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| Content Provider | ACM Digital Library |
|---|---|
| Author | Kundeti, Vamsi Dinh, Hieu Rajasekaran, Sanguthevar |
| Abstract | Protein/Peptide microarrays are rapidly gaining momentum in the diagnosis of cancer. High-density and high-throughput peptide arrays are being extensively used to detect tumor biomarkers, examine kinase activity, identify antibodies having low serum titers and locate antibody signatures. Improving the yield of microarray fabrication involves solving a hard combinatorial optimization problem called the Border Length Minimization Problem (BLMP). An important question that remained open for the past seven years is if the BLMP is tractable or not. We settle this open problem by proving that the BLMP is NP-hard. We also present a hierarchical refinement algorithm which can refine any heuristic solution for the BLMP problem. We also prove that the TSP+1-threading heuristic is an O(N)-approximation. The hierarchical refinement solver is available as an open-source code at http://launchpad.net/blm-solve. |
| Starting Page | 112 |
| Ending Page | 119 |
| Page Count | 8 |
| File Format | |
| ISBN | 9781450304382 |
| DOI | 10.1145/1854776.1854796 |
| Language | English |
| Publisher | Association for Computing Machinery (ACM) |
| Publisher Date | 2010-08-02 |
| Publisher Place | New York |
| Access Restriction | Subscribed |
| Subject Keyword | Border length minimization Microarray optimization Quadratic assignment Appoximation algorithms Computational biology |
| Content Type | Text |
| Resource Type | Article |
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