Proceedings of the 2017 5th International Conference on Frontiers of Manufacturing Science and Measuring Technology (FMSMT 2017)

Application of Analytic Number Theory in Bioinformatics

Authors
Jinrui Wang
Corresponding Author
Jinrui Wang
Available Online April 2017.
DOI
https://doi.org/10.2991/fmsmt-17.2017.63How to use a DOI?
Keywords
Analytic Number Theory, Bioinformatics, Application Study
Abstract
Many topics in the field of bioinformatics can be abstracted into character sequence processing problems, such as gene recognition, protein secondary structure prediction, and so on. The sequence of characters can provide information from two aspects: composition and arrangement. The composition of the information can be used to reflect the conventional frequency. The key to the problem is how to reflect the arrangement of the character sequence. On the basis of summarizing the existing algorithms, this paper attempts to view the problem of character sequence analysis from the perspective of number theory, and puts forward the analytic number theory model of character sequence. In this model, the character sequence is regarded as a representation of the number, so that the problem of character sequence analysis is transformed into a number theory problem and solved by mathematical analysis method.
Open Access
This is an open access article distributed under the CC BY-NC license.

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Cite this article

TY  - CONF
AU  - Jinrui Wang
PY  - 2017/04
DA  - 2017/04
TI  - Application of Analytic Number Theory in Bioinformatics
BT  - Proceedings of the 2017 5th International Conference on Frontiers of Manufacturing Science and Measuring Technology (FMSMT 2017)
PB  - Atlantis Press
SP  - 292
EP  - 295
SN  - 2352-5401
UR  - https://doi.org/10.2991/fmsmt-17.2017.63
DO  - https://doi.org/10.2991/fmsmt-17.2017.63
ID  - Wang2017/04
ER  -