A computational method to analyze the similarity of biological sequences under uncertainty

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KHASTAN A.; Hooshyar L.

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Journal Paper

Paper Information

Journal: Iranian Journal of Fuzzy Systems Year:2019 | Volume:16 | Issue:6 Page(s): 33-41

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Information Journal Paper

Title

A computational method to analyze the similarity of biological sequences under uncertainty

Author(s)

KHASTAN A. | Hooshyar L. | Issue Writer Certificate

Keywords

Similarity of biological sequencesQ2

fuzzy polynucleotide spaceQ2

fuzzy clusteringQ2

unit hypercubeQ2

fuzzy sim-ilarity matrixQ2

Abstract

In this paper, we propose a new method to analyze the di erence and Similarity of biological sequences, based on the fuzzy sets theory. Considering the sequence order and some chemical and structural properties, we present a computational method to cluster the biological sequences. By some examples, we show that the new method is relatively easy and we are able to compare the sequences of arbitrary lengths.

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APA: Copy

KHASTAN, A., & Hooshyar, L.. (2019). A computational method to analyze the similarity of biological sequences under uncertainty. IRANIAN JOURNAL OF FUZZY SYSTEMS, 16(6 ), 33-41. SID. https://sid.ir/paper/392310/en

Vancouver: Copy

KHASTAN A., Hooshyar L.. A computational method to analyze the similarity of biological sequences under uncertainty. IRANIAN JOURNAL OF FUZZY SYSTEMS[Internet]. 2019;16(6 ):33-41. Available from: https://sid.ir/paper/392310/en

IEEE: Copy

A. KHASTAN, and L. Hooshyar, “A computational method to analyze the similarity of biological sequences under uncertainty,” IRANIAN JOURNAL OF FUZZY SYSTEMS, vol. 16, no. 6 , pp. 33–41, 2019, [Online]. Available: https://sid.ir/paper/392310/en

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