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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...
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...
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%...
Genome Annotation and Assembly03:36

Genome Annotation and Assembly

The genome refers to all of the genetic material in an organism. It can range from a few million base pairs in microbial cells to several billion base pairs in many eukaryotic organisms. Genome assembly refers to the process of taking the DNA sequencing data and putting it all back together in a correct order to create a close representation of the original genome. This is followed by the identification of functional elements on the newly assembled genome, a process called genome annotation.
DNA Microarrays02:34

DNA Microarrays

Microarrays are high-throughput and relatively inexpensive assays that can be automated to analyze large quantities of data at a time. They are used in genome-wide studies to compare gene or protein expression under two varied conditions, such as healthy and diseased states. Microarrays consist of glass or silica slides on which probe molecules are covalently attached through surface functionalization. Most commonly, the slides are prepared through the chemisorption of silanes to silica...

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An Integrated Approach for Microprotein Identification and Sequence Analysis
09:37

An Integrated Approach for Microprotein Identification and Sequence Analysis

Published on: July 12, 2022

A comparative analysis of soft computing techniques for gene prediction.

Neelam Goel1, Shailendra Singh, Trilok Chand Aseri

  • 1Department of Computer Science and Engineering, PEC University of Technology, Sector-12, Chandigarh 160 012, UT, India. neelam.goyal85@gmail.com

Analytical Biochemistry
|March 27, 2013
PubMed
Summary
This summary is machine-generated.

Analyzing genomic sequences for gene prediction is crucial for biology and medicine. This review explores soft computing techniques for accurate gene identification in eukaryotes.

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Area of Science:

  • Genomics and Bioinformatics
  • Computational Biology
  • Molecular Biology

Background:

  • Genomic sequence data is rapidly expanding for diverse species.
  • Accurate gene prediction is vital for biological research and human health.
  • Existing gene prediction methods for eukaryotes have limitations.

Purpose of the Study:

  • To review and analyze soft computing techniques for gene prediction.
  • To describe the challenges inherent in gene prediction.
  • To provide a comparative analysis of different soft computing approaches.

Main Methods:

  • Review of literature on soft computing applications in gene prediction.
  • Description of various soft computing methodologies.
  • Comparative analysis of technique performance and applicability.

Main Results:

  • Soft computing techniques offer promising solutions for gene prediction challenges.
  • Specific soft computing methods demonstrate varying degrees of effectiveness.
  • The review highlights the strengths and weaknesses of different approaches.

Conclusions:

  • Soft computing techniques are valuable tools for eukaryotic gene prediction.
  • Further research is needed to overcome current limitations.
  • Future directions include refining existing methods and exploring novel approaches.