Califano,A. and Rigoutsos,I. (1993) FLASH: A fast look-up algorithm for string homology. InISMB, Bethesda, MD, pp.56--64.  Home/Search   Document Not in Database   Summary   Related Articles   Check

....one given by Lemma 1. Indeed, even de ning the threshold precisely is far from trivial. The de nition we give here not only solves the problem for the one gapped q gram lters but provides a framework for solving it for other even more complicated lters. Gapped q grams have also been used in [3, 12, 9]. In [3, 12] the motivation is to increase the ltration eciency by considering multiple shapes. Pevzner and Waterman [12] use q grams containing every (k 1)st character together with contiguous q grams for the Hamming distance. Califano and Rigoutsos [3] describe a lossy lter for the ....

....Lemma 1. Indeed, even de ning the threshold precisely is far from trivial. The de nition we give here not only solves the problem for the one gapped q gram lters but provides a framework for solving it for other even more complicated lters. Gapped q grams have also been used in [3, 12, 9] In [3, 12], the motivation is to increase the ltration eciency by considering multiple shapes. Pevzner and Waterman [12] use q grams containing every (k 1)st character together with contiguous q grams for the Hamming distance. Califano and Rigoutsos [3] describe a lossy lter for the Levenshtein distance ....

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A. Califano and I. Rigoutsos. FLASH: A fast look-up algorithm for string homology. In Proc. 1st International Conference on Intelligent Systems for Molecular Biology, pages 56-64. AAAI Press, 1993.

....Indexed q gram filters are described in [9, 10, 15, 17, 19, 26] A generalization of the q gram filter uses gapped q grams, subsets of q characters of a fixed noncontiguous shape. For example, the 3 grams of shape ## # in the string ACAGCT are ACG, CAC and AGT. Gapped q grams have been used in [7, 20, 13]. In [7, 20] the motivation is to increase the filtration efficiency by considering multiple shapes. Pevzner and Waterman [20] use q grams containing every (k 1)st character together with ordinary contiguous q grams for the Hamming distance. Califano and Rigoutsos [7] describe a lossy filter ....

....filters are described in [9, 10, 15, 17, 19, 26] A generalization of the q gram filter uses gapped q grams, subsets of q characters of a fixed noncontiguous shape. For example, the 3 grams of shape ## # in the string ACAGCT are ACG, CAC and AGT. Gapped q grams have been used in [7, 20, 13] In [7, 20], the motivation is to increase the filtration efficiency by considering multiple shapes. Pevzner and Waterman [20] use q grams containing every (k 1)st character together with ordinary contiguous q grams for the Hamming distance. Califano and Rigoutsos [7] describe a lossy filter that uses as ....

[Article contains additional citation context not shown here]

Califano, A., Rigoutsos, I.: FLASH: A Fast Look-Up Algorithm for String Homology, Proceedings of the First International Conference on Intelligent Systems for Molecular Biology, AAAI Press, 1993.

.... index size at the cost of ltration eciency is to consider only a sample, say every 5th, of the q grams of the text or the pattern [8, 24, 14, 22, 23, 21, 17, 19] Multiple shapes As an opposite to sampling, the number of q grams can be increased by using gapped q grams of several di erent shapes [7, 20]. This improves ltration eciency but increases time and or space requirements. Approximate q grams Another way to improve ltration eciency at the cost of slower ltering is to allow errors in q grams [14, 8, 22, 19] Of course, various combinations of these methods are possible. For example, ....

....programming algorithm. Pevzner and Waterman [20] too, consider only the Hamming distance and give an equation for a very limited class of regular shapes, and even that is not the optimal value but a lower bound (which guarantees losslessness but at a reduced eciency) Califano and Rigoutsos [7] use a heuristically chosen threshold supported by probabilistic calculations and experiments; their lter is lossy. In this paper, we consider the problem of computing the threshold. We give a formal de nition of the value of the threshold that captures the essence of the concept and describe ....

A. Califano and I. Rigoutsos. FLASH: A fast look-up algorithm for string homology. In Proc. 1st International Conference on Intelligent Systems for Molecular Biology, pages 56-64. AAAI Press, 1993.

....one given by Lemma 1. Indeed, even de ning the threshold precisely is far from trivial. The de nition we give here not only solves the problem for the onegapped q gram lters but provides a framework for solving it for other even more complicated lters. Gapped q grams have also been used in [4, 13, 10]. In [4, 13] the motivation is to increase the ltration eciency by considering multiple shapes. Pevzner and Waterman [13] use q grams containing every (k 1)st character together with contiguous q grams for the Hamming distance. Califano and Rigoutsos [4] describe a lossy lter for the ....

....1. Indeed, even de ning the threshold precisely is far from trivial. The de nition we give here not only solves the problem for the onegapped q gram lters but provides a framework for solving it for other even more complicated lters. Gapped q grams have also been used in [4, 13, 10] In [4, 13], the motivation is to increase the ltration eciency by considering multiple shapes. Pevzner and Waterman [13] use q grams containing every (k 1)st character together with contiguous q grams for the Hamming distance. Califano and Rigoutsos [4] describe a lossy lter for the Levenshtein distance ....

[Article contains additional citation context not shown here]

A. Califano and I. Rigoutsos. FLASH: A fast look-up algorithm for string homology. In Proc. 1st International Conference on Intelligent Systems for Molecular Biology, pages 56-64. AAAI Press, 1993.

....best trade o depends on the implementation and the application. A generalization of the q gram method uses gapped q grams, subsets of q characters of a xed non contiguous shape. For example, the 3 grams of shape ## # in the string ACAGCT are AC.G, CA.C and AG.T. Gapped q grams have been used in [3, 11, 8]. In [3, 11] the motivation is to increase the ltration eciency by considering multiple shapes. Pevzner and Waterman [11] use q grams containing every (k 1)st character together with contiguous q grams for the k mismatches problem. The FLASH algorithm of Califano and Rigoutsos [3] uses as many ....

....on the implementation and the application. A generalization of the q gram method uses gapped q grams, subsets of q characters of a xed non contiguous shape. For example, the 3 grams of shape ## # in the string ACAGCT are AC.G, CA.C and AG.T. Gapped q grams have been used in [3, 11, 8] In [3, 11], the motivation is to increase the ltration eciency by considering multiple shapes. Pevzner and Waterman [11] use q grams containing every (k 1)st character together with contiguous q grams for the k mismatches problem. The FLASH algorithm of Califano and Rigoutsos [3] uses as many as 40 ....

[Article contains additional citation context not shown here]

A. Califano and I. Rigoutsos. FLASH: A fast look-up algorithm for string homology. In L. Hunter, D. Searls, and J. Shavlik, editors, Proceedings of the First International Conference on Intelligent Systems for Molecular Biology, pages 56{ 64, Bethesda, MD, 1993. AAAI Press.

....longer in length than the indexed interval length. The indexed approach of ramdb is shown to result in a 0 to 800 fold speedup in search times over comparable exhaustive approximate pattern matching approaches. The flash search tool redundantly indexes genomic data based on a probabilistic scheme [12]. For each interval of length n,theflash search structure stores, in a hash table, all possible similarly ordered contiguous and non contiguous subsequences of length m that begin with the first base in the interval, where m n. As an example, for a nucleotide sequence acctgatt the index terms for ....

A. Califano and I. Rigoutsos. FLASH: A fast look-up algorithm for string homology. In International Conference on Intelligent Systems for Molecular Biology, pages 56-- 64, Bethesda, MD, 1993.

....Sun OS 4.1 and Solaris on Sparc stations, and OS 2 2.1 on IBM PCs, with communication over TCP and OSF DCE and interoperability with SUN RPC. Some serious applications have been built with Concert C. One application searches a database of genetic information on 64 Risc System 6000s in parallel [12]. Another uses similar search techniques to perform complex visual pattern recognition [28] Concert C has been used to connect a natural language textual query program to a collection of large, geographically dispersed text repositories [23] Another project uses Concert C to enable the ....

A. Califano and I. Rigoutsos. FLASH: A Fast LookUp Algorithm for String Homology. In Proceedings First International Conference on Intelligent Systems for Molecular Biology, Washington, DC, July 1993.

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Califano,A. and Rigoutsos,I. (1993) FLASH: A fast look-up algorithm for string homology. InISMB, Bethesda, MD, pp.56--64.

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A. Califano and I. Rigoutsos. FLASH: A fast look-up algorithm for string homology. In L. Hunter, D. Searls, and J. Shavlik, editors, Proceedings of the 1st International Conference on Intelligent Systems for Molecular Biology, pages 56--64, Menlo Park, CA, USA, July 1993. AAAI Press.

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CALIFANO, A., AND RIGOUTSOS, I. Flash: A fast look-up algorithm for string homology. In Proceedings of the 1st International Conference on Intelligent Systems for Molecular Biology (July 1993), pp. 56--64.

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A. Califano and I. Rigoutsos. Flash: A fast look-up algorithm for string homology. In Proceedings of the 1st International Conference on Intelligent Systems for Molecular Biology, pages 56--64, July 1993.

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A. Califano and I. Rigoutsos. Flash: A fast look-up algorithm for string homology. In Proceedings of the 1st International Conference on Intelligent Systems for Molecular Biology, pages 5664, July 1993.

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Califano, A., Rigoutsos, I.: Flash: A fast look-up algorithm for string homology. In: Proceedings of the 1st International Conference on Intelligent Systems for Molecular Biology. (1993) 56--64

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Califano,A. and Rigoutsos,I. (1993) Flash: a fast look-up algorithm for string homology. Proc. Int. Conf. Intell. Syst. Mol. Biol., 1, 56--64.

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Califano, A. and Rigoutsos, I., FLASH: fast look-up algorithm for string homology, Technical Report, IBM T.J. Watson Research Center, 1995.

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A. Califano and I. Rigoutsos. FLASH: a fast look-up algorithm for string homology. In Proc. of IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pp. 353--359, 1993.

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Califano, A., Rigoutsos, I.: Flash: A fast look-up algorithm for string homology. In: Proceedings of the 1st International Conference on Intelligent Systems for Molecular Biology. (1993) 56--64

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Califano, A. and Rigoutsos, I., FLASH: fast look-up algorithm for string homology, Tech. Rep., IBM T.J. Watson Research Center, 1995.

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A. Califano and I. Rigoutsos, \FLASH: fast look-up algorithm for string homology", Tech. Rep., IBM T.J. Watson Research Center (1995).

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A. Califano, I. Rigoutsos, FLASH: fast look-up algorithm for string homology. Tech. Rep., IBM T.J. Watson Research Center, 1995.

No context found.

CALIFANO, A., AND RIGOUTSOS, I. Flash: A fast look-up algorithm for string homology. In Proceedings of the 1st International Conference on Intelligent Systems for Molecular Biology (July 1993), pp. 56--64.

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Califano A., Rigoutsos I., FLASH: A Fast Look-up Algorithm for String Homology, Hunter L., Searls D., Shavlik J. eds., Proc. First International Conference on Intelligent Systems for Molecular Biology, AAAI Press, 1993, 145--153.

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A. Califano and I. Rigoutsos. FLASH: Fast look-up algorithm for string homology. In CVPR, 1993.

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A. Califano and I. Rigoutsos. FLASH: Fast look-up algorithm for string homology. In CVPR, 1993.

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Califano, A., and Rigoutsos, I. 1993. FLASH: A fast look-up algorithm for string homology. Proceedings of the 1st International Conference on Intelligent Systems for Molecular Biology, 56--64.

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