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Sanger Sequencing01:57

Sanger Sequencing

DNA sequencing is a fundamental technique that is routinely used in the biological sciences. This method can be applied to a range of questions at different scales - from the sequencing of a cloned DNA fragment or the study of a mutation in a gene up to whole-genome sequencing. However, despite the widespread use of sequencing today, it was not until 1977 that Fredrick Sanger and his collaborators developed the chain-termination method to decode DNA sequences. It relies on the separation of a...
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...
Maxam-Gilbert Sequencing01:05

Maxam-Gilbert Sequencing

In the same year as the discovery of the Sanger sequencing method, another group of scientists, Allan Maxam and Walter Gilbert, demonstrated their chemical-cleavage method for DNA sequencing. The Maxam-Gilbert method relies on using different chemicals that can cleave the DNA sequence at specific sites, the separation of resulting DNA fragments of variable size using electrophoresis, and deciphering the DNA sequence from the resulting gel bands.
Challenges of the Maxam-Gilbert Method
The...
DNA Isolation01:24

DNA Isolation

DNA isolation protocols can be fast and straightforward or complex and time-consuming depending on the type and quality of DNA required for further processing. For example, plasmid DNA extraction is a bit more complicated than genomic DNA extraction because of the need for an appropriate lysis method to separate plasmid DNA from gDNA during isolation. However, for specific applications, such as long-range DNA sequencing that require a good yield of high- quality DNA samples, we need to follow...
Next-generation Sequencing03:00

Next-generation Sequencing

The first human genome sequencing project cost $2.7 billion and was declared complete in 2003, after 15 years of international cooperation and collaboration between several research teams and funding agencies. Today, with the advent of next-generation sequencing technologies, the cost and time of sequencing a human genome have dropped over 100 fold.
Next-Generation Sequencing Methods
Although all next-generation methods use different technologies, they all share a set of standard features.
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...

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Related Experiment Video

Updated: Jun 2, 2026

Pattern-based Search of Epigenomic Data Using GeNemo
06:38

Pattern-based Search of Epigenomic Data Using GeNemo

Published on: October 8, 2017

Searching a pattern in compressed DNA sequences.

Ashutosh Gupta1, Suneeta Agarwal

  • 1Department of Computer Science and Information Technology, I.E.T, MJP Rohilkhand University, Bareilly 243006, India. ashutosh333@rediffmail.com

International Journal of Bioinformatics Research and Applications
|May 18, 2011
PubMed
Summary
This summary is machine-generated.

This study presents a new DNA sequence compression algorithm using a transformation and statistical analysis. The method efficiently compresses DNA data and enables pattern searching for knowledge discovery, outperforming existing methods.

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Area of Science:

  • Bioinformatics
  • Computational Biology
  • Data Compression

Background:

  • DNA sequences are large and require efficient compression.
  • Existing compression methods may not fully leverage the statistical properties of DNA data.
  • Pattern discovery within compressed DNA data is crucial for biological insights.

Purpose of the Study:

  • Introduce a novel algorithm for DNA sequence compression.
  • Utilize sequence transformation and statistical properties for enhanced compression.
  • Enable pattern searching within compressed DNA for knowledge discovery.

Main Methods:

  • A transformation is applied to the DNA sequence.
  • Statistical properties of the transformed sequence are analyzed.
  • A word-based tagged code, utilizing frequency distribution, is employed for encoding.

Main Results:

  • The algorithm demonstrates efficient and effective DNA sequence compression.
  • Experimental results show superior performance compared to existing compressors on DNA datasets.
  • The statistical compression approach facilitates pattern searching within the compressed data.

Conclusions:

  • The novel algorithm offers a significant advancement in DNA sequence compression.
  • The method's ability to support pattern discovery enhances its utility in bioinformatics.
  • This approach provides a valuable tool for managing and analyzing large-scale genomic data.