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303,903
Maximum likelihood from incomplete data via the EM algorithm
 JOURNAL OF THE ROYAL STATISTICAL SOCIETY, SERIES B
, 1977
"... A broadly applicable algorithm for computing maximum likelihood estimates from incomplete data is presented at various levels of generality. Theory showing the monotone behaviour of the likelihood and convergence of the algorithm is derived. Many examples are sketched, including missing value situat ..."
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Cited by 11962 (17 self)
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A broadly applicable algorithm for computing maximum likelihood estimates from incomplete data is presented at various levels of generality. Theory showing the monotone behaviour of the likelihood and convergence of the algorithm is derived. Many examples are sketched, including missing value
A Simple, Fast, and Accurate Algorithm to Estimate Large Phylogenies by Maximum Likelihood
, 2003
"... The increase in the number of large data sets and the complexity of current probabilistic sequence evolution models necessitates fast and reliable phylogeny reconstruction methods. We describe a new approach, based on the maximumlikelihood principle, which clearly satisfies these requirements. The ..."
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Cited by 2176 (27 self)
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of distancebased and parsimony approaches. The reduction of computing time is dramatic in comparison with other maximumlikelihood packages, while the likelihood maximization ability tends to be higher. For example, only 12 min were required on a standard personal computer to analyze a data set consisting
Mega: molecular evolutionary genetic analysis software for microcomputers
 CABIOS
, 1994
"... A computer program package called MEGA has been developed for estimating evolutionary distances, reconstructing phylogenetic trees and computing basic statistical quantities from molecular data. It is written in C+ + and is intended to be used on IBM and IBMcompatible personal computers. In this pr ..."
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Cited by 503 (10 self)
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. In this program, various methods for estimating evolutionary distances from nucleotide and amino acid sequence data, three different methods of phylogenetic inference (UPGMA, neighborjoining and maximum parsimony) and two statistical tests of topological differences are included. For the maximum parsimony method
Y: Haplotype inference by maximum parsimony
 Bioinformatics
"... Motivation: Haplotypes have been attracting increasing attention because of their importance in analysis of many finescale moleculargenetics data. Since direct sequencing of haplotype via experimental methods is both timeconsuming and expensive, haplotype inference methods that infer haplotypes b ..."
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Cited by 64 (4 self)
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Motivation: Haplotypes have been attracting increasing attention because of their importance in analysis of many finescale moleculargenetics data. Since direct sequencing of haplotype via experimental methods is both timeconsuming and expensive, haplotype inference methods that infer haplotypes
Supervised learning from incomplete data via an EM approach
 Advances in Neural Information Processing Systems 6
, 1994
"... Realworld learning tasks may involve highdimensional data sets with arbitrary patterns of missing data. In this paper we present a framework based on maximum likelihood density estimation for learning from such data sets. We use mixture models for the density estimates and make two distinct appeal ..."
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Cited by 232 (2 self)
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Realworld learning tasks may involve highdimensional data sets with arbitrary patterns of missing data. In this paper we present a framework based on maximum likelihood density estimation for learning from such data sets. We use mixture models for the density estimates and make two distinct
Parsimony accelerated Maximum Likelihood searches
 INTERNATIONAL JOURNAL OF COMPUTAIONAL BIOLOGY AND DRUG DESIGN
, 2008
"... Phylogenetic search is a key tool used in a variety of biological research endeavors. However, this search problem is known to be computationally difficult, due to the astronomically large search space, making the use of heuristic methods necessary. The performance of heuristic methods for finding ..."
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Cited by 2 (1 self)
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for finding maximum likelihood trees can be improved by using parsimony as an initial estimator for maximum likelihood. The time spent in performing the parsimony search to boost performance is insignificant compared to the time spent in the maximum likelihood search, leading to an overall gain in search time
Parametric maximum parsimonious reconstruction on trees
, 2009
"... We give a formal study of the relationships between the transition cost parameters and the generalized maximum parsimonious reconstructions of unknown (ancestral) binary character states {0, 1} over a phylogenetic tree. As a main result, we show there are two thresholds λ1n and λ 0 n, generally con ..."
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erally confounded, associated to each node n of the phylogenetic tree and such that there exists a maximum parsimonious reconstruction associating state 1 to n (resp. state 0 to n) if the ratio “10cost”/“01cost ” is smaller than λ1n (resp. greater than λ 0 n). We propose a dynamic programming algorithm computing
Parsimonious Neurofuzzy
, 1996
"... this paper. Another important issue when constructing models from empirical data, is the quality of this data. Ideally this data should be well distributed and noise free, two unrealistic demands (especially in high dimensions). A common approach to these problems in both statistical and neural netw ..."
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this paper. Another important issue when constructing models from empirical data, is the quality of this data. Ideally this data should be well distributed and noise free, two unrealistic demands (especially in high dimensions). A common approach to these problems in both statistical and neural
An approximation algorithm for haplotype inference by maximum parsimony
 Journal of Computational Biology
, 2005
"... This paper studies haplotype inference by maximum parsimony using population data. We define the optimal haplotype inference (OHI) problem as given a set of genotypes and a set of related haplotypes, find a minimum subset of haplotypes that can resolve all the genotypes. We prove that OHI is NPhard ..."
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Cited by 31 (2 self)
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This paper studies haplotype inference by maximum parsimony using population data. We define the optimal haplotype inference (OHI) problem as given a set of genotypes and a set of related haplotypes, find a minimum subset of haplotypes that can resolve all the genotypes. We prove that OHI is NP
Results 1  10
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303,903