A Highly Scalable Algorithm for the Extraction of Cis-Regulatory Regions

Abstract

In this paper we propose a new algorithm for identifying cis-regulatory modules in genomic sequences. In particular, the algorithm extracts structured motifs, defined as a collection of highly conserved regions with pre-specified sizes and spacings between them. This type of motifs is extremely relevant in the research of gene regulatory mechanisms since it can effectively represent promoter models. The proposed algorithm uses a new data structure, called box-link, to store the information about conserved regions that occur in a well-ordered and regularly spaced manner in the dataset sequences. The complexity analysis shows a time and space gain over previous algorithms that is exponential on the spacings between binding sites. Experimental results show that the algorithm is much faster than existing ones, sometimes by more than two orders of magnitude. The application of the method to biological datasets shows its ability to extract relevant consensi.

Lossless Filter for Finding Long Multiple Approximate Repetitions Using a New Data Structure, the Bi-factor Array

“…We now show some tests that prove this claim. For testing the ability of NIMBUS concerning the inference of long approximate repetitions, we ran an algorithm for extracting structured motifs called RISO [5] on a set of 6 sequences of total length 21 kB for finding motifs of length 40 occurring in every sequence with at most 3 substitutions pairwise. Using RISO, this test took 230 seconds.…”

An efficient multicore implementation of planted motif problem

“…A number of these algorithms find the approximate motif [1], [3], [4] and others find the exact motif [5], [6], [7], [8], [9], [10], [11], [12], [13], [14]. In this paper, we focus on the exact motif finding problem.…”

An Efficient Algorithm for the Identification of Structured Motifs in DNA Promoter Sequences

“…In Section 3 we present the main contribution of this paper, the box-link data structure and the new algorithm to extract structured motifs [5]. A complete complexity analysis of the algorithms for the extraction of structured motifs is presented in Appendix, which can be skipped in a first reading.…”