BAYESIAN MODELS IN PROTEINS ALIGNMENT

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NAJIBI S.MORTEZA; GOLALIZADEH MOUSA; FAGHIHI MOHAMMAD REZA

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Journal: JOURNAL OF STATISTICAL SCIENCES Year:2016 | Volume:9 | Issue:2 Page(s): 253-267

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Information Journal Paper

Title

BAYESIAN MODELS IN PROTEINS ALIGNMENT

Author(s)

NAJIBI S.MORTEZA | GOLALIZADEH MOUSA | FAGHIHI MOHAMMAD REZA | Issue Writer Certificate

Keywords

STATISTICAL SHAPE ANALYSISQ1

SIZEQ2

ANDQ2

SHAPE DISTANCEQ2

BIOINFORMATICSQ2

STRUCTURAL ALIGNMENT OF PROTEINQ2

TERTIARY STRUCTURE OF PROTEINQ2

BAYESIAN INFERENCEQ2

Abstract

In this paper, we study the applicability of probabilistic solutions for the alignment of TERTIARY STRUCTURE OF PROTEINs AND discuss its difference with the deterministic algorithms. For this purpose, we introduce two Bayesian models AND address a solution to add amino acid sequence AND type (primary structure) to protein alignment. Furthermore, we will study the parameter estimation with Markov Chain Monte Carlo sampling from the posterior distribution. Finally, in order to see the effectiveness of these methods in the protein alignment, we have compared the parameter estimations in a real data set.

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APA: Copy

NAJIBI, S.MORTEZA, GOLALIZADEH, MOUSA, & FAGHIHI, MOHAMMAD REZA. (2016). BAYESIAN MODELS IN PROTEINS ALIGNMENT. JOURNAL OF STATISTICAL SCIENCES, 9(2), 253-267. SID. https://sid.ir/paper/124103/en

Vancouver: Copy

NAJIBI S.MORTEZA, GOLALIZADEH MOUSA, FAGHIHI MOHAMMAD REZA. BAYESIAN MODELS IN PROTEINS ALIGNMENT. JOURNAL OF STATISTICAL SCIENCES[Internet]. 2016;9(2):253-267. Available from: https://sid.ir/paper/124103/en

IEEE: Copy

S.MORTEZA NAJIBI, MOUSA GOLALIZADEH, and MOHAMMAD REZA FAGHIHI, “BAYESIAN MODELS IN PROTEINS ALIGNMENT,” JOURNAL OF STATISTICAL SCIENCES, vol. 9, no. 2, pp. 253–267, 2016, [Online]. Available: https://sid.ir/paper/124103/en

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