Results 1 - 10 of 619

MEGA5: Molecular evolutionary genetics analysis using maximum . . .

by Koichiro Tamura, Daniel Peterson, Nicholas Peterson, Glen Stecher, Masatoshi Nei, Sudhir Kumar , 2011
"... Comparative analysis of molecular sequence data is essential for reconstructing the evolutionary histories of species and inferring the nature and extent of selective forces shaping the evolution of genes and species. Here, we announce the release of Molecular Evolutionary Genetics Analysis version ..."
Abstract - Cited by 7284 (25 self) - Add to MetaCart
) analyses for inferring evolutionary trees, selecting best-fit substitution models (nucleotide or amino acid), inferring ancestral states and sequences (along with probabilities), and estimating evolutionary rates site-by-site. In computer simulation analyses, ML tree inference algorithms in MEGA5 compared

Evolving Networks: Using the Genetic Algorithm with Connectionist Learning

by Richard K. Belew, John Mcinerney, Nicol N. Schraudolph - In , 1990
"... It is appealing to consider hybrids of neural-network learning algorithms with evolutionary search procedures, simply because Nature has so successfully done so. In fact, computational models of learning and evolution offer theoretical biology new tools for addressing questions about Nature that hav ..."
Abstract - Cited by 193 (2 self) - Add to MetaCart
It is appealing to consider hybrids of neural-network learning algorithms with evolutionary search procedures, simply because Nature has so successfully done so. In fact, computational models of learning and evolution offer theoretical biology new tools for addressing questions about Nature

A Framework for Evolutionary Optimization with Approximate Fitness Functions

by Yaochu Jin, Markus Olhofer, Bernhard Sendhoff - IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION , 2002
"... It is a common engineering practice to use approximate models instead of the original computationally expensive model in optimization. When an approximate model is used for evolutionary optimization, the convergence properties of the evolutionary algorithm are unclear due to the approximation error. ..."
Abstract - Cited by 117 (18 self) - Add to MetaCart
It is a common engineering practice to use approximate models instead of the original computationally expensive model in optimization. When an approximate model is used for evolutionary optimization, the convergence properties of the evolutionary algorithm are unclear due to the approximation error

A Study of Shape Parameterisation Methods for Airfoil Optimisation

by Wenbin Song, Andrew J. Keane
"... This paper presents a study on parameterisation methods for airfoil shape optimisation within a CAD-based design optimisation framework. The objective of the paper is to study the effect of different methods on airfoil shape optimisation when using computational fluid dynamics (CFD). Parameterisatio ..."
Abstract - Cited by 7 (2 self) - Add to MetaCart
This paper presents a study on parameterisation methods for airfoil shape optimisation within a CAD-based design optimisation framework. The objective of the paper is to study the effect of different methods on airfoil shape optimisation when using computational fluid dynamics (CFD

The Adaptive Self Parameterising Texture Region Boundary Tracker

by D M Booth, J E W Mayhew
"... A texture segmentation algorithm is described. Its approach is to locate the texture boundary within a processing window, and then follow the discontinuity through the image. The system operates in two modes: bootstrap and feed forward mode. In bootstrap mode a portion of the image is segmented, the ..."
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: • What texture measures should be used? • Over how small an area can the texture measures be computed with a reasonable level of statistical confidence? • How is the training set to be derived and modeled? • What type of clustering algorithm should be employed? • What will be the source of the prototype

Modelling and analysis of gene regulatory networks,

by Guy Karlebach , Ron Shamir - Nat Rev Mol Cell Biol , 2008
"... The genome encodes thousands of genes whose pro ducts enable cell survival and numerous cellular func tions. The amounts and the temporal pattern in which these products appear in the cell are crucial to the pro cesses of life. Gene regulatory networks govern the levels of these gene products. A ge ..."
Abstract - Cited by 118 (2 self) - Add to MetaCart
range of behaviours that this system exhibits under different conditions? What changes are expected in the dynamics of the system if certain parts stop functioning? How robust is the system under extreme conditions? Various computational models have been developed for regulatory network analysis

On the computational complexity of the rooted subtree prune and regraft distance

by Magnus Bordewich, Charles Semple - ANNALS OF COMBINATORICS , 2004
"... The graph-theoretic operation of rooted subtree prune and regraft is increasingly being used as a tool for understanding and modelling reticulation events in evolutionary biology. In this paper, we show that computing the rooted subtree prune and regraft distance between two rooted binary phylogene ..."
Abstract - Cited by 78 (8 self) - Add to MetaCart
The graph-theoretic operation of rooted subtree prune and regraft is increasingly being used as a tool for understanding and modelling reticulation events in evolutionary biology. In this paper, we show that computing the rooted subtree prune and regraft distance between two rooted binary

Adaptively Parameterised Evolutionary Systems: Self Adaptive Recombination and Mutation in a Genetic Algorithm

by Smith Fogarty , 1996
"... . It has long been recognised that the choice of recombination and mutation operators and the rates at which they are applied to a Genetic Algorithm will have a significant effect on the outcome of the evolutionary search, with sub-optimal values often leading to poor performance. In this paper an e ..."
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an evolutionary algorithm (APES) is presented within which both the units of heredity and the probability that those units will subject to mutation are learnt via self adaptation of the genetic material. Using Kaufmann's NK model, this algorithm is compared to a number of combinations of frequently used

The System for Evolutionary Computing on the Computational Grid

by Yusuke Tanimura, Tomoyuki Hiroyasu, Mitsunori Miki - In Parallel and Distributed Computing and Systems (PDCS 2002 , 2002
"... The computational Grid can offer users tremendous computer resources. Many researchers are developing the Grid middleware and the typical results are Grid RPCs. However, application models are restricted to use when Grid RPCs are applied. In this paper, we proposed the "EVOLVE/G" system fo ..."
Abstract - Cited by 3 (0 self) - Add to MetaCart
The computational Grid can offer users tremendous computer resources. Many researchers are developing the Grid middleware and the typical results are Grid RPCs. However, application models are restricted to use when Grid RPCs are applied. In this paper, we proposed the "EVOLVE/G" system

Automatic program repair with evolutionary computation,”

by Stephanie Forrest , Westley Weimer , Stephanie Forrest , Claire Le Goues , Thanhvu Nguyen - Commun. ACM, , 2010
"... Abstract There are many methods for detecting and mitigating software errors but few generic methods for automatically repairing errors once they are discovered. This paper highlights recent work combining program analysis methods with evolutionary computation to automatically repair bugs in off-th ..."
Abstract - Cited by 34 (5 self) - Add to MetaCart
Abstract There are many methods for detecting and mitigating software errors but few generic methods for automatically repairing errors once they are discovered. This paper highlights recent work combining program analysis methods with evolutionary computation to automatically repair bugs in off
Results 1 - 10 of 619