Ken D. Nguyen

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One of the most fundamental operation in biological sequence analysis is multiple sequence alignment (MSA). Optimally aligning multiple sequences is an intractable problem; however, it is a critical tool for biologists to identify the relationships between species and also possibly predict the structure and functionality of biological sequences. The most(More)
Aligning multiple DNA/RNA/protein sequences to identify common functionalities, structures, or relationships between species is a fundamental task in bioinformatics. In this study, we propose a new multiple sequence strategy that extracts sequence information, sequence global and local similarities to provide different weights for each input sequence. A(More)
One of the most fundamental and challenging tasks in bio-informatics is to identify related sequences and their hidden biological significance. The most popular and proven best practice method to accomplish this task is aligning multiple sequences together. However, multiple sequence alignment is a computing extensive task. In addition, the advancement in(More)
A common and cost-effective mechanism to identify the functionalities, structures, or relationships between species is multiple-sequence alignment, in which DNA/RNA/protein sequences are arranged and aligned so that similarities between sequences are clustered together. Correctly identifying and aligning these sequence biological similarities help from(More)
In this paper, we demonstrate how to implement and improve two ant colony optimization (ACO) algorithms on the optical pipelined reconfigurable mesh (PR-mesh): the generic ACO and the fast ant colony optimization (FACO) algorithm. The run-time complexity of our improved generic ACO algorithm, with x generations each generation having m ants, on an n times n(More)
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