HIDDEN MARKOV MODEL (HMM) IS APPLIED TO THE CASE OF MUTATION OF HUMAN MITOCHONDRIAL DNA. A TOTAL OF 25 SAMPLES WERE TAKEN AT RANDOM FROM THE 100 SEQUENCES OF HUMAN MITOCHONDRIAL DNA. FROM EACH SAMPLE, THE EMISSION MATRICES AND THE TRANSITION MATRICES WERE DETERMINED. FURTHERMORE, THE VITERBI ALGORITHM IS USED TO FIND THE OPTIMAL HIDDEN STATE SEQUENCE (MUTATION / NORMAL). THIS ALGORITHM SHOWS THAT THERE IS NO MUTATION THAT ARISE IN EACH SAMPLE. FURTHERMORE, THE LEVEL OF UNCERTAINTY OF THE MODELS WERE OBTAINED WITH A VARIETY ENTROPY BETWEEN 7.1735 TO 49.7388. THERE ARE 3 MODELS WHICH HAVE ENTROPY 7.1735 AND 1 MODEL WHICH HAS ENTROPY 49.7388.

HIDDEN MARKOV MODEL (HMM) IS APPLIED TO THE CASE OF MUTATION OF HUMAN MITOCHONDRIAL DNA. A TOTAL OF 25 SAMPLES WERE TAKEN AT RANDOM FROM THE 100 SEQUENCES OF HUMAN MITOCHONDRIAL DNA. FROM EACH SAMPLE, THE EMISSION MATRICES AND THE TRANSITION MATRICES WERE DETERMINED. FURTHERMORE, THE VITERBI ALGORITHM IS USED TO FIND THE OPTIMAL HIDDEN STATE SEQUENCE (MUTATION / NORMAL). THIS ALGORITHM SHOWS THAT THERE IS NO MUTATION THAT ARISE IN EACH SAMPLE. FURTHERMORE, THE LEVEL OF UNCERTAINTY OF THE MODELS WERE OBTAINED WITH A VARIETY ENTROPY BETWEEN 7.1735 TO 49.7388. THERE ARE 3 MODELS WHICH HAVE ENTROPY 7.1735 AND 1 MODEL WHICH HAS ENTROPY 49.7388.

Hidden Markov Model (HMM) is applied to the case of mutation of human mitochondrial DNA. A total of 25 samples were taken at random from the 100 sequences of human mitochondrial DNA. From each sample, the emission matrices and the transition matrices were determined. Furthermore, the Viterbi algorit...

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Main Author: Vantika, Sandy
Format: Theses
Language:Indonesia
Online Access:https://digilib.itb.ac.id/gdl/view/69646
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spelling id-itb.:696462022-11-04T13:50:42ZHIDDEN MARKOV MODEL (HMM) IS APPLIED TO THE CASE OF MUTATION OF HUMAN MITOCHONDRIAL DNA. A TOTAL OF 25 SAMPLES WERE TAKEN AT RANDOM FROM THE 100 SEQUENCES OF HUMAN MITOCHONDRIAL DNA. FROM EACH SAMPLE, THE EMISSION MATRICES AND THE TRANSITION MATRICES WERE DETERMINED. FURTHERMORE, THE VITERBI ALGORITHM IS USED TO FIND THE OPTIMAL HIDDEN STATE SEQUENCE (MUTATION / NORMAL). THIS ALGORITHM SHOWS THAT THERE IS NO MUTATION THAT ARISE IN EACH SAMPLE. FURTHERMORE, THE LEVEL OF UNCERTAINTY OF THE MODELS WERE OBTAINED WITH A VARIETY ENTROPY BETWEEN 7.1735 TO 49.7388. THERE ARE 3 MODELS WHICH HAVE ENTROPY 7.1735 AND 1 MODEL WHICH HAS ENTROPY 49.7388. Vantika, Sandy Indonesia Theses DNA, entropy, HMM, mitochondrial, mutation. INSTITUT TEKNOLOGI BANDUNG https://digilib.itb.ac.id/gdl/view/69646 Hidden Markov Model (HMM) is applied to the case of mutation of human mitochondrial DNA. A total of 25 samples were taken at random from the 100 sequences of human mitochondrial DNA. From each sample, the emission matrices and the transition matrices were determined. Furthermore, the Viterbi algorithm is used to find the optimal hidden state sequence (mutation / normal). This algorithm shows that there is no mutation that arise in each sample. Furthermore, the level of uncertainty of the models were obtained with a variety entropy between 7.1735 to 49.7388. There are 3 models which have entropy 7.1735 and 1 model which has entropy 49.7388. 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 Hidden Markov Model (HMM) is applied to the case of mutation of human mitochondrial DNA. A total of 25 samples were taken at random from the 100 sequences of human mitochondrial DNA. From each sample, the emission matrices and the transition matrices were determined. Furthermore, the Viterbi algorithm is used to find the optimal hidden state sequence (mutation / normal). This algorithm shows that there is no mutation that arise in each sample. Furthermore, the level of uncertainty of the models were obtained with a variety entropy between 7.1735 to 49.7388. There are 3 models which have entropy 7.1735 and 1 model which has entropy 49.7388.
format Theses
author Vantika, Sandy
spellingShingle Vantika, Sandy
HIDDEN MARKOV MODEL (HMM) IS APPLIED TO THE CASE OF MUTATION OF HUMAN MITOCHONDRIAL DNA. A TOTAL OF 25 SAMPLES WERE TAKEN AT RANDOM FROM THE 100 SEQUENCES OF HUMAN MITOCHONDRIAL DNA. FROM EACH SAMPLE, THE EMISSION MATRICES AND THE TRANSITION MATRICES WERE DETERMINED. FURTHERMORE, THE VITERBI ALGORITHM IS USED TO FIND THE OPTIMAL HIDDEN STATE SEQUENCE (MUTATION / NORMAL). THIS ALGORITHM SHOWS THAT THERE IS NO MUTATION THAT ARISE IN EACH SAMPLE. FURTHERMORE, THE LEVEL OF UNCERTAINTY OF THE MODELS WERE OBTAINED WITH A VARIETY ENTROPY BETWEEN 7.1735 TO 49.7388. THERE ARE 3 MODELS WHICH HAVE ENTROPY 7.1735 AND 1 MODEL WHICH HAS ENTROPY 49.7388.
author_facet Vantika, Sandy
author_sort Vantika, Sandy
title HIDDEN MARKOV MODEL (HMM) IS APPLIED TO THE CASE OF MUTATION OF HUMAN MITOCHONDRIAL DNA. A TOTAL OF 25 SAMPLES WERE TAKEN AT RANDOM FROM THE 100 SEQUENCES OF HUMAN MITOCHONDRIAL DNA. FROM EACH SAMPLE, THE EMISSION MATRICES AND THE TRANSITION MATRICES WERE DETERMINED. FURTHERMORE, THE VITERBI ALGORITHM IS USED TO FIND THE OPTIMAL HIDDEN STATE SEQUENCE (MUTATION / NORMAL). THIS ALGORITHM SHOWS THAT THERE IS NO MUTATION THAT ARISE IN EACH SAMPLE. FURTHERMORE, THE LEVEL OF UNCERTAINTY OF THE MODELS WERE OBTAINED WITH A VARIETY ENTROPY BETWEEN 7.1735 TO 49.7388. THERE ARE 3 MODELS WHICH HAVE ENTROPY 7.1735 AND 1 MODEL WHICH HAS ENTROPY 49.7388.
title_short HIDDEN MARKOV MODEL (HMM) IS APPLIED TO THE CASE OF MUTATION OF HUMAN MITOCHONDRIAL DNA. A TOTAL OF 25 SAMPLES WERE TAKEN AT RANDOM FROM THE 100 SEQUENCES OF HUMAN MITOCHONDRIAL DNA. FROM EACH SAMPLE, THE EMISSION MATRICES AND THE TRANSITION MATRICES WERE DETERMINED. FURTHERMORE, THE VITERBI ALGORITHM IS USED TO FIND THE OPTIMAL HIDDEN STATE SEQUENCE (MUTATION / NORMAL). THIS ALGORITHM SHOWS THAT THERE IS NO MUTATION THAT ARISE IN EACH SAMPLE. FURTHERMORE, THE LEVEL OF UNCERTAINTY OF THE MODELS WERE OBTAINED WITH A VARIETY ENTROPY BETWEEN 7.1735 TO 49.7388. THERE ARE 3 MODELS WHICH HAVE ENTROPY 7.1735 AND 1 MODEL WHICH HAS ENTROPY 49.7388.
title_full HIDDEN MARKOV MODEL (HMM) IS APPLIED TO THE CASE OF MUTATION OF HUMAN MITOCHONDRIAL DNA. A TOTAL OF 25 SAMPLES WERE TAKEN AT RANDOM FROM THE 100 SEQUENCES OF HUMAN MITOCHONDRIAL DNA. FROM EACH SAMPLE, THE EMISSION MATRICES AND THE TRANSITION MATRICES WERE DETERMINED. FURTHERMORE, THE VITERBI ALGORITHM IS USED TO FIND THE OPTIMAL HIDDEN STATE SEQUENCE (MUTATION / NORMAL). THIS ALGORITHM SHOWS THAT THERE IS NO MUTATION THAT ARISE IN EACH SAMPLE. FURTHERMORE, THE LEVEL OF UNCERTAINTY OF THE MODELS WERE OBTAINED WITH A VARIETY ENTROPY BETWEEN 7.1735 TO 49.7388. THERE ARE 3 MODELS WHICH HAVE ENTROPY 7.1735 AND 1 MODEL WHICH HAS ENTROPY 49.7388.
title_fullStr HIDDEN MARKOV MODEL (HMM) IS APPLIED TO THE CASE OF MUTATION OF HUMAN MITOCHONDRIAL DNA. A TOTAL OF 25 SAMPLES WERE TAKEN AT RANDOM FROM THE 100 SEQUENCES OF HUMAN MITOCHONDRIAL DNA. FROM EACH SAMPLE, THE EMISSION MATRICES AND THE TRANSITION MATRICES WERE DETERMINED. FURTHERMORE, THE VITERBI ALGORITHM IS USED TO FIND THE OPTIMAL HIDDEN STATE SEQUENCE (MUTATION / NORMAL). THIS ALGORITHM SHOWS THAT THERE IS NO MUTATION THAT ARISE IN EACH SAMPLE. FURTHERMORE, THE LEVEL OF UNCERTAINTY OF THE MODELS WERE OBTAINED WITH A VARIETY ENTROPY BETWEEN 7.1735 TO 49.7388. THERE ARE 3 MODELS WHICH HAVE ENTROPY 7.1735 AND 1 MODEL WHICH HAS ENTROPY 49.7388.
title_full_unstemmed HIDDEN MARKOV MODEL (HMM) IS APPLIED TO THE CASE OF MUTATION OF HUMAN MITOCHONDRIAL DNA. A TOTAL OF 25 SAMPLES WERE TAKEN AT RANDOM FROM THE 100 SEQUENCES OF HUMAN MITOCHONDRIAL DNA. FROM EACH SAMPLE, THE EMISSION MATRICES AND THE TRANSITION MATRICES WERE DETERMINED. FURTHERMORE, THE VITERBI ALGORITHM IS USED TO FIND THE OPTIMAL HIDDEN STATE SEQUENCE (MUTATION / NORMAL). THIS ALGORITHM SHOWS THAT THERE IS NO MUTATION THAT ARISE IN EACH SAMPLE. FURTHERMORE, THE LEVEL OF UNCERTAINTY OF THE MODELS WERE OBTAINED WITH A VARIETY ENTROPY BETWEEN 7.1735 TO 49.7388. THERE ARE 3 MODELS WHICH HAVE ENTROPY 7.1735 AND 1 MODEL WHICH HAS ENTROPY 49.7388.
title_sort hidden markov model (hmm) is applied to the case of mutation of human mitochondrial dna. a total of 25 samples were taken at random from the 100 sequences of human mitochondrial dna. from each sample, the emission matrices and the transition matrices were determined. furthermore, the viterbi algorithm is used to find the optimal hidden state sequence (mutation / normal). this algorithm shows that there is no mutation that arise in each sample. furthermore, the level of uncertainty of the models were obtained with a variety entropy between 7.1735 to 49.7388. there are 3 models which have entropy 7.1735 and 1 model which has entropy 49.7388.
url https://digilib.itb.ac.id/gdl/view/69646
_version_ 1822991094862839808

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