A maximum likelihood method for reconstruction of the evolution of eukaryotic gene structure.

Liran Carmel; Igor B. Rogozin; Yuri I. Wolf; Eugene V. Koonin

doi:10.1007/978-1-59745-243-4_16

A maximum likelihood method for reconstruction of the evolution of eukaryotic gene structure.

Liran Carmel^*, Igor B. Rogozin, Yuri I. Wolf, Eugene V. Koonin

^*Corresponding author for this work

Research output: Contribution to journal › Review article › peer-review

6 Scopus citations

Abstract

Spliceosomal introns are one of the principal distinctive features of eukaryotes. Nevertheless, different large-scale studies disagree about even the most basic features of their evolution. In order to come up with a more reliable reconstruction of intron evolution, we developed a model that is far more comprehensive than previous ones. This model is rich in parameters, and estimating them accurately is infeasible by straightforward likelihood maximization. Thus, we have developed an expectation-maximization algorithm that allows for efficient maximization. Here, we outline the model and describe the expectation-maximization algorithm in detail. Since the method works with intron presence-absence maps, it is expected to be instrumental for the analysis of the evolution of other binary characters as well.

Original language	English
Pages (from-to)	357-371
Number of pages	15
Journal	Methods in Molecular Biology
Volume	541
DOIs	https://doi.org/10.1007/978-1-59745-243-4_16
State	Published - 2009
Externally published	Yes

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title = "A maximum likelihood method for reconstruction of the evolution of eukaryotic gene structure.",

abstract = "Spliceosomal introns are one of the principal distinctive features of eukaryotes. Nevertheless, different large-scale studies disagree about even the most basic features of their evolution. In order to come up with a more reliable reconstruction of intron evolution, we developed a model that is far more comprehensive than previous ones. This model is rich in parameters, and estimating them accurately is infeasible by straightforward likelihood maximization. Thus, we have developed an expectation-maximization algorithm that allows for efficient maximization. Here, we outline the model and describe the expectation-maximization algorithm in detail. Since the method works with intron presence-absence maps, it is expected to be instrumental for the analysis of the evolution of other binary characters as well.",

author = "Liran Carmel and Rogozin, {Igor B.} and Wolf, {Yuri I.} and Koonin, {Eugene V.}",

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AU - Rogozin, Igor B.

AU - Wolf, Yuri I.

AU - Koonin, Eugene V.

PY - 2009

Y1 - 2009

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AB - Spliceosomal introns are one of the principal distinctive features of eukaryotes. Nevertheless, different large-scale studies disagree about even the most basic features of their evolution. In order to come up with a more reliable reconstruction of intron evolution, we developed a model that is far more comprehensive than previous ones. This model is rich in parameters, and estimating them accurately is infeasible by straightforward likelihood maximization. Thus, we have developed an expectation-maximization algorithm that allows for efficient maximization. Here, we outline the model and describe the expectation-maximization algorithm in detail. Since the method works with intron presence-absence maps, it is expected to be instrumental for the analysis of the evolution of other binary characters as well.

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A maximum likelihood method for reconstruction of the evolution of eukaryotic gene structure.

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