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Related Concept Videos

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...
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...
Genome Size and the Evolution of New Genes03:21

Genome Size and the Evolution of New Genes

While every living organism has a genome of some kind (be it RNA, or DNA), there is considerable variation in the sizes of these blueprints. One major factor that impacts genome size is whether the organism is prokaryotic or eukaryotic. In prokaryotes, the genome contains little to no non-coding sequence, such that genes are tightly clustered in groups or operons sequentially along the chromosome. Conversely, the genes in eukaryotes are punctuated by long stretches of non-coding sequence.
Genome Size and the Evolution of New Genes03:21

Genome Size and the Evolution of New Genes

While every living organism has a genome of some kind (be it RNA, or DNA), there is considerable variation in the sizes of these blueprints. One major factor that impacts genome size is whether the organism is prokaryotic or eukaryotic. In prokaryotes, the genome contains little to no non-coding sequence, such that genes are tightly clustered in groups or operons sequentially along the chromosome. Conversely, the genes in eukaryotes are punctuated by long stretches of non-coding sequence.
Exon Recombination02:32

Exon Recombination

The evolution of new genes is critical for speciation. Exon recombination, also known as exon shuffling or domain shuffling, is an important means of new gene formation. It is observed across vertebrates, invertebrates, and in some plants such as potatoes and sunflowers. During exon recombination, exons from the same or different genes recombine and produce new exon-intron combinations, which might evolve into new genes. 
Exon shuffling follows “splice frame rules.” Each exon has three reading...
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...

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Related Experiment Video

Updated: May 25, 2026

Comprehensive Workflow for the Genome-wide Identification and Expression Meta-analysis of the ATL E3 Ubiquitin Ligase Gene Family in Grapevine
10:40

Comprehensive Workflow for the Genome-wide Identification and Expression Meta-analysis of the ATL E3 Ubiquitin Ligase Gene Family in Grapevine

Published on: December 22, 2017

A new efficient algorithm for the gene-team problem on general sequences.

Biing-Feng Wang1, Chung-Chin Kuo, Shang-Ju Liu

  • 1Department of Computer Science, National Tsing Hua University, Hsinchu, Taiwan, Republic of China. bfwang@cs.nthu.edu.tw

IEEE/ACM Transactions on Computational Biology and Bioinformatics
|January 28, 2012
PubMed
Summary
This summary is machine-generated.

A new algorithm efficiently identifies gene teams in genomic sequences, improving upon existing methods. This advancement aids in understanding genome evolution and predicting gene functions more effectively.

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Novel Sequence Discovery by Subtractive Genomics
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Novel Sequence Discovery by Subtractive Genomics
09:40

Novel Sequence Discovery by Subtractive Genomics

Published on: January 25, 2019

Area of Science:

  • Genomics
  • Bioinformatics
  • Computational Biology

Background:

  • Conserved gene clusters are crucial for understanding genome evolution and gene function prediction.
  • The gene-team model is a key framework for analyzing these clusters.
  • Previous algorithms for finding gene teams in two sequences had limitations in efficiency.

Purpose of the Study:

  • To develop a more efficient algorithm for identifying gene teams in general sequences.
  • To improve upon the time complexity of existing gene-team finding algorithms.
  • To extend the method for analyzing multiple gene sequences.

Main Methods:

  • Introduced a novel algorithm with a time complexity of O(min{C lg n, mn}) and O(m + n) working space.
  • The algorithm's performance is dependent on C, a measure of gene copy numbers across sequences.
  • Developed an output-sensitive approach with running time proportional to O(lg n) times the output size.

Main Results:

  • The new algorithm offers a practical improvement over the O(mn) time complexity of prior methods.
  • The algorithm is significantly faster when the value of C is substantially smaller than mn.
  • Successfully extended the algorithm for efficient analysis of k general sequences.

Conclusions:

  • The presented algorithm provides a more efficient and practical solution for identifying gene teams.
  • This advancement has implications for comparative genomics and functional genomics research.
  • The scalability to k sequences enhances its utility for complex genomic studies.