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One of the major subjects of study in computational biology is finding the similarity between DNA sequences. Several techniques exist that are either based on alignment between sequences or are alignment-free. This paper demonstrates two techniques that are alignment-free. The first one is based on a graphical representation of the difference between DNA sequences, while the other one is based on...
Understanding the structure and function of DNA sequences represents an important area of research in modern biology. Unfortunately, analysis of such data is often complicated by the presence of mutations introduced by evolutionary processes. At the lowest scale, these usually occur in biological sequences as character substitutions, insertions or deletions (indel). They increase the time-complexity...
Phylogenic analysis relies on alignment of related sequences from different species to obtain the distances between these species. The quality of the alignment and the distance measure would depend on the alignment parameters that are used. In this work, we propose to use Relative Complexity Measure (RCM) to find the distances between the sequences which is not a parameter dependent measure. We used...
A new class of message-passing algorithms for motif finding is presented. Motif finding is the problem of identifying a collection of common subsequences within a given set of DNA sequences. It can be cast as an integer linear program (ILP). Message-passing techniques are a computationally efficient alternative to the often infeasible combinatorial solutions to the ILP. We introduce a new graphical...
We consider the problem of identifying motifs, recurring or conserved patterns, in the sets of biological sequences. To solve this task, we present new deterministic and exact algorithms for finding patterns that are embedded as exact or inexact instances in all or most of the input strings. The proposed algorithms (1) improve search efficiency compared to existing exact algorithms by focusing search...
Exact pairwise sequence alignment algorithms using dynamic programming require quadratic space and time, and this makes these algorithms impractical for large-scale sequences. In this paper, we propose and evaluate a new Anti-Diagonal based Parallel Linear-Space Algorithm (AD-PLSA). It records similarity matrix scores and start points on special anti-diagonals instead of special rows or columns. This...
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