A Joint DNA Encoding Approach Based on LZW and Arithmetic Encoding

Molecular communication (MC) represents a novel approach to communication that employs nanoengineering and bioengineering technology to establish transient communication links in challenging environments. Deoxyribonucleic acid (DNA) molecular communication can transmit more and faster data than traditional molecular communication. Deoxyribonucleic acid (DNA) has been demonstrated to offer significant advantages over traditional information carriers, including its excellent storage density and structural stability, which renders it an ideal medium for information transmission. It is therefore imperative to investigate methods of increasing the data information density of DNA in order to reduce costs and enhance overall performance. LZW encoding is Lempel–Ziv–Welch encoding which creates a string table with shorter codes representing longer strings. Arithmetic coding is a compression process that involves the continuous refinement of probabilities of the input stream within an interval. A notable drawback of LZW coding is its suboptimal compression efficiency and the presence of data redundancy after dictionary mapping. Conversely, arithmetic coding attains compression efficiency that approaches the Shannon limit. In this study, we propose a novel DNA encoding method which is capable of adaptively generating coding streams in accordance with the characteristics of the stored content. The contribution of this paper is as follows: 1) A bespoke coding dictionary is constructed, which is capable of intelligently generating the corresponding coding stream in accordance with the specific characteristics of the file to be stored. 2) Utilising arithmetic coding techniques, these coding streams are converted into the final DNA sequence by means of compression techniques. Following comprehensive verification, it has been established that the information density of this encoding method is markedly superior to that of the prevailing mainstream encoding schemes.

Authors

Institutions

Publication Details

Journal
IEEE Transactions on Molecular Biological and Multi-Scale Communications
Published
2025-04-03
DOI
https://doi.org/10.1109/tmbmc.2025.3556858
Citations
1
Primary Topic
DNA and Biological Computing
Type
article
Field-Weighted Citation Impact
0.81

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

A Joint DNA Encoding Approach Based on LZW and Arithmetic Encoding

Zhigang Cheng, Qiang Liu, Kun Yang
1 citations
IEEE Transactions on Molecular Biological and Multi-Scale Communications
DNA and Biological Computing
0.81
article

A Joint DNA Encoding Approach Based on LZW and Arithmetic Encoding

Zhigang Cheng, Qiang Liu, Kun Yang
article en
1 citations

Abstract

Molecular communication (MC) represents a novel approach to communication that employs nanoengineering and bioengineering technology to establish transient communication links in challenging environments. Deoxyribonucleic acid (DNA) molecular communication can transmit more and faster data than traditional molecular communication. Deoxyribonucleic acid (DNA) has been demonstrated to offer significant advantages over traditional information carriers, including its excellent storage density and structural stability, which renders it an ideal medium for information transmission. It is therefore imperative to investigate methods of increasing the data information density of DNA in order to reduce costs and enhance overall performance. LZW encoding is Lempel–Ziv–Welch encoding which creates a string table with shorter codes representing longer strings. Arithmetic coding is a compression process that involves the continuous refinement of probabilities of the input stream within an interval. A notable drawback of LZW coding is its suboptimal compression efficiency and the presence of data redundancy after dictionary mapping. Conversely, arithmetic coding attains compression efficiency that approaches the Shannon limit. In this study, we propose a novel DNA encoding method which is capable of adaptively generating coding streams in accordance with the characteristics of the stored content. The contribution of this paper is as follows: 1) A bespoke coding dictionary is constructed, which is capable of intelligently generating the corresponding coding stream in accordance with the specific characteristics of the file to be stored. 2) Utilising arithmetic coding techniques, these coding streams are converted into the final DNA sequence by means of compression techniques. Following comprehensive verification, it has been established that the information density of this encoding method is markedly superior to that of the prevailing mainstream encoding schemes.

IEEE Transactions on Molecular Biological and Multi-Scale CommunicationsVol. 11(2)
University of Essex (GB), University of Electronic Science and Technology of China (CN), Quzhou University (CN)
National Natural Science Foundation of China
Zero hunger
Openalex Percentile: Top 29%
DNA and Biological Computing
0.81
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.