An improving method for estimating amino acid replacement models
Amino acid replacement models (amino acid substitution models or ma-trices) play important roles in protein phylogenetics analysis and protein sequence alignment. Dayhoff was the fi rst person who proposed a method to build amino acid models in 1972. Currently, maximum likelihood (ML) methods ar...
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| Main Author: | |
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| Format: | Theses and Dissertations |
| Language: | other |
| Published: |
Đại học Quốc gia Hà Nội
2016
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| Subjects: | |
| Online Access: | http://repository.vnu.edu.vn/handle/VNU_123/8266 |
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| Institution: | Vietnam National University, Hanoi |
| Language: | other |
| Summary: | Amino acid replacement models (amino acid substitution models or ma-trices) play important roles in protein phylogenetics analysis and protein sequence
alignment. Dayhoff was the fi rst person who proposed a method to build amino
acid models in 1972. Currently, maximum likelihood (ML) methods are widely
used to estimate popular models such as WAG, LG, FLU, etc. However, ML
methods are slow and not applicable to large datasets. The most time consuming
step in estimating matrices is build-ingphylogenetics trees from protein
alignments. In this thesis, we propose new methods to overcome the obstacle by
splitting large alignments into small ones which still contain enough evolutionary
information for esti-mating matrices. Experiments with both Pfam and FLU data
sets show that proposed meth-ods are about three to nine times faster than the best
current method while the quality of estimated matrices are nearly the same. Thus,
our methods will enable researchers to estimate matrices from very large datasets. |
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