1998 Fiscal Year Final Research Report Summary
Inference of molecular phylogenetic tree based on minimum complexity principle
| Project/Area Number |
09680354
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
Intelligent informatics
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| Research Institution | Medical Research Institute, Tokyo Medical and Dental University |
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Principal Investigator |
TANAKA Hiroshi Medical Research Institute/Tokyo Medical and Dental University Professor, 難治疾患研究所, 教授 (60155158)
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| Co-Investigator(Kenkyū-buntansha) |
REN Fengrong Medical Research Institute/Tokyo Medical and Dental University Research Assistan, 難治疾患研究所, 教務職員 (60280989)
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| Project Period (FY) |
1997 – 1998
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| Keywords | Molecular phylogenetic tree / Minimum complexity principle / Model-based complexity / Maximum likelihood method / DNA sequence |
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| Research Abstract |
In reconstruction of phylogenetic trees from molecular data, it has been pointed oat that multifurcate phylogenetic trees are difficult to be correctly reconstructed by the conventional methods like maximum likelihood method. In order to resolve this problem, we have been engaged in developing a new phylogenetic tree reconstruction method based on the minimum complexity principle widely used in the inductive inference. In this study, we defined a new concept of complexity, which we call "empirical model-based complexity" and proposed "minimum model-based complexity(MBC)" criterion for reconstructing molecular phylogenetic tree. This method describes the complexity of molecular phylogenetic tree by three terms which are related to the tree topology, the branch length and fitness between the model and data measured by likelihood function.
The Computer simulation is used to investigate the efficiency of this method in estimating rooted and unrooted phylogenetic tree in comparison with those of maximum likelihood method and Akaike information method(AIC). The results suggest that the MBC method has a good asymptotic property compared with traditional maximum likelihood method or its modification, AIC method in the case that the multifurcate tree is considered as a candidate topology of the tree and/or long DNA sequences could be used in reconstructing phylogenetic tree (over 3000-bp), because it avoids excess-complexity of the tree model in relation to the amount of the information available from DNA sequences of current species. Therefore it could be generally used for reconstruction of phylogenetic tree having arbitrary multifurcations.
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