Years and Authors of Summarized Original Work
2002; Bader, Moret, Warnow
Problem Definition
In the 50 years since the discovery of the structure of DNA, and with new techniques for sequencing the entire genome of organisms, biology is rapidly moving towards a data-intensive, computational science. Many of the newly faced challenges require high-performance computing, either due to the massive-parallelism required by the problem, or the difficult optimization problems that are often combinatoric and NP-hard. Unlike the traditional uses of supercomputers for regular, numerical computing, many problems in biology are irregular in structure, significantly more challenging to parallelize, and integer-based using abstract data structures.
Biologists are in search of biomolecular sequence data, for its comparison with other genomes, and because its structure determines function and leads to the understanding of biochemical pathways, disease prevention and cure, and the mechanisms of life...
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Recommended Reading
Bader DA, Moret BME, Warnow T, Wyman SK, Yan M (2001) High-performance algorithm engineering for gene-order phylogenies. In: DIMACS workshop on whole genome comparison. Rutgers University, Piscataway
Bader DA, Moret BME, Vawter L (2001) Industrial applications of high-performance computing for phylogeny reconstruction. In: Siegel HJ (ed) Proceedings of the SPIE commercial applications for high-performance computing, vol 4528. Denver, pp 159–168
Bader DA, Moret BME, Yan M (2001) A linear-time algorithm for computing inversion distance between signed permutations with an experimental study. J Comput Biol 8(5):483–491
Farris JS (1983) The logical basis of phylogenetic analysis. In: Platnick NI, Funk VA (eds) Advances in cladistics. Columbia University Press, New York, pp 1–36
Felsenstein J (1981) Evolutionary trees from DNA sequences: a maximum likelihood approach. J Mol Evol 17:368–376
Moret BME, Bader DA, Warnow T, Wyman SK, Yan M (2001) GRAPPA: a high performance computational tool for phylogeny reconstruction from gene-order data. In: Proceedings of the botany, Albuquerque
Moret BME, Bader DA, Warnow T (2002) High-performance algorithm engineering for computational phylogenetics. J Supercomput 22:99–111, Special issue on the best papers from ICCS’01
Moret BME, Wyman S, Bader DA, Warnow T, Yan M (2001) A new implementation and detailed study of breakpoint analysis. In: Proceedings of the 6th Pacific symposium biocomputing (PSB 2001), Hawaii, Jan 2001, pp 583–594
Saitou N, Nei M (1987) The neighbor-joining method: a new method for reconstruction of phylogenetic trees. Mol Biol Evol 4:406–425
Sankoff D, Blanchette M (1998) Multiple genome rearrangement and breakpoint phylogeny. J Comput Biol 5:555–570
Yan M (2004) High performance algorithms for phylogeny reconstruction with maximum parsimony. PhD thesis, Electrical and Computer Engineering Department, University of New Mexico, Albuquerque, Jan 2004
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Bader, D.A. (2016). Engineering Algorithms for Computational Biology. In: Kao, MY. (eds) Encyclopedia of Algorithms. Springer, New York, NY. https://doi.org/10.1007/978-1-4939-2864-4_124
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DOI: https://doi.org/10.1007/978-1-4939-2864-4_124
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