Treffer: Transformation distances : a family of dissimilarity measures based on movements of segments

Title:
Transformation distances : a family of dissimilarity measures based on movements of segments
Source:
Selection of papers presented at the German Conference on Bioinformatics (GCB'98, Cologne, Germany, October 1998Bioinformatics (Oxford. Print). 15(3):195-202
Publisher Information:
Oxford: Oxford University Press, 1999.
Publication Year:
1999
Physical Description:
print, 28 ref
Original Material:
INIST-CNRS
Document Type:
Konferenz Conference Paper
File Description:
text
Language:
English
Author Affiliations:
Laboratoire d'Informatique Fondamentale de Lille (LIFL), UFR IEEA - Bât M3, 59655 Villeneuve d'Ascq, France
Theoretische Bioinformatik Deutsches Krebsforschungzentrum (DKFZ), Im Neuenheimer Feld 280, Heidelberg 69120, Germany
ISSN:
1367-4803
Rights:
Copyright 1999 INIST-CNRS
CC BY 4.0
Sauf mention contraire ci-dessus, le contenu de cette notice bibliographique peut être utilisé dans le cadre d’une licence CC BY 4.0 Inist-CNRS / Unless otherwise stated above, the content of this bibliographic record may be used under a CC BY 4.0 licence by Inist-CNRS / A menos que se haya señalado antes, el contenido de este registro bibliográfico puede ser utilizado al amparo de una licencia CC BY 4.0 Inist-CNRS
Notes:
Biological sciences. Generalities. Modelling. Methods

Generalities in biological sciences
Accession Number:
edscal.1831435
Database:
PASCAL Archive

Weitere Informationen

Motivation: Evolution acts in several ways on DNA: either by mutating a base, or by inserting, deleting or copying a segment of the sequence (Ruddle, 1997; Russell, 1994; Li and Grauer, 1991). Classical alignment methods deal with point mutations (Waterman, 1995), genome-level mutations are studied using genome rearrangement distances (Bafna and Pevzner, 1993, 1995; Kececioglu and Sankoff, 1994; Kececioglu and Ravi, 1995). The latter distances generally operate, not on the sequences, but on an ordered list ofgenes. To our knowledge, no measure of distance attempts to compare sequences using a general set of segment-based operations. Results: Here we define a new family of distances, called transformation distances, which quantify the dissimilarity between two sequences in terms of segment-based events. We focus on the case where segment-copy, -reverse-copy and -insertion are allowed in our set of operations. Those events are weighted by their description length, but other sets of weights are possible when biological information is available. The transformation distance from sequence S to sequence T is then the Minimum Description Length among all possible scripts that build T knowing S with segment-based operations. The underlying idea is related to Kolmogorov complexity theory. We present an algorithm which, given two sequences S and T, computes exactly and efficiently the transformation distance from S to T. Unlike alignment methods, the method we propose does not necessarily respect the order of the residues within the compared sequences and is thereford able to account for duplications and translocations that cannot be properly described by sequence alignment. A biological application on Tntl tobacco retrotransposon is presented.