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Related Concept Videos

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.
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...
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...
RNA-seq03:21

RNA-seq

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. 
Before the discovery of RNA-seq, microarray-based methods and Sanger sequencing were used for transcriptome analysis. However, while microarray-based...

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Related Experiment Video

Updated: May 9, 2026

Next-generation Sequencing of 16S Ribosomal RNA Gene Amplicons
10:24

Next-generation Sequencing of 16S Ribosomal RNA Gene Amplicons

Published on: August 29, 2014

Compressing resequencing data with GReEn.

Armando J Pinho1, Diogo Pratas, Sara P Garcia

  • 1IEETA/DETI, University of Aveiro, Aveiro, Portugal.

Methods in Molecular Biology (Clifton, N.J.)
|July 23, 2013
PubMed
Summary
This summary is machine-generated.

Genome sequencing generates vast amounts of data. GReEn (Genome Resequencing Encoding) is a new compression tool designed to efficiently compress genome resequencing data using a reference genome sequence.

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Last Updated: May 9, 2026

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Published on: August 29, 2014

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Published on: January 13, 2017

Area of Science:

  • Genomics
  • Bioinformatics
  • Computational Biology

Background:

  • Genome sequencing centers are producing unprecedented volumes of data.
  • The data output of a single modern sequencing machine surpasses the entire yearly output from 2005.
  • There is a critical need for advanced data compression algorithms in genomics.

Purpose of the Study:

  • To introduce and describe GReEn (Genome Resequencing Encoding).
  • To address the challenge of compressing large-scale genome resequencing data.
  • To provide an efficient solution for managing the growing volume of genomic data.

Main Methods:

  • Development of a novel compression tool named GReEn.
  • Utilizing a reference genome sequence as a basis for compression.
  • Application of the GReEn tool to genome resequencing data.

Main Results:

  • GReEn is a proposed compression tool for genome resequencing data.
  • The tool leverages reference genome sequences for compression.
  • It aims to alleviate the pressure caused by massive sequencing data generation.

Conclusions:

  • GReEn offers a potential solution for efficient genome resequencing data compression.
  • The tool is designed to manage the increasing data output from genome sequencing.
  • Efficient compression is crucial for the scientific community dealing with large genomic datasets.