# A multiple divide-and-conquer (MDC) algorithm for optimal alignments in linear space

## Abstract

Dynamic programming algorithms are often used to find the similarities of sequences as well as to deliver the actual alignment of two sequences. Two kinds of alignments are used to compare sequences: local alignments and global alignments. The local alignments attempt to locate conserved regions, while the global alignments identify overall relationship between two sequences. While dynamic programming algorithms are relatively time consuming, the space required is often the limiting factor when aligning long sequences. A linear space algorithm for computing maximal common subsequences, proposed by Hirschberg, was applied by Myers and Miller to deliver optimal alignments in linear space. The authors have improved the Myers and Miller algorithm by introducing a multiple divide and conquer technique that reduces the algorithm`s running time while maintaining its linear space property. Efficient sequence alignment algorithms have been an active topic in computational biology.

- Authors:

- Publication Date:

- Research Org.:
- Oak Ridge National Lab., TN (United States)

- Sponsoring Org.:
- USDOE, Washington, DC (United States)

- OSTI Identifier:
- 10168027

- Report Number(s):
- ORNL/TM-12764

ON: DE94015457; TRN: AHC29417%%30

- DOE Contract Number:
- AC05-84OR21400

- Resource Type:
- Technical Report

- Resource Relation:
- Other Information: PBD: Jun 1994

- Country of Publication:
- United States

- Language:
- English

- Subject:
- 99 GENERAL AND MISCELLANEOUS//MATHEMATICS, COMPUTING, AND INFORMATION SCIENCE; MATHEMATICAL SPACE; ALIGNMENT; DYNAMIC PROGRAMMING; ALGORITHMS; COMPARATIVE EVALUATIONS; OPTIMIZATION; MATRICES; USES; BIOLOGY; PERFORMANCE; 990200; MATHEMATICS AND COMPUTERS

### Citation Formats

```
Guan, X, and Uberbacher, E C.
```*A multiple divide-and-conquer (MDC) algorithm for optimal alignments in linear space*. United States: N. p., 1994.
Web. doi:10.2172/10168027.

```
Guan, X, & Uberbacher, E C.
```*A multiple divide-and-conquer (MDC) algorithm for optimal alignments in linear space*. United States. doi:10.2172/10168027.

```
Guan, X, and Uberbacher, E C. Wed .
"A multiple divide-and-conquer (MDC) algorithm for optimal alignments in linear space". United States. doi:10.2172/10168027. https://www.osti.gov/servlets/purl/10168027.
```

```
@article{osti_10168027,
```

title = {A multiple divide-and-conquer (MDC) algorithm for optimal alignments in linear space},

author = {Guan, X and Uberbacher, E C},

abstractNote = {Dynamic programming algorithms are often used to find the similarities of sequences as well as to deliver the actual alignment of two sequences. Two kinds of alignments are used to compare sequences: local alignments and global alignments. The local alignments attempt to locate conserved regions, while the global alignments identify overall relationship between two sequences. While dynamic programming algorithms are relatively time consuming, the space required is often the limiting factor when aligning long sequences. A linear space algorithm for computing maximal common subsequences, proposed by Hirschberg, was applied by Myers and Miller to deliver optimal alignments in linear space. The authors have improved the Myers and Miller algorithm by introducing a multiple divide and conquer technique that reduces the algorithm`s running time while maintaining its linear space property. Efficient sequence alignment algorithms have been an active topic in computational biology.},

doi = {10.2172/10168027},

journal = {},

number = ,

volume = ,

place = {United States},

year = {1994},

month = {6}

}