A New Method to Study DNA Sequences: The Languages pf Evolution

2006 ◽  
Author(s):  
Gino Spinelli ◽  
David Mayer-Foulkes
Keyword(s):  
Dna Sequences ◽  
New Method

A new method to analyze the similarity of the DNA sequences

2008 ◽  
Vol 853 (1-3) ◽  
pp. 62-67 ◽  
Author(s):  
Ying Guo ◽  
Tian-ming Wang
Keyword(s):  
Dna Sequences ◽  
New Method

Resolving the multiple sequence alignment problem using biogeography-based optimization with multiple populations

2015 ◽  
Vol 13 (04) ◽  
pp. 1550016 ◽  
Author(s):  
El-Amine Zemali ◽  
Abdelmadjid Boukra
Keyword(s):  
Sequence Alignment ◽  
Dna Sequences ◽  
Multiple Sequence Alignment ◽  
Search Space ◽  
New Method ◽  
Average Score ◽  
Solution Quality ◽  
Multiple Sequence ◽  
Multiple Populations ◽  
Alignment Problem

The multiple sequence alignment (MSA) is one of the most challenging problems in bioinformatics, it involves discovering similarity between a set of protein or DNA sequences. This paper introduces a new method for the MSA problem called biogeography-based optimization with multiple populations (BBOMP). It is based on a recent metaheuristic inspired from the mathematics of biogeography named biogeography-based optimization (BBO). To improve the exploration ability of BBO, we have introduced a new concept allowing better exploration of the search space. It consists of manipulating multiple populations having each one its own parameters. These parameters are used to build up progressive alignments allowing more diversity. At each iteration, the best found solution is injected in each population. Moreover, to improve solution quality, six operators are defined. These operators are selected with a dynamic probability which changes according to the operators efficiency. In order to test proposed approach performance, we have considered a set of datasets from Balibase 2.0 and compared it with many recent algorithms such as GAPAM, MSA-GA, QEAMSA and RBT-GA. The results show that the proposed approach achieves better average score than the previously cited methods.

scholarly journals SERS-Melting: A New Method for Discriminating Mutations in DNA Sequences

2008 ◽  
Vol 130 (46) ◽  
pp. 15589-15601 ◽  
Author(s):  
Sumeet Mahajan ◽  
James Richardson ◽  
Tom Brown ◽  
Philip N. Bartlett
Keyword(s):  
Dna Sequences ◽  
New Method

scholarly journals The evolutionary origin of the universal distribution of mutation fitness effect

2021 ◽  
Vol 17 (3) ◽  
pp. e1008822
Author(s):  
Ayuna Barlukova ◽  
Igor M. Rouzine
Keyword(s):  
Exponential Distribution ◽  
Dna Sequences ◽  
Large Population ◽  
New Method ◽  
Striking Difference ◽  
Fitness Effect ◽  
Wave Regime ◽  
Site Model ◽  
Fitness Effects

An intriguing fact long defying explanation is the observation of a universal exponential distribution of beneficial mutations in fitness effect for different microorganisms. To explain this effect, we use a population model including mutation, directional selection, linkage, and genetic drift. The multiple-mutation regime of adaptation at large population sizes (traveling wave regime) is considered. We demonstrate analytically and by simulation that, regardless of the inherent distribution of mutation fitness effect across genomic sites, an exponential distribution of fitness effects emerges in the long term. This result follows from the exponential statistics of the frequency of the less-fit alleles, f, that we predict to evolve, in the long term, for both polymorphic and monomorphic sites. We map the logarithmic slope of the distribution onto the previously derived fixation probability and demonstrate that it increases linearly in time. Our results demonstrate a striking difference between the distribution of fitness effects observed experimentally for naturally occurring mutations, and the "inherent" distribution obtained in a directed-mutagenesis experiment, which can have any shape depending on the organism. Based on these results, we develop a new method to measure the fitness effect of mutations for each variable residue using DNA sequences sampled from adapting populations. This new method is not sensitive to linkage effects and does not require the one-site model assumptions.

scholarly journals The evolutionary origin of the universal distribution of mutation fitness effect

2019 ◽  
Author(s):  
Ayuna Barlukova ◽  
Igor M. Rouzine
Keyword(s):  
Exponential Distribution ◽  
Dna Sequences ◽  
Evolutionary Process ◽  
New Method ◽  
Striking Difference ◽  
Fitness Effect ◽  
Site Model ◽  
Fitness Effects ◽  
Linkage Effects

AbstractAn intriguing fact long defying explanation is the observation of a universal exponential distribution of beneficial mutations in fitness effect for different microorganisms. Here we use a general and straightforward analytic model to demonstrate that, regardless of the inherent distribution of mutation fitness effect across genomic sites, an observed exponential distribution of fitness effects emerges naturally in the long term, as a consequence of the evolutionary process. This result follows from the exponential statistics of the frequency of the less-fit alleles f predicted to evolve, in the long term, for both polymorphic and monomorphic sites. The exponential distribution disappears when the system arrives at the steady state, when it is replaced with the classical mutation-selection result, f = μ/s. Based on these findings, we develop a technique to measure selection coefficients for specific genomic sites from two single-time sequence sets. Our results demonstrate the striking difference between the distribution of fitness effects observed experimentally, for naturally occurring mutations, and the “inherent” distribution obtained in a directed-mutagenesis experiment, which can have any shape depending on organism. Based on these results, we develop a new method to measure fitness effects of mutations for each variable residue based on DNA sequences isolated from an adapting population at two time points. This new method is not sensitive to linkage effects and does not require one-site model assumptions.

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