DNAMAT: An efficient graphic matrix sequence homology algorithm and its application to structural analysis

Ron Unger, David Harel, Joel L. Sussman

Research output: Contribution to journalArticlepeer-review

6 Scopus citations

Abstract

We present a fast algorithm to produce a graphic matrix representation of sequence homology. The algorithm is based on lexicographical ordering of fragments. It preserves most of the options of a simple naive algorithm with a significant increase in speed. This algorithm was the basis for a program, called DNAMAT, that has been extensively tested during the last three years at the Weizmann Institute of Science and has proven to be very useful. In addition we suggest a way to extend our approach to analyse a series of related DNA or RNA sequences, in order to determine certain common structural features. The analysis is done by 'summing' a set of dot-matrices to produce an overall matrix that displays structural elements common to most of the sequences. We give an example of this procedure by analysing tRNA sequences.

Original languageEnglish
Pages (from-to)283-289
Number of pages7
JournalBioinformatics
Volume2
Issue number4
DOIs
StatePublished - Dec 1986
Externally publishedYes

Bibliographical note

Funding Information:
This work was supported in part by grants from the Gutwirth Foundation and from the Joseph and Ceil Mazer Center for Structural Biology

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