Fast profile matching algorithms — A survey

AbstractPosition-specific scoring matrices are a popular choice for modelling signals or motifs in biological sequences, both in DNA and protein contexts. A lot of effort has been dedicated to the definition of suitable scores and thresholds for increasing the specificity of the model and the sensitivity of the search. It is quite surprising that, until very recently, little attention has been paid to the actual process of finding the matches of the matrices in a set of sequences, once the score and the threshold have been fixed. In fact, most profile matching tools still rely on a simple sliding window approach to scan the input sequences. This can be a very time expensive routine when searching for hits of a large set of scoring matrices in a sequence database. In this paper we will give a survey of proposed approaches to speed up profile matching based on statistical significance, multipattern matching, filtering, indexing data structures, matrix partitioning, Fast Fourier Transform and data compression. These approaches improve the expected searching time of profile matching, thus leading to implementation of faster tools in practice