Unknown

Dataset Information

0

Mapping sequences by parts.


ABSTRACT: BACKGROUND:We present the N-map method, a pairwise and asymmetrical approach which allows us to compare sequences by taking into account evolutionary events that produce shuffled, reversed or repeated elements. Basically, the optimal N-map of a sequence s over a sequence t is the best way of partitioning the first sequence into N parts and placing them, possibly complementary reversed, over the second sequence in order to maximize the sum of their gapless alignment scores. RESULTS:We introduce an algorithm computing an optimal N-map with time complexity O (|s| x |t| x N) using O (|s| x |t| x N) memory space. Among all the numbers of parts taken in a reasonable range, we select the value N for which the optimal N-map has the most significant score. To evaluate this significance, we study the empirical distributions of the scores of optimal N-maps and show that they can be approximated by normal distributions with a reasonable accuracy. We test the functionality of the approach over random sequences on which we apply artificial evolutionary events. PRACTICAL APPLICATION:The method is illustrated with four case studies of pairs of sequences involving non-standard evolutionary events.

SUBMITTER: Didier G 

PROVIDER: S-EPMC2148040 | biostudies-literature | 2007 Sep

REPOSITORIES: biostudies-literature

altmetric image

Publications

Mapping sequences by parts.

Didier Gilles G   Guziolowski Carito C  

Algorithms for molecular biology : AMB 20070919


<h4>Background</h4>We present the N-map method, a pairwise and asymmetrical approach which allows us to compare sequences by taking into account evolutionary events that produce shuffled, reversed or repeated elements. Basically, the optimal N-map of a sequence s over a sequence t is the best way of partitioning the first sequence into N parts and placing them, possibly complementary reversed, over the second sequence in order to maximize the sum of their gapless alignment scores.<h4>Results</h4  ...[more]

Similar Datasets

| S-EPMC1456965 | biostudies-literature
| S-EPMC5426715 | biostudies-literature
| S-EPMC10120640 | biostudies-literature
| S-EPMC3634013 | biostudies-literature
| S-EPMC3130275 | biostudies-literature
| S-EPMC4707848 | biostudies-literature
| S-EPMC5737678 | biostudies-literature
| S-EPMC10510034 | biostudies-literature
| S-EPMC6632085 | biostudies-literature
| S-EPMC4322921 | biostudies-literature