A guided tour to approximate string matching

Navarro, Gonzalo

doi:10.1145/375360.375365

Cited by 2,034 publications

(1,190 citation statements)

References 82 publications

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“…Alternatively, we can use another definition of distance: the minimum number of operations, i.e., substitutions, insertions, and deletions, we must use in order to convert one sequence into another. This distance, which may always be used regardless of any length difference between the sequences, is also referred to as the edit distance [31,32].…”

Section: Clustering Of Related Sequencesmentioning

confidence: 99%

Computational analysis of fitness landscapes and evolutionary networks from in vitro evolution experiments

Xulvi-Brunet

Campbell

Rajamani

et al. 2016

Methods

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In vitro selection experiments in biochemistry allow for the discovery of novel molecules capable of specific desired biochemical functions. However, this is not the only benefit we can obtain from such selection experiments. Since selection from a random library yields an unprecedented, and sometimes comprehensive, view of how a particular biochemical function is distributed across sequence space, selection experiments also provide data for creating and analyzing molecular fitness landscapes, which directly map function (phenotypes) to sequence information (genotypes). Given the importance of understanding the relationship between sequence and functional activity, reliable methods to build and analyze fitness landscapes are needed. Here, we present some statistical methods to extract this information from pools of RNA molecules. We also provide new computational tools to construct and study molecular fitness landscapes.

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Section: Clustering Of Related Sequencesmentioning

confidence: 99%

Computational analysis of fitness landscapes and evolutionary networks from in vitro evolution experiments

Xulvi-Brunet

Campbell

Rajamani

et al. 2016

Methods

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“…In this paper, we learn an alphabet to represent human body parts and build a dictionary to characterize human poses. Furthermore, string matching [30], a technique widely used in text recognition and retrieval, is employed to verify hypotheses in human detection.…”

Section: Related Workmentioning

confidence: 99%

“…The benefit of representing human poses by sequences is that comparison and matching of human poses can be transformed into string matching [30], which has been proven to be both robust and efficient in text recognition. For human detection, hypothesis verification can be accomplished by matching the hypotheses with a set of reference poses.…”

Section: Introductionmentioning

confidence: 99%

Human Detection Using Learned Part Alphabet and Pose Dictionary

Yao

Bai

Liu

et al. 2014

Computer Vision – ECCV 2014

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Abstract. As structured data, human body and text are similar in many aspects. In this paper, we make use of the analogy between human body and text to build a compositional model for human detection in natural scenes. Basic concepts and mature techniques in text recognition are introduced into this model. A discriminative alphabet, each grapheme of which is a mid-level element representing a body part, is automatically learned from bounding box labels. Based on this alphabet, the flexible structure of human body is expressed by means of symbolic sequences, which correspond to various human poses and allow for robust, efficient matching. A pose dictionary is constructed from training examples, which is used to verify hypotheses at runtime. Experiments on standard benchmarks demonstrate that the proposed algorithm achieves state-of-the-art or competitive performance.

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“…As such it has been heavily researched and many such algorithms have been presented, surveyed in [11].…”

Section: Computing Edit Distancementioning

confidence: 99%

Faster Generation of Super Condensed Neighbourhoods Using Finite Automata

S.Russo

Oliveira

2005

String Processing and Information Retrieval

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Abstract. We present a new algorithm for generating super condensed neighbourhoods. Super condensed neighbourhoods have recently been presented as the minimal set of words that represent a pattern neighbourhood. These sets play an important role in the generation phase of hybrid algorithms for indexed approximate string matching. An existing algorithm for this purpose is based on a dynamic programming approach, implemented using bit-parallelism. In this work we present a bit-parallel algorithm based on automata which is faster, conceptually much simpler and uses less memory than the existing method.

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A guided tour to approximate string matching

Cited by 2,034 publications

References 82 publications

Computational analysis of fitness landscapes and evolutionary networks from in vitro evolution experiments

Computational analysis of fitness landscapes and evolutionary networks from in vitro evolution experiments

Human Detection Using Learned Part Alphabet and Pose Dictionary

Faster Generation of Super Condensed Neighbourhoods Using Finite Automata

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