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Inference of molecular phylogenetic tree based on minimum complexity principle

Research Project

Project/Area Number 09680354
Research Category

Grant-in-Aid for Scientific Research (C)

Allocation TypeSingle-year Grants
Section一般
Research Field Intelligent informatics
Research InstitutionMedical Research Institute, Tokyo Medical and Dental University

Principal Investigator

TANAKA Hiroshi  Medical Research Institute/Tokyo Medical and Dental University Professor, 難治疾患研究所, 教授 (60155158)

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)
津本 周作  東京医科歯科大学, 難治疾患研究所, 助手 (10251555)
Project Period (FY) 1997 – 1998
Project Status Completed (Fiscal Year 1998)
Budget Amount *help
¥3,600,000 (Direct Cost: ¥3,600,000)
Fiscal Year 1998: ¥500,000 (Direct Cost: ¥500,000)
Fiscal Year 1997: ¥3,100,000 (Direct Cost: ¥3,100,000)
KeywordsMolecular phylogenetic tree / Minimum complexity principle / Model-based complexity / Maximum likelihood method / DNA sequence / 計算生物学 / 分子進化 / 数理統計学 / モデル / 複雑性 / 経験的複雑性 / モデル準拠複雑性法 / 多重分岐系統樹 / 近隣結合法
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.

Report

(3 results)
  • 1998 Annual Research Report   Final Research Report Summary
  • 1997 Annual Research Report
  • Research Products

    (12 results)

All Other

All Publications (12 results)

  • [Publications] H.Tanaka,F.Ren,T.Okayama,T.Gojobori: "Inference of Molecular Phylogenetic Tree Based on Minimum Model-Based Complexity Method" Intelligent Systems for Molecular Biology. 5. 319-328 (1997)

    • Description
      「研究成果報告書概要(和文)」より
    • Related Report
      1998 Final Research Report Summary
  • [Publications] H.Tanaka,F.Ren,T.Okayama,T.Gojobori: "Topology Selection in Unrooted Molecular Phylogenetic Tree by Minimum Model-based Complexity" Pacific Symposium on Biocomputing. 4. 326-337 (1999)

    • Description
      「研究成果報告書概要(和文)」より
    • Related Report
      1998 Final Research Report Summary
  • [Publications] F.Ren,H.Tanaka,T.Okayama,T.Gojobori: "Molecular Phylogenetic Trees Are Inferred by Using Minimum Model-based Complexity" Biocomputing and Emergent Computation. 1. 122-131 (1997)

    • Description
      「研究成果報告書概要(和文)」より
    • Related Report
      1998 Final Research Report Summary
  • [Publications] Hiroshi Tanaka, Fengrong Ren, Toshitsugu Okayama and Takashi Gojobori: "Inference of Molecular Phylogenetic Tree Based on Minimum Model-Based Complexity Method" Intelligent Systems for Molecular Biology. 5.AAAI Press. 319-328 (1997)

    • Description
      「研究成果報告書概要(欧文)」より
    • Related Report
      1998 Final Research Report Summary
  • [Publications] Hiroshi Tanaka, Fengrong Ren, Toshitsugu Okayama and Takashi Gojobori: "Topology Selection in Unrooted Molecular Phylogenetic Tree by Minimum Model-based Complexity" Pacific Symposium on Biocomputing. 4, World Scientific. 326-337 (1999)

    • Description
      「研究成果報告書概要(欧文)」より
    • Related Report
      1998 Final Research Report Summary
  • [Publications] Fengrong Ren, Hiroshi Tanaka, Toshitsugu Okayama and Takashi Gojobori: "Molecular Phylogenetic Trees Are Inferred by Using Minimum Model-based Complexity" Biocomputing and Emergent Computation. 1, Springer-Verlag. 122-131 (1997)

    • Description
      「研究成果報告書概要(欧文)」より
    • Related Report
      1998 Final Research Report Summary
  • [Publications] H. Tanaka: "Towards the theory of bio-complexity" AROB'98. 1. 646-649 (1998)

    • Related Report
      1998 Annual Research Report
  • [Publications] 田中 博: "医学・生物学における高性能計算" 医療情報学誌. 18・1. 13-25 (1998)

    • Related Report
      1998 Annual Research Report
  • [Publications] F. Ren: "Efficiency of Model-based Complexity Method for Estimating unrooted Multifurcare Phylogenetic Tree" Genome Informatics. 9. 342-343 (1998)

    • Related Report
      1998 Annual Research Report
  • [Publications] F. Ren: "The Application of Model-based Complexity Inference Method to Molecular Evolution Analysis" Proc. of MEDINFD. 367-371 (1998)

    • Related Report
      1998 Annual Research Report
  • [Publications] H.Tanaka, F.Ren et al.: "Inference of Molecular Phylogenetic Tree Based on Minimum Model-Based Complexity Method." Proc.,Fifth International Conference on Intelligent Systems for Molecular Biology,AAAI Press, 10 (1997)

    • Related Report
      1997 Annual Research Report
  • [Publications] F.Ren, H.Tanaka et al.: "Molecular Phylogenetic Trees Are Inferred by Using Minimum Model-Based Complexity" Proc.of International Conference on Bio-Computing and Emergent Computation,Springer-Verlag, 10 (1997)

    • Related Report
      1997 Annual Research Report

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Published: 1997-04-01   Modified: 2016-04-21  

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