Improved Lower Bounds for Constant GC-Content DNA Codes

TL;DR

This paper introduces a new stochastic local search method that significantly improves lower bounds for constant GC-content DNA codes, enhancing the design of DNA libraries with specific constraints.

Contribution

The paper presents a novel stochastic local search technique and identifies optimal libraries through graph-based maximum clique computations, advancing DNA code construction methods.

Findings

Improved lower bounds by over 33% for n <= 14

Identified several optimal DNA libraries

Enhanced methods for DNA code design

Abstract

The design of large libraries of oligonucleotides having constant GC-content and satisfying Hamming distance constraints between oligonucleotides and their Watson-Crick complements is important in reducing hybridization errors in DNA computing, DNA microarray technologies, and molecular bar coding. Various techniques have been studied for the construction of such oligonucleotide libraries, ranging from algorithmic constructions via stochastic local search to theoretical constructions via coding theory. We introduce a new stochastic local search method which yields improvements up to more than one third of the benchmark lower bounds of Gaborit and King (2005) for n-mer oligonucleotide libraries when n <= 14. We also found several optimal libraries by computing maximum cliques on certain graphs.