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Abstract; <br /> <br /> <br /> <br /> <br /> <br /> <br /> <br /> <br /> <br /> <br /> <br /> <br /> <br /> <br /> In analysis of phylogenetic model, intensity of nucleotide substitutio...

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Main Author: Haryono ( NIM: 20105017), Mohamad
Format: Theses
Language:Indonesia
Online Access:https://digilib.itb.ac.id/gdl/view/6477
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Institution: Institut Teknologi Bandung
Language: Indonesia
id id-itb.:6477
spelling id-itb.:64772017-09-27T14:41:44Z#TITLE_ALTERNATIVE# Haryono ( NIM: 20105017), Mohamad Indonesia Theses INSTITUT TEKNOLOGI BANDUNG https://digilib.itb.ac.id/gdl/view/6477 Abstract; <br /> <br /> <br /> <br /> <br /> <br /> <br /> <br /> <br /> <br /> <br /> <br /> <br /> <br /> <br /> In analysis of phylogenetic model, intensity of nucleotide substitution is very important as a measure of evolutionary rate. Hidden Markov model (HMM) is allowed in this model for category of evolutionary rate, by assuming that rate of evolution is different for each site. In here, evolutionary rate is assumed having <br /> <br /> <br /> <br /> <br /> <br /> <br /> <br /> <br /> <br /> <br /> <br /> <br /> <br /> <br /> gamma distribution. Felsenstein Algorithm is used to calculate likelihood of the model. This algorithm is identical process with backward algorithm that usually used in HMM. Viterbi algorithm is used to find the optimal state of rate category. To estimate transition matrix, we used Baum Welch algorithm by involving <br /> <br /> <br /> <br /> <br /> <br /> <br /> <br /> <br /> <br /> <br /> <br /> <br /> <br /> <br /> autocorrelation function from rate categories among neighboring sites. text
institution Institut Teknologi Bandung
building Institut Teknologi Bandung Library
continent Asia
country Indonesia
Indonesia
content_provider Institut Teknologi Bandung
collection Digital ITB
language Indonesia
description Abstract; <br /> <br /> <br /> <br /> <br /> <br /> <br /> <br /> <br /> <br /> <br /> <br /> <br /> <br /> <br /> In analysis of phylogenetic model, intensity of nucleotide substitution is very important as a measure of evolutionary rate. Hidden Markov model (HMM) is allowed in this model for category of evolutionary rate, by assuming that rate of evolution is different for each site. In here, evolutionary rate is assumed having <br /> <br /> <br /> <br /> <br /> <br /> <br /> <br /> <br /> <br /> <br /> <br /> <br /> <br /> <br /> gamma distribution. Felsenstein Algorithm is used to calculate likelihood of the model. This algorithm is identical process with backward algorithm that usually used in HMM. Viterbi algorithm is used to find the optimal state of rate category. To estimate transition matrix, we used Baum Welch algorithm by involving <br /> <br /> <br /> <br /> <br /> <br /> <br /> <br /> <br /> <br /> <br /> <br /> <br /> <br /> <br /> autocorrelation function from rate categories among neighboring sites.
format Theses
author Haryono ( NIM: 20105017), Mohamad
spellingShingle Haryono ( NIM: 20105017), Mohamad
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author_facet Haryono ( NIM: 20105017), Mohamad
author_sort Haryono ( NIM: 20105017), Mohamad
title #TITLE_ALTERNATIVE#
title_short #TITLE_ALTERNATIVE#
title_full #TITLE_ALTERNATIVE#
title_fullStr #TITLE_ALTERNATIVE#
title_full_unstemmed #TITLE_ALTERNATIVE#
title_sort #title_alternative#
url https://digilib.itb.ac.id/gdl/view/6477
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