Michael Arock

Work place: Department of Computer Applications, National Institute of Technology, Tiruchirappalli, Tamil Nadu, India

E-mail: michael@nitt.edu


Research Interests: Computer systems and computational processes, Autonomic Computing, Data Structures and Algorithms, Analysis of Algorithms


Dr. Michael Arock is an Associate Professor presently working in the Department of Computer Applications, National Institute of Technology, and Tiruchirappalli. His specialization is Parallel Algorithms. His Areas of interest include Data Structures and Algorithms, High Performance Computing and Bioinformatics. Currently, he guides Ph.D scholars in the field of DNA computing, natural Language Processing and Bioinformatics.

Author Articles
Aligning Molecular Sequences by Wavelet Transform using Cross Correlation Similarity Metric

By J.Jayapriya Michael Arock

DOI: https://doi.org/10.5815/ijisa.2017.11.08, Pub. Date: 8 Nov. 2017

The first fact of sequence analysis is sequence alignment for the study of structural and functional analysis of the molecular sequence. Owing to the increase in biological data, there is a trade-off between accuracy and the computation of sequence alignment process. Sequences can be aligned both in locally and globally to gives vital information for biologists. Focusing these issues, in this work the local and global alignment are focused on aligning multiple molecular sequences by applying a wavelet transform. Here, the sequence is converted into numerical values using the electron-ion interaction potential model. This is decomposed using a type of wavelet transform and the similarity between the sequences is found using the cross- correlation measure. The significance of the similarity is evaluated using two scoring function namely Position Specific Matrix and a new function called Count score. The work is compared with Fast Fourier Transform based approach and the result shows that the proposed method improves the alignment.

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A Novel Distance Metric for Aligning Multiple Sequences Using DNA Hybridization Process

By Jayapriya J Michael Arock

DOI: https://doi.org/10.5815/ijisa.2016.06.05, Pub. Date: 8 Jun. 2016

This paper elucidates a new approach for aligning multiple sequences using DNA operations. A new distance metric using DNA hybridization melting temperature that gives approximate solutions for the multiple sequence alignment (MSA) problem is proposed. This paper provides proof for the proposed distance metric using the distance function properties. With this distance metric, a distance matrix is constructed that generates a guide tree for the alignment. Providing an accurate solution in less computational time is considered to be a challenging task for the MSA problem. Developing an algorithm for the MSA problem is essentially a trade-off between finding an accurate solution and that can be completed in less computational time. In order to reduce the time complexity, the Bio-inspired technique called the DNA computing is applied in calculating the distance between the sequences. The main application of this multiple sequence alignment (MSA) is to identify the sub-sequences for the functional study of the whole genome sequences. The detailed theoretical study of this approach is explained in this paper.

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