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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.
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.
Genomics02:02

Genomics

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...
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...
RACE - Rapid Amplification of cDNA Ends02:35

RACE - Rapid Amplification of cDNA Ends

Rapid Amplification of cDNA Ends, or RACE, is one of the most effective methods to obtain a full-length cDNA from an mRNA sequence between a known internal region to the unknown sequence at the 5’ or 3’ end. The unknown region is cloned in the cDNA by a gene-specific primer that binds the known end, and a hybrid primer that attaches a predefined anchor sequence to the unknown end of the cDNA. The sequence in between is amplified by PCR with an anchor primer and a gene-specific primer.
Since the...

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Related Experiment Video

Updated: May 15, 2026

Novel Sequence Discovery by Subtractive Genomics
09:40

Novel Sequence Discovery by Subtractive Genomics

Published on: January 25, 2019

A de novo next generation genomic sequence assembler based on string graph and MapReduce cloud computing framework.

Yu-Jung Chang1, Chien-Chih Chen, Chuen-Liang Chen

  • 1Institute of Information Science, Academia Sinica, Taipei, Taiwan, ROC.

BMC Genomics
|January 4, 2013
PubMed
Summary
This summary is machine-generated.

CloudBrush, a novel distributed genome assembler, addresses challenges in de novo genome assembly from high-throughput sequencing data. It improves assembly quality with an edge-adjustment algorithm, achieving high precision and recall.

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Collection and Extraction of Saliva DNA for Next Generation Sequencing
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Collection and Extraction of Saliva DNA for Next Generation Sequencing

Published on: August 27, 2014

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Last Updated: May 15, 2026

Novel Sequence Discovery by Subtractive Genomics
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Published on: January 25, 2019

Hybrid De Novo Genome Assembly for the Generation of Complete Genomes of Urinary Bacteria using Short- and Long-read Sequencing Technologies
12:08

Hybrid De Novo Genome Assembly for the Generation of Complete Genomes of Urinary Bacteria using Short- and Long-read Sequencing Technologies

Published on: August 20, 2021

Collection and Extraction of Saliva DNA for Next Generation Sequencing
06:58

Collection and Extraction of Saliva DNA for Next Generation Sequencing

Published on: August 27, 2014

Area of Science:

  • Genomics
  • Bioinformatics
  • Computational Biology

Background:

  • High-throughput sequencers generate large datasets (up to 600 Gbp) with longer reads.
  • De novo genome assembly faces challenges with memory limitations and structural defects in graph-theoretical models.
  • Existing assembly algorithms struggle to manage data structures and graph defects from modern sequencing technologies.

Purpose of the Study:

  • To develop a distributed genome assembler capable of handling large datasets from high-throughput sequencing.
  • To address memory constraints and structural defects inherent in de novo genome assembly.
  • To improve the accuracy and reliability of genome assemblies.

Main Methods:

  • Developed CloudBrush, a distributed genome assembler utilizing string graphs and the MapReduce framework.
  • Implemented a novel edge-adjustment algorithm to detect and correct structural defects in the string graph by examining neighboring reads.
  • Evaluated CloudBrush using GAGE benchmarks and simulated datasets, assessing assembly quality metrics like N50, misassembly rates, precision, and recall.

Main Results:

  • CloudBrush demonstrates a moderate N50 and low rates of misjoins and indels (> 5 bp).
  • The assembler achieves high precision and recall in contig alignment compared to other benchmarked tools.
  • The edge-adjustment algorithm's effectiveness was verified on simulated data and a nematode dataset.

Conclusions:

  • CloudBrush offers an effective solution for de novo genome assembly using high-throughput sequencing data.
  • The novel edge-adjustment algorithm enhances assembly accuracy by managing structural defects.
  • CloudBrush provides a scalable and accurate approach for genomic data analysis, available via GitHub.