NDLI: Computer-Aided Optimization of DNA Array Design and Manufacturing

Content Provider	IEEE Xplore Digital Library
Author	Kahng, A.B. Mandoiu, I.I. Reda, S. Xu Xu Zelikovsky, A.Z.
Copyright Year	1982
Abstract	DNA probe arrays, or DNA chips, have emerged as a core genomic technology that enables cost-effective gene expression monitoring, mutation detection, single nucleotide polymorphism analysis, and other genomic analyses. DNA chips are manufactured through a highly scalable process called very large-scale immobilized polymer synthesis (VLSIPS) that combines photolithographic technologies adapted from the semiconductor industry with combinatorial chemistry. Commercially available DNA chips contain more than half a million probes and are expected to exceed 100 million probes in the next generation. This paper is one of the first attempts to apply very large scale integration (VLSI) computer-aided design methods to the physical design of DNA chips, where the main objective is to minimize total border cost (i.e., the number of nucleotide mismatches between adjacent sites). By exploiting analogies between manufacturing processes for DNA arrays and for VLSI chips, the authors demonstrate the potential for transfer of methodologies from the 40-year-old field of electronic design automation to the newer DNA array design field. The main contributions of this paper are the following. First, it proposes several partitioning-based algorithms for DNA probe placement that improve solution quality by over 4% compared to best previously known methods. Second, it gives a new design flow for DNA arrays, which enhances current methodologies by adding flow awareness to each optimization step and introducing feedback loops. Third, it proposes solution methods for new formulations integrating multiple design steps, including probe selection, placement, and embedding. Finally, it introduces new techniques to experimentally evaluate the scalability and suboptimality of existing and newly proposed probe placement algorithms. Interestingly, the authors find that DNA placement algorithms appear to have better suboptimality properties than those recently reported for VLSI placement algorithms [C.C. Chang et al., Optimality and scalability study of existing placement algorithms, Proc. Asia South-Pacific Design Automation Conf., Kitakyushu, Japan, p.621-7, Jan. 2003; J. Cong et al., Optimality, scalability and stability study of partitioning and placement algorithms, Proc. Int. Symp. Physical Design (ISPD), Monterey, CA, p.88-94, 2003]
Sponsorship	IEEE Council on Electronic Design Automation IEEE Circuits and Systems Society
Starting Page	305
Ending Page	320
Page Count	16
File Size	481571
File Format	PDF
ISSN	02780070
Volume Number	25
Issue Number	2
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2006-02-01
Publisher Place	U.S.A.
Access Restriction	One Nation One Subscription (ONOS)
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Computer aided manufacturing DNA computing Design optimization Probes Partitioning algorithms Very large scale integration Scalability Genomics Bioinformatics Chemical technology
Content Type	Text
Resource Type	Article
Subject	Computer Graphics and Computer-Aided Design Electrical and Electronic Engineering Software

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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