Algorithmic Approach for finding Convolutional Code generators for the Translation Initiation of Escherichia coli K-12.

E.coli;mRNA translation;convolutional code model

Ponnala, Lalit ; Winser E. Alexander, Committee Co-Chair,Donald L. Bitzer, Committee Co-Chair,Ponnala, Lalit ; Winser E. Alexander ; Committee Co-Chair ; Donald L. Bitzer ; Committee Co-Chair

University:North Carolina State University

关键词: E.coli;    mRNA translation;    convolutional code model;   

Others  :  https://repository.lib.ncsu.edu/bitstream/handle/1840.16/2092/etd.pdf?sequence=1&isAllowed=y

美国|英语

来源: null

【 摘 要 】

Using error-control coding theory, we parallel the functionality of the translation of mRNA into amino acids to the decoding of noisy parity streams that have been encoded using a convolutional code. This enables us to model the ribosome as a table-based convolution decoder. In this work, we attempt to find plausible convolutional code generators for the translation initiation of Escherichia coli K-12. We choose the g-mask from the exposed part of the 16S rRNA. We develop an algorithmic approach to calculate the generators from the g-mask. We assign plausibility to the generators based on their ability to produce encoded sequences which exhibit a clear distinction between the translated and non-translated sequences. We also explore the construction of g-masks based on binding patterns, and evaluate the performance of the corresponding generators.