#TITLE_ALTERNATIVE#
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...
Saved in:
主要作者: | |
---|---|
格式: | Theses |
語言: | Indonesia |
在線閱讀: | https://digilib.itb.ac.id/gdl/view/6477 |
標簽: |
添加標簽
沒有標簽, 成為第一個標記此記錄!
|
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 #TITLE_ALTERNATIVE# |
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 |
_version_ |
1825531173448712192 |