ON THE HARDNESS OF THE BORDER LENGTH MINIMIZATION PROBLEM ON A RECTANGULAR ARRAY

Abstract

DNA microarray technology has proven to be an invaluable tool for molecular biologists. Microarrays are used extensively in SNP detection, genomic hybridization, alternative splicing and gene expression profiling. However the manufacturers of the microarrays are often stuck with the problem of minimizing the effects of unwanted illumination (border length minimization (BLM)) which is a hard combinatorial problem. In this paper we prove that the BLM problem on a rectangular grid is NP-hard – this however does not mean the BLM problem on a square grid is NP-hard. We also give the first integer linear programming (ILP) formulation to solve BLM problem optimally. Experimental results indicate that our ILP method produces superior results (both in runtime and cost) compared to the current state of the art algorithms to solve the BLM problem optimally.