Parametric optimization of sequence alignment

Gusfield, Dan; Balasubramanian, K.; Naor, Dalit

doi:10.1007/bf01185430

Cited by 85 publications

(73 citation statements)

References 12 publications

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“…Parametric edit distances try to put these issues into consideration in determining the suitable cost functions for each edit operation and in the choice of thresholds. For the case of traditional string edit distance, some methods have been proposed for the basic edit operations-insertion, deletion, and substitution [5,17]. Parametric video edit distance operations can borrow ideas from these proposals for their realization, with special attention to the new edit operations.…”

Section: Discussionmentioning

confidence: 99%

A Distance Measure for Video Sequences

Adjeroh¹,

Lee²,

King³

1999

Computer Vision and Image Understanding

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Video is a unique multimedia data type, in that it comes with distinguished spatio-temporal constraints. Content-based video retrieval thus requires methods for video sequence-to-sequence matching, incorporating the temporal ordering inherent in a video sequence, without losing sight of the visual nature of the information in the sequence. Such methods will require reliable measures of similarity between the video sequences. In this paper, we formulate the problem of video sequence-to-sequence matching as a patternmatching problem and propose the vstring edit distance as a suitable distance measure for video sequences.

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Section: Discussionmentioning

confidence: 99%

A Distance Measure for Video Sequences

Adjeroh¹,

Lee²,

King³

1999

Computer Vision and Image Understanding

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“…Another direction for generalization is in the functions defining the matroid element weights as functions of the parameter t. Work of Gusfield et al on parametric sequence alignment [20] can be interpreted as a shortest path problem with weights depending linearly on two parameters, and, similarly to the situation in two dimensions, multi-parameter uniform matroid optimization problems are essentially equivalent to levels in higher dimensional arrangements [1,2,8,11]. Tamaki and Tokuyama [34] have also investigated parametric matroid problems with quadratic element weight functions, but much more work remains to be done in this direction.…”

Section: Discussionmentioning

confidence: 99%

Geometric lower bounds for parametric matroid optimization

Eppstein

1995

Proceedings of the Twenty-Seventh Annual ACM Symposium on Theory of Computing - STOC '95

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We relate the sequence of minimum bases of a matroid with linearly varying weights to three problems from combinatorial geometry: k-sets, lower envelopes of line segments, and convex polygons in line arrangements. Using these relations we show new lower bounds on the number of base changes in such sequences: (nr 1/3 ) for a general n-element matroid with rank r , and (mα(n)) for the special case of parametric graph minimum spanning trees. The only previous lower bound was (n log r ) for uniform matroids; upper bounds of O(mn 1/2 ) for arbitrary matroids and O(mn 1/2 / log * n) for uniform matroids were also known.

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“…A single, "optimal" answer is often unsatisfactory. Considerable work has been devoted to this problem, producing algorithms providing near-optimal [25,27] and parametric [18] solutions. -Duplicate solutions: While there is a general technique to enumerate all solutions to a DP problem (possibly up to some threshold value) [32,33], such enumeration is hampered by the fact that the algorithm may produce the same solution several times -and in fact, this may lead to combinatorial explosion of redundancy.…”

Section: Ambiguity Issues In Dynamic Programmingmentioning

confidence: 99%

Matching and Significance Evaluation of Combined Sequence-Structure Motifs in RNA

Meyer¹,

Giegerich²

2002

Zeitschrift Für Physikalische Chemie

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Abstract. The discipline of Algebraic Dynamic Programming is a powerful method to design and implement versatile pattern matching algorithms on sequences; here we consider mixed sequence and secondary structure motifs in RNA. A recurring challenge when designing new pattern matchers is to provide a statistical analysis of pattern significance. We demonstrate that by the use of so-called canonical pattern descriptions, the expected number of hits on a sequence of length n can be computed a priori, using the pattern matcher itself. This provides a systematic way to calibrate the specificity of pattern matching algorithms. The technique is exemplified by examples using IRE and SECIS elements. Motivation and Overview Evaluation of Pattern SignificanceSignificance of standard patterns. A mathematical evaluation of the significance of hits is essential in all pattern matching applications. For simple sequence patterns, the approach of [2], implemented in the tool Verbumculus, provides a complete analysis of over-and underrepresented words in a sequence. The E-values computed by the BLAST programs [1] for sequence similarity search give an account of how small the probability is to find a given match by chance. Similarly, the REPuter tool [24] provides significance scores in the analysis of approximate repeats and palindromes in genome data.Significance analysis of general patterns. Sequence subwords, local similarity and repeats are rather elementary patterns. In searching for, say, regulatory elements in RNA, we need all of the above, and more: We design patterns that adhere to a structural shape, may carry some well defined sequence motifs, but else allow considerable variation in both sequence and structure. When designing such a motif description, a central problem is to balance specificity against variation, or in statistical terms: to analyse E m (n, c), the expected number of hits of the motif m on a random sequence of length n and base composition c.Note that E m (n, c) is a property of the motif, in contrast to a BLAST E-value that rates a particular motif instance. Although an analysis of

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Parametric optimization of sequence alignment

Cited by 85 publications

References 12 publications

A Distance Measure for Video Sequences

A Distance Measure for Video Sequences

Geometric lower bounds for parametric matroid optimization

Matching and Significance Evaluation of Combined Sequence-Structure Motifs in RNA

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