Discover Community Create You

Loading publication...

Noodle always counts identifier-free feature events for service operation. With your permission, Google Analytics can also estimate audience and engagement. Search text, publication identifiers, cookies, IP addresses and browser fingerprints are never included in Noodle's first-party event counters.

Privacy details

Article

The role of crossover operator in evolutionary-based approach to the problem of genetic code optimization.

Bio Systems - 1 Dec 2016

Błażej Paweł, Wnȩtrzak Małgorzata, Mackiewicz Paweł

Abstract excerpt

One of theories explaining the present structure of canonical genetic code assumes that it was optimized to minimize harmful effects of amino acid replacements resulting from nucleotide substitutions and translational errors. A way to testify this concept is to find the optimal code under given criteria and compare it with the canonical genetic code. Unfortunately, the huge number of possible alternatives makes...

Read the complete abstract on PubMed

Topics

Share this publication in a Topic to start or enrich a Post.

Share to Amino Acids
Share to Biological Evolution
Share to Codon

Methodology Data sources Editorial policy Privacy Delete account & data About Contact Helena Bioinformatics

Share to Evolution, Molecular

Share to Genetic Code

Share to Models, Genetic

Share to Mutation

Source

Identifiers

PMID: 27555085
DOI: 10.1016/j.biosystems.2016.08.008

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 7 Sept 2026. Manifest publication-graph-cohort-2026-09-08.1.

Source receipt: pubmed, retrieved 7 Sept 2026.

Related research

Semantic proximity does not establish scientific evidence. Graph snapshot: 2026-09-29.

Research trail→

Click a neighbor to travelStep 1 · 12 closest

The role of crossover operator in evolutionary-based approach to the problem of genetic code optimization.PMID 27555085Read ↗

A multiobjective approach to the genetic code adaptability problem.Semantic proximity Read ↗

Study of the genetic code adaptability by means of a genetic algorithm.Semantic proximity Read ↗

Coding rules for amino acids in the genetic code: the genetic code is a minimal code of mutational deterioration.Semantic proximity Read ↗

Designing a neural network for the constraint optimization of the fitness functions devised based on the load minimization of the genetic code.Semantic proximity Read ↗

Analysis of the optimality of the standard genetic code.Semantic proximity Read ↗

Genetic algorithms in chemistry.Semantic proximity Read ↗

A genetic engineering approach to genetic algorithms.Semantic proximity Read ↗

Chemical genetic algorithms--evolutionary optimization of binary-to-real-value translation in genetic algorithms.Semantic proximity Read ↗

On the coevolution of genes and genetic code.Semantic proximity Read ↗

Guidelines: From artificial evolution to computational evolution: a research agenda.Semantic proximity Read ↗

Experimental verification of the error minimization theory using non-standard genetic codes constructed in vitro.Semantic proximity Read ↗

Computational evolution: taking liberties.Semantic proximity Read ↗

⌁Select a neighboring publication to make it the new centre.