Evolutionary tree reconstruction using structural expectation maximization and homotopy
Genet. mol. res. (Online)
;
6(3): 522-533, 2007. ilus, tab, graf
Article
in English
| LILACS
| ID: lil-498919
ABSTRACT
The evolutionary tree reconstruction algorithm called SEMPHY using structural expectation maximization (SEM) is an efficient approach but has local optimality problem. To improve SEMPHY, a new algorithm named HSEMPHY based on the homotopy continuation principle is proposed in the present study for reconstructing evolutionary trees. The HSEMPHY algorithm computes the condition probability of hidden variables in the structural through maximum entropy principle. It can reduce the influence of the initial value of the final resolution by simulating the process of the homotopy principle and by introducing the homotopy parameter â. HSEMPHY is tested on real datasets and simulated dataset to compare with SEMPHY and the two most popular reconstruction approaches PHYML and RAXML. Experimental results show that HSEMPHY is at least as good as PHYML and RAXML and is very robust to poor starting trees.
Full text:
Available
Index:
LILACS (Americas)
Main subject:
Algorithms
/
Computer Simulation
/
Software
/
Models, Statistical
/
Computational Biology
/
Models, Genetic
Type of study:
Prognostic study
/
Risk factors
Language:
English
Journal:
Genet. mol. res. (Online)
Journal subject:
Molecular Biology
/
Genetics
Year:
2007
Type:
Article
/
Project document
Affiliation country:
China
Institution/Affiliation country:
School of Computer Science and Technology/CN
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