### Abstract

Ordered, labeled trees are trees in which each node has a label and the left-to-right order of its children (if it has any) is fixed. Such trees have many applications in vision, pattern recognition, molecular biology and natural language processing. We consider a substructure of an ordered labeled tree Tto be a connected subgraph of T. Given two ordered labeled trees 7 and T2 and an integer d, the largest approximately common substructure problem is to find a substructure U1 of 7 and a substructure U2 of T2 such that U1 is within edit distance dof U2 and where there does not exist any other substructure l of 7 and V2 of T2 such that l and V2 satisfy the distance constraint and the sum of the sizes of V-, and V2 is greater than the sum of the sizes of U1 and U2. We present a dynamic programming algorithm to solve this problem, which runs as fast as the fastest known algorithm for computing the edit distance of two trees when the distance allowed in the common substructures is a constant independent of the input trees. To demonstrate the utility of our algorithm, we discuss its application to discovering motifs in multiple RNA secondary structures (which are ordered labeled trees).

Original language | English (US) |
---|---|

Pages (from-to) | 889-895 |

Number of pages | 7 |

Journal | IEEE Transactions on Pattern Analysis and Machine Intelligence |

Volume | 20 |

Issue number | 8 |

DOIs | |

State | Published - 1998 |

### Fingerprint

### Keywords

- Computational biology
- Dynamic programming
- Pattern matching
- Pattern recognition
- Trees

### ASJC Scopus subject areas

- Control and Systems Engineering
- Electrical and Electronic Engineering
- Artificial Intelligence
- Computer Vision and Pattern Recognition

### Cite this

*IEEE Transactions on Pattern Analysis and Machine Intelligence*,

*20*(8), 889-895. https://doi.org/10.1109/34.709622

**An Algorithm for Finding the Largest Approximately Common Substructures of Two Trees.** / Wang, Jason T L; Shapiro, Bruce A.; Shasha, Dennis; Zhang, Kaizhong; Currey, Kathleen M.

Research output: Contribution to journal › Article

*IEEE Transactions on Pattern Analysis and Machine Intelligence*, vol. 20, no. 8, pp. 889-895. https://doi.org/10.1109/34.709622

}

TY - JOUR

T1 - An Algorithm for Finding the Largest Approximately Common Substructures of Two Trees

AU - Wang, Jason T L

AU - Shapiro, Bruce A.

AU - Shasha, Dennis

AU - Zhang, Kaizhong

AU - Currey, Kathleen M.

PY - 1998

Y1 - 1998

N2 - Ordered, labeled trees are trees in which each node has a label and the left-to-right order of its children (if it has any) is fixed. Such trees have many applications in vision, pattern recognition, molecular biology and natural language processing. We consider a substructure of an ordered labeled tree Tto be a connected subgraph of T. Given two ordered labeled trees 7 and T2 and an integer d, the largest approximately common substructure problem is to find a substructure U1 of 7 and a substructure U2 of T2 such that U1 is within edit distance dof U2 and where there does not exist any other substructure l of 7 and V2 of T2 such that l and V2 satisfy the distance constraint and the sum of the sizes of V-, and V2 is greater than the sum of the sizes of U1 and U2. We present a dynamic programming algorithm to solve this problem, which runs as fast as the fastest known algorithm for computing the edit distance of two trees when the distance allowed in the common substructures is a constant independent of the input trees. To demonstrate the utility of our algorithm, we discuss its application to discovering motifs in multiple RNA secondary structures (which are ordered labeled trees).

AB - Ordered, labeled trees are trees in which each node has a label and the left-to-right order of its children (if it has any) is fixed. Such trees have many applications in vision, pattern recognition, molecular biology and natural language processing. We consider a substructure of an ordered labeled tree Tto be a connected subgraph of T. Given two ordered labeled trees 7 and T2 and an integer d, the largest approximately common substructure problem is to find a substructure U1 of 7 and a substructure U2 of T2 such that U1 is within edit distance dof U2 and where there does not exist any other substructure l of 7 and V2 of T2 such that l and V2 satisfy the distance constraint and the sum of the sizes of V-, and V2 is greater than the sum of the sizes of U1 and U2. We present a dynamic programming algorithm to solve this problem, which runs as fast as the fastest known algorithm for computing the edit distance of two trees when the distance allowed in the common substructures is a constant independent of the input trees. To demonstrate the utility of our algorithm, we discuss its application to discovering motifs in multiple RNA secondary structures (which are ordered labeled trees).

KW - Computational biology

KW - Dynamic programming

KW - Pattern matching

KW - Pattern recognition

KW - Trees

UR - http://www.scopus.com/inward/record.url?scp=0032136849&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=0032136849&partnerID=8YFLogxK

U2 - 10.1109/34.709622

DO - 10.1109/34.709622

M3 - Article

AN - SCOPUS:0032136849

VL - 20

SP - 889

EP - 895

JO - IEEE Transactions on Pattern Analysis and Machine Intelligence

JF - IEEE Transactions on Pattern Analysis and Machine Intelligence

SN - 0162-8828

IS - 8

ER -