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Chromosome Reconstruction from Physical Maps Using a Cluster of Workstations

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Abstract

Ordering clones from a genomic library into physical maps of whole chromosomes presents a central computational problem in genetics. Chromosome reconstruction via clone ordering is shown to be isomorphic to the classical NP-complete Optimal Linear Arrangement problem. Parallel algorithms for simulated annealing and microcanonical annealing based on Markov chain decomposition are proposed and applied to the problem of chromosome reconstruction via clone ordering. These algorithms are implemented on a cluster of UNIX workstations using the Parallel Virtual Machine (PVM) system. PVM is a software system that permits a heterogeneous collection of networked computers to be viewed by a user's program as a single monolithic parallel computing resource. The parallel algorithms are implemented and tested on clonal data derived from Chromosome IV of the fungus Asperigillus nidulans Perturbation methods and problem-specific annealing heuristics for the parallel simulated annealing and parallel microcanonical annealing algorithms are proposed and described. Convergence, speedup and scalability characteristics of the various parallel algorithms are analyzed and discussed.

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Authors and Affiliations

  1. Department of Computer Science, University of Georgia, 415 Boyd Graduate Studies Research Center, Athens, GA, 30602-7404, USA

    Suchendra Bhandarkar & Salem Machaka

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  1. Suchendra Bhandarkar
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  2. Salem Machaka
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Bhandarkar, S., Machaka, S. Chromosome Reconstruction from Physical Maps Using a Cluster of Workstations. The Journal of Supercomputing 11, 61–86 (1997). https://doi.org/10.1023/A:1007913429509

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