REMA

A computer-based mapping tool for analysis of restriction sites in multiple DNA sequences

Jan Szubert, Caroline Reiff, Andrew Thorburn, Brajesh Singh

Research output: Contribution to journalArticle

13 Citations (Scopus)

Abstract

REMA is an interactive web-based program which predicts endonuclease cut sites in DNA sequences. It analyses multiple sequences simultaneously and predicts the number and size of fragments as well as provides restriction maps. The users can select single or paired combinations of all commercially available enzymes. Additionally, REMA permits prediction of multiple sequence terminal fragment sizes and suggests suitable restriction enzymes for maximally discriminatory results. REMA is an easy to use, web based program which will have a wide application in molecular biology research. Availability: REMA is written in Perl and is freely available for non-commercial use. Detailed information on installation can be obtained from Jan Szubert (jan.szubert@gmail.com) and the web based application is accessible on the internet at the URL http://www.macaulay.ac.uk/rema Contact: b.singh@macaulay.ac.uk.
Original languageEnglish
Pages (from-to)411-413
Number of pages3
JournalJournal of Microbiological Methods
Volume69
Issue number2
Early online date24 Jan 2007
DOIs
Publication statusPublished - May 2007

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Endonucleases
Enzymes
Internet
Sequence Analysis
Molecular Biology
Research

Keywords

  • DNA restriction enzymes
  • DNA, bacterial
  • restriction mapping
  • software
  • Restiction enzyme
  • Terminal restriction fragements
  • Multiple sequences

Cite this

REMA : A computer-based mapping tool for analysis of restriction sites in multiple DNA sequences. / Szubert, Jan; Reiff, Caroline; Thorburn, Andrew; Singh, Brajesh.

In: Journal of Microbiological Methods, Vol. 69, No. 2, 05.2007, p. 411-413.

Research output: Contribution to journalArticle

Szubert, Jan ; Reiff, Caroline ; Thorburn, Andrew ; Singh, Brajesh. / REMA : A computer-based mapping tool for analysis of restriction sites in multiple DNA sequences. In: Journal of Microbiological Methods. 2007 ; Vol. 69, No. 2. pp. 411-413.
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