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Related Concept Videos

Evolutionary Relationships through Genome Comparisons02:54

Evolutionary Relationships through Genome Comparisons

Genome comparison is one of the excellent ways to interpret the evolutionary relationships between organisms. The basic principle of genome comparison is that if two species share a common feature, it is likely encoded by the DNA sequence conserved between both species. The advent of genome sequencing technologies in the late 20th century enabled scientists to understand the concept of conservation of domains between species and helped them to deduce evolutionary relationships across diverse...
Comparing Copy Number Variations and SNPs02:26

Comparing Copy Number Variations and SNPs

Sequencing of the human genome has opened up several best-kept secrets of the genome. Scientists have identified thousands of genome variations that exist within a population. These variations can be a single nucleotide or a larger chromosomal variation.
Copy number variations or CNVs are the structural variations that cover more than 1kb of DNA sequence. The single nucleotide polymorphism (SNP), on the other hand, is a single nucleotide change or a point mutation that is found in more than 1%...
Comparing Mitochondrial, Chloroplast, and Prokaryotic Genomes02:16

Comparing Mitochondrial, Chloroplast, and Prokaryotic Genomes

The present-day mitochondrial and chloroplast genomes have retained some of the characteristics of their ancestral prokaryotes and also have acquired new attributes during their evolution within eukaryotic cells. Like prokaryotic genomes, mitochondrial and chloroplast genomes neither bind with histone-like proteins nor show complex packaging into chromosome-like structures, as observed in eukaryotes. Unlike mitotic cell divisions observed in eukaryotic cells, mitochondria and chloroplasts...
Gene Duplication and Divergence02:37

Gene Duplication and Divergence

The seminal work of Ohno in 1970 popularized the idea of gene duplication and divergence. DNA sequence comparison studies reveal that a large portion of the genes in bacteria, archaebacteria, and eukaryotes was  generated by gene duplication and divergence, indicating its critical role in evolution.
The duplicated copies of the gene are called Paralogs. Paralogs with similar sequences and functions form a gene family. Across several species, a large number of gene families are characterized.
Gene Evolution - Fast or Slow?02:05

Gene Evolution - Fast or Slow?

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.
In contrast, regions which code...

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A Novel Bayesian Change-point Algorithm for Genome-wide Analysis of Diverse ChIPseq Data Types
12:39

A Novel Bayesian Change-point Algorithm for Genome-wide Analysis of Diverse ChIPseq Data Types

Published on: December 10, 2012

Efficiently identifying max-gap clusters in pairwise genome comparison.

Xu Ling1, Xin He, Dong Xin

  • 1Department of Computer Science, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, USA. xuling@uiuc.edu

Journal of Computational Biology : a Journal of Computational Molecular Cell Biology
|July 18, 2008
PubMed
Summary
This summary is machine-generated.

We developed a highly efficient algorithm for computing max-gap clusters in comparative genomics. This method significantly speeds up the identification of gene structures like operons and homologous regions across species.

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Competitive Genomic Screens of Barcoded Yeast Libraries
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Published on: August 11, 2011

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A Novel Bayesian Change-point Algorithm for Genome-wide Analysis of Diverse ChIPseq Data Types
12:39

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Published on: December 10, 2012

Competitive Genomic Screens of Barcoded Yeast Libraries
11:59

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Published on: August 11, 2011

Area of Science:

  • Genomics
  • Bioinformatics
  • Computational Biology

Background:

  • Spatial gene clustering is crucial for comparative genomics, aiding in operon identification and homologous region detection.
  • Previous methods often relied on heuristics, lacking rigorous statistical validation.
  • Formal models like max-gap clusters offer completeness and statistical significance.

Purpose of the Study:

  • To develop a highly efficient algorithm for computing max-gap clusters in pairwise genome comparisons.
  • To improve upon existing algorithms for identifying conserved gene clusters.
  • To demonstrate the utility of max-gap clusters in both bacterial and mammalian genome analysis.

Main Methods:

  • Developed a novel, efficient algorithm for calculating max-gap clusters.
  • Applied the algorithm to pairwise genome comparisons.
  • Evaluated performance against previous algorithms and biological datasets.

Main Results:

  • The new algorithm is an order-of-magnitude faster than prior methods.
  • Successfully identified known operons and novel gene structures in bacterial genomes.
  • Demonstrated the detection of homologous regions between human and mouse genomes.

Conclusions:

  • The efficient max-gap cluster algorithm enhances comparative genomics analysis.
  • This approach provides a robust framework for identifying conserved gene clusters.
  • The method is applicable to diverse organisms, from bacteria to mammals.