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A Practical and Scalable Tool to Find Overlaps between Sequences.

Rachid MH, Malluhi Q - Biomed Res Int (2015)

Bottom Line: The paper demonstrates an efficient construction of this time-efficient and space-economical tree data structure.Experimental evaluation indicates superior results in terms of space and time over existing solutions.Results also show that the proposed technique is highly scalable in a parallel execution environment.

View Article: PubMed Central - PubMed

Affiliation: KINDI Lab for Computing Research, Qatar University, P.O. Box 2713, Doha, Qatar.

ABSTRACT
The evolution of the next generation sequencing technology increases the demand for efficient solutions, in terms of space and time, for several bioinformatics problems. This paper presents a practical and easy-to-implement solution for one of these problems, namely, the all-pairs suffix-prefix problem, using a compact prefix tree. The paper demonstrates an efficient construction of this time-efficient and space-economical tree data structure. The paper presents techniques for parallel implementations of the proposed solution. Experimental evaluation indicates superior results in terms of space and time over existing solutions. Results also show that the proposed technique is highly scalable in a parallel execution environment.

No MeSH data available.


Constructing the tree after sorting the sequences.
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Related In: Results  -  Collection


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alg1: Constructing the tree after sorting the sequences.

Mentions: Figure 2 demonstrates the stages of constructing the tree. The character which is on the left side of a node is the label of the node. The interval above the node denotes its string interval. The number shown on the right side of the node denotes chain_len of the node. Algorithm 1 demonstrates the pseudocode for constructing the tree.


A Practical and Scalable Tool to Find Overlaps between Sequences.

Rachid MH, Malluhi Q - Biomed Res Int (2015)

Constructing the tree after sorting the sequences.
© Copyright Policy - open-access
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC4417569&req=5

alg1: Constructing the tree after sorting the sequences.
Mentions: Figure 2 demonstrates the stages of constructing the tree. The character which is on the left side of a node is the label of the node. The interval above the node denotes its string interval. The number shown on the right side of the node denotes chain_len of the node. Algorithm 1 demonstrates the pseudocode for constructing the tree.

Bottom Line: The paper demonstrates an efficient construction of this time-efficient and space-economical tree data structure.Experimental evaluation indicates superior results in terms of space and time over existing solutions.Results also show that the proposed technique is highly scalable in a parallel execution environment.

View Article: PubMed Central - PubMed

Affiliation: KINDI Lab for Computing Research, Qatar University, P.O. Box 2713, Doha, Qatar.

ABSTRACT
The evolution of the next generation sequencing technology increases the demand for efficient solutions, in terms of space and time, for several bioinformatics problems. This paper presents a practical and easy-to-implement solution for one of these problems, namely, the all-pairs suffix-prefix problem, using a compact prefix tree. The paper demonstrates an efficient construction of this time-efficient and space-economical tree data structure. The paper presents techniques for parallel implementations of the proposed solution. Experimental evaluation indicates superior results in terms of space and time over existing solutions. Results also show that the proposed technique is highly scalable in a parallel execution environment.

No MeSH data available.