Integrating alignment-based and alignment-free sequence similarity measures for biological sequence classification.

ABSTRACT:

Motivation

Alignment-based sequence similarity searches, while accurate for some type of sequences, can produce incorrect results when used on more divergent but functionally related sequences that have undergone the sequence rearrangements observed in many bacterial and viral genomes. Here, we propose a classification model that exploits the complementary nature of alignment-based and alignment-free similarity measures with the aim to improve the accuracy with which DNA and protein sequences are characterized.

Results

Our model classifies sequences using a combined sequence similarity score calculated by adaptively weighting the contribution of different sequence similarity measures. Weights are determined independently for each sequence in the test set and reflect the disc

SUBMITTER: Borozan I 

PROVIDER: S-EPMC4410667 | biostudies-literature | 2015 May

REPOSITORIES: biostudies-literature