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Related Concept Videos

Next-generation Sequencing03:00

Next-generation Sequencing

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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
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Maxam-Gilbert Sequencing01:05

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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.
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Sanger Sequencing01:57

Sanger Sequencing

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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...
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Evolutionary Relationships through Genome Comparisons02:54

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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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RNA-seq03:21

RNA-seq

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RNA sequencing, or RNA-Seq, is a high-throughput sequencing technology used to study the transcriptome of a cell. Transcriptomics helps to interpret the functional elements of a genome and identify the molecular constituents of an organism. Additionally, it also helps in understanding the development of an organism and the occurrence of diseases. 
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Genomics02:02

Genomics

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Genomics is the science of genomes: it is the study of all the genetic material of an organism. In humans, the genome consists of information carried in 23 pairs of chromosomes in the nucleus, as well as mitochondrial DNA. In genomics, both coding and non-coding DNA is sequenced and analyzed. Genomics allows a better understanding of all living things, their evolution, and their diversity. It has a myriad of uses: for example, to build phylogenetic trees, to improve productivity and...
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Updated: Mar 26, 2026

G2-seq: A High Throughput Sequencing-based Technique for Identifying Late Replicating Regions of the Genome
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G2-seq: A High Throughput Sequencing-based Technique for Identifying Late Replicating Regions of the Genome

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Advances in high throughput DNA sequence data compression.

Muhammad Sardaraz1, Muhammad Tahir1, Ataul Aziz Ikram2

  • 11 Department of Computer Science, University of Wah, Quaid Avenue, Wah Cantt 47040, Pakistan.

Journal of Bioinformatics and Computational Biology
|February 6, 2016
PubMed
Summary
This summary is machine-generated.

High-throughput DNA sequencing generates massive data, posing storage and transmission challenges. This review covers genome and reads compression methods, categorizing algorithms and analyzing their performance to address these challenges.

Keywords:
Genome compressionread compressionreference free compressionreferential compression

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Area of Science:

  • Bioinformatics
  • Computational Biology
  • Genomics

Background:

  • High-throughput sequencing technologies have led to an exponential increase in DNA sequence data.
  • The massive volume of sequencing data presents significant challenges in storage, retrieval, and transmission.

Purpose of the Study:

  • To provide a comprehensive review of data compression methods for genome and reads.
  • To categorize compression algorithms and present experimental results and comparative analyses.

Main Methods:

  • Algorithms are categorized into referential and reference-free methods.
  • Experimental results and comparative analyses of various compression techniques are presented.

Main Results:

  • A comparative analysis of different DNA sequence data compression methods is provided.
  • The effectiveness of referential and reference-free algorithms is evaluated.

Conclusions:

  • Data compression is crucial for managing the challenges of large-scale DNA sequencing data.
  • Key challenges and future research directions in DNA sequence data compression are highlighted.