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Journal ArticleDOI

A Review of Algorithms for Border Length Minimization Problem

TLDR
A comparative study of different techniques reported in the literature for border minimization problem and current open challenges in DNA microarrays is presented.
Abstract
Genomic analysis is a gaining prominence, specifically in the areas of forensics and drug discovery. DNA microarrays are the devices employed for performing the genomic analysis. Border minimization problem (BMP) is a well-known optimization problem in the automated design of DNA microarrays. The problem of BMP can be considered from two perspectives, namely placement and embedding. This paper presents a comparative study of different techniques reported in the literature for BMP and current open challenges.

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Citations
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Posted Content

Batch Optimization for DNA Synthesis

TL;DR: The results uncover a surprising separation between two cases that naturally arise in the context of DNA data storage: the asymptotic cost savings of batch optimization are significantly greater in the case where strings in $\mathcal{S}$ do not contain repeats of the same character (homopolymers), as compared to the caseWhere strings in $S are unconstrained.
Patent

Methods for generating polymer arrays

TL;DR: In this article, a polymer array comprising a plurality of polymers, each of which is immobilized at a distinct locations and differs from adjacent polymers by one and only one subunit.
Proceedings ArticleDOI

Batch Optimization for DNA Synthesis

TL;DR: In this article, the authors study the role of batch optimization in reducing the cost of large scale DNA synthesis, which translates to the following algorithmic task: given a large pool of random quaternary strings of fixed length, partition $S$ into batches in a way that minimizes the sum of the lengths of the shortest common supersequences across batches.
Journal ArticleDOI

Batch Optimization for DNA Synthesis

TL;DR: The results uncover a surprising separation between two cases that naturally arise in the context of DNA data storage: the asymptotic cost savings of batch optimization are significantly greater in the case where strings in $\mathcal {S}$ are unconstrained.
Journal ArticleDOI

Optimal Reference for DNA Synthesis

TL;DR: It is proved that for any k (cid:62) 1 , the optimal reference strand, minimizing the cost of DNA synthesis is, perhaps surprisingly, the periodic sequence ACGT .
References
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Journal ArticleDOI

Optimization by Simulated Annealing

TL;DR: There is a deep and useful connection between statistical mechanics and multivariate or combinatorial optimization (finding the minimum of a given function depending on many parameters), and a detailed analogy with annealing in solids provides a framework for optimization of very large and complex systems.
BookDOI

Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control and Artificial Intelligence

TL;DR: Initially applying his concepts to simply defined artificial systems with limited numbers of parameters, Holland goes on to explore their use in the study of a wide range of complex, naturally occuring processes, concentrating on systems having multiple factors that interact in nonlinear ways.
Journal ArticleDOI

No free lunch theorems for optimization

TL;DR: A framework is developed to explore the connection between effective optimization algorithms and the problems they are solving and a number of "no free lunch" (NFL) theorems are presented which establish that for any algorithm, any elevated performance over one class of problems is offset by performance over another class.
Journal ArticleDOI

Molecular Structure of Nucleic Acids: A Structure for Deoxyribose Nucleic Acid

James D. Watson, +1 more
- 25 Apr 1953 - 
TL;DR: The determination in 1953 of the structure of deoxyribonucleic acid (DNA), with its two entwined helices and paired organic bases, was a tour de force in X-ray crystallography and opened the way for a deeper understanding of perhaps the most important biological process.
Book

Tabu Search

TL;DR: This book explores the meta-heuristics approach called tabu search, which is dramatically changing the authors' ability to solve a host of problems that stretch over the realms of resource planning, telecommunications, VLSI design, financial analysis, scheduling, spaceplanning, energy distribution, molecular engineering, logistics, pattern classification, flexible manufacturing, waste management,mineral exploration, biomedical analysis, environmental conservation and scores of other problems.
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