Similarity Analysis of Position Specific Motif Matrices using Lacunarity for Promoter Sequences

Kouser,; Rangarajan, Lalitha

doi:10.1145/2660859.2660949

Cited by 6 publications

(2 citation statements)

References 11 publications

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“…The overall schema and flow of the method is as described in Figure 1. The detailed description of obtaining the PSMM for a promoter is presented in [18], [19]. Once the PSMM is obtained, they are given as input to the various methods briefly described below.…”

Section: Methodsmentioning

confidence: 99%

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Statistical and Alignment Based Methods for Comparison of Non-Coding DNA Sequences

Kouser¹,

Rangarajan²

2015

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Increase in the amount of biological sequence data being generated is due to the advancement in the sequencing technologies. This has led to an upsurge in the need for methods/techniques that analyze these sequences to make biological inferences. Promoter sequences are one such biological sequences that play an important role in the process of gene regulation. These promoter sequences are made up of motifs arranged/configured in a particular order which is very important for its functionality. In this work, we propose a few techniques that capture the information regarding the arrangement of these motifs. Further this captured information help in the analysis of the promoter sequences. The methods use the motif features obtained from the Position Specific Motif Matrices (PSMMs) of the promoter sequences and then give a dissimilarity measure. Alignment-free as well as alignment based methods are proposed. The experimental results show that these methods are quite successful in bringing out the similarity/dissimilarity existing between given promoters/promoter sets. The alignment based method also helps in the process of inferring homology and in the phylogenetic analysis. In general, all the methods might help biologists in applications like drug target identification, biological pathway analysis and gene expression analysis.

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Section: Methodsmentioning

confidence: 99%

“…This value then goes as an entry into the dissimilarity matrix. The algorithm can be found in detail in [18].…”

Section: Lacunarity Based Methodsmentioning

confidence: 99%

Statistical and Alignment Based Methods for Comparison of Non-Coding DNA Sequences

Kouser¹,

Rangarajan²

2015

RCS

Self Cite

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Alignment Free Frequency Based Distance Measures for Promoter Sequence Comparison

Kouser¹,

Rangarajan²,

Chandrashekar

et al. 2015

Bioinformatics and Biomedical Engineering

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Feature Reduced Weighted Fuzzy Binarization for Histogram Comparison of Promoter Sequences

Kouser

Rangarajan

2017

Communications in Computer and Information Science

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Similarity Analysis of Position Specific Motif Matrices using Lacunarity for Promoter Sequences

Cited by 6 publications

References 11 publications

Statistical and Alignment Based Methods for Comparison of Non-Coding DNA Sequences

Statistical and Alignment Based Methods for Comparison of Non-Coding DNA Sequences

Alignment Free Frequency Based Distance Measures for Promoter Sequence Comparison

Feature Reduced Weighted Fuzzy Binarization for Histogram Comparison of Promoter Sequences

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