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Related Concept Videos

Multi-species Conserved Sequences02:51

Multi-species Conserved Sequences

Next-generation sequencing technologies have created large genomic databases of a variety of animals and plants. Ever since the human genome project was completed, scientists studied the genome of primates, mammals, and other phylogenetically distant living beings. Such large-scale  studies have provided new insights into the evolutionary relationship between organisms.
Although the genome of each species varies greatly from each other, a few sequences are highly conserved. Such conserved DNA...
Genetic Variation01:25

Genetic Variation

Genetic variation is the diversity in DNA sequences found among individuals of the same species. This diversity is crucial for a species' survival because it helps organisms adapt to environmental changes. Genetic variation begins with fertilization, where an egg and sperm cell merge. Each of these cells carries 23 chromosomes, up to 46 in the fertilized egg. Chromosomes are long DNA strands that contain genes, the basic units of heredity.
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Genetic Screens02:46

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Because the DNA segments are cut and reorganized in a direction-specific manner, site-specific recombination has emerged as an efficient genetic engineering technique. Flippase and Cyclization recombinases or Flp and Cre, respectively, are two members of the tyrosine recombinase family derived from bacteriophages, that are used to mediate site-specific DNA insertions, deletions, and targeted expression of proteins in mammalian cell lines.
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Gene Evolution - Fast or Slow?02:05

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The genomes of eukaryotes are punctuated by long stretches of sequence which do not code for proteins or RNAs. Although some of these regions do contain crucial regulatory sequences, the vast majority of this DNA serves no known function. Typically, these regions of the genome are the ones in which the fastest change, in evolutionary terms, is observed, because there is typically little to no selection pressure acting on these regions to preserve their sequences.
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Updated: May 16, 2026

Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry
05:53

Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry

Published on: June 21, 2018

Core Hunter II: fast core subset selection based on multiple genetic diversity measures using Mixed Replica search.

Herman De Beukelaer1, Petr Smýkal, Guy F Davenport

  • 1Department of Applied Mathematics and Computer Science, Faculty of Sciences, Ghent University, Krijgslaan 281, S9, 9000 Gent, Belgium. herman.debeukelaer@ugent.be

BMC Bioinformatics
|November 24, 2012
PubMed
Summary

Gene banks can improve genetic diversity sampling with Core Hunter II. The new Mixed Replica algorithm enhances core set diversity and reduces computation time compared to older methods.

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07:35

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances

Published on: October 11, 2018

Area of Science:

  • Genetics
  • Bioinformatics
  • Computational Biology

Background:

  • Gene bank managers face challenges in creating representative core subsets from large genetic resources.
  • The Core Hunter program aids in generating these subsets using genetic distance and diversity measures.
  • Investigating alternative distance measures and algorithms is crucial for optimizing core set creation.

Purpose of the Study:

  • To evaluate the impact of minimum distance measures versus mean distance measures in Core Hunter.
  • To compare the performance of the original Core Hunter algorithm (REMC) with other heuristics.
  • To introduce and assess a new algorithm, Mixed Replica search (MixRep), for improved core set generation.

Main Methods:

  • Core Hunter program utilizing distance and diversity indices.
  • Comparison of Replica Exchange Monte Carlo (REMC) with simpler heuristic algorithms.
  • Implementation and testing of the novel Mixed Replica search (MixRep) algorithm.

Main Results:

  • Minimum distance measures ensure greater genetic distance between selected accessions.
  • Simpler heuristics offer faster computation but may yield suboptimal diversity, especially with minimum distance measures.
  • Mixed Replica search (MixRep) achieved comparable or superior diversity with reduced computation time compared to REMC and other heuristics.

Conclusions:

  • The original REMC algorithm performs well but can be surpassed by simpler methods in speed.
  • The Mixed Replica algorithm offers significant improvements in both diversity and efficiency.
  • Minimum distance measures are recommended for objective functions when maximizing genetic distance is key.