TY - JOUR
AU - Zhu, Enqiang
AB - DNA computing is an emerging computational model that has garnered significant attention due to its distinctive advantages at the molecular biological level. Since it was introduced by Adelman in 1994, this field has made remarkable progress in solving NP-complete problems, enhancing information security, encrypting images, controlling diseases, and advancing nanotechnology. A key challenge in DNA computing is the design of DNA coding, which aims to minimize nonspecific hybridization and enhance computational reliability. The DNA coding design is a classical combinatorial optimization problem focused on generating high-quality DNA sequences that meet specific constraints, including distance, thermodynamics, secondary structure, and sequence requirements. This paper comprehensively examines the advances in DNA coding design, highlighting mathematical models, counting theory, and commonly used DNA coding methods. These methods include the template method, multi-objective evolutionary methods, and implicit enumeration techniques.
TI - Dna coding theory and algorithms
JF - Artificial Intelligence Review
DO - 10.1007/s10462-025-11132-x
DA - 2025-03-21
UR - https://www.deepdyve.com/lp/springer-journals/dna-coding-theory-and-algorithms-ORbAwCw5N0
VL - 58
IS - 6
DP - DeepDyve
ER -