacent codons appear in genomes with frequencies different than would be predicted under an independence assumption, and thus is indicative of evolutionary selection. The synthetic attenuated virus engineering (SAVE) paradigm to design vaccines creates weak viruses by designing coding sequences that favor underrepresented codon pairs. Designing genes which achieve the absolute minimum codon pair bias with an arbitrary codon distribution is computationally difficult. In this paper, we develop new algorithms for constructing provably optimal codon pair designs under coding constraints of up to 186 codons in under one minute. We explore a variety of search mechanisms, lower bounds, and pruning strategies to optimize sequences. Our results make it possible for the first time to truly evaluate the performance of commonly used design methods, and quantify the potential improvement possible through better algorithms.",
author = "Nolan Donoghue and Justin Gardin and Bruce Futcher and Steven Skiena",
note = "Publisher Copyright: {\textcopyright} 2017 IEEE.; 2017 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2017 ; Conference date: 13-11-2017 Through 16-11-2017",
year = "2017",
month = dec,
day = "15",
doi = "10.1109/BIBM.2017.8217703",
language = "English",
series = "Proceedings - 2017 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2017",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "529--532",
editor = "Illhoi Yoo and Zheng, \{Jane Huiru\} and Yang Gong and Hu, \{Xiaohua Tony\} and Chi-Ren Shyu and Yana Bromberg and Jean Gao and Dmitry Korkin",
booktitle = "Proceedings - 2017 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2017",
}