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Related Concept Videos

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...
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...
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.
Sequences01:29

Sequences

Sequences are fundamental mathematical objects consisting of ordered lists of numbers that follow a specific rule or pattern. Sequences are critical in various mathematical concepts, including calculus, series, and number theory. They can model real-world phenomena such as population growth, financial investments, and physical processes like the diminishing height of a bouncing ball.Each number in a sequence is referred to as a term. Typically, the terms are denoted as a1, a2, a3,…, where the...
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...
Per-Unit Sequence Models01:26

Per-Unit Sequence Models

An ideal Y-Y transformer, grounded through neutral impedances, displays per-unit sequence networks akin to those of a single-phase ideal transformer when subjected to balanced positive- or negative-sequence currents. These currents do not produce neutral currents, and their associated voltage drops.
Zero-sequence currents, which are identical in magnitude and phase, generate a neutral current, resulting in voltage drops across the neutral impedance and the low-voltage winding. If the...

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Related Experiment Video

Updated: Jun 5, 2026

Detection of Rare Genomic Variants from Pooled Sequencing Using SPLINTER
14:06

Detection of Rare Genomic Variants from Pooled Sequencing Using SPLINTER

Published on: June 23, 2012

SeqWare Query Engine: storing and searching sequence data in the cloud.

Brian D O'Connor1, Barry Merriman, Stanley F Nelson

  • 1UNC Lineberger Comprehensive Cancer Center, University of North Carolina, Chapel Hill, NC 27599, USA.

BMC Bioinformatics
|January 8, 2011
PubMed
Summary
This summary is machine-generated.

The SeqWare Query Engine offers a scalable cloud-based solution for managing and querying vast amounts of genomic data, including variants and annotations. This open-source tool facilitates easier analysis for both technical and non-technical users in biomedical research.

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Novel Sequence Discovery by Subtractive Genomics
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Novel Sequence Discovery by Subtractive Genomics

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The ITS2 Database
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The ITS2 Database

Published on: March 12, 2012

Related Experiment Videos

Last Updated: Jun 5, 2026

Detection of Rare Genomic Variants from Pooled Sequencing Using SPLINTER
14:06

Detection of Rare Genomic Variants from Pooled Sequencing Using SPLINTER

Published on: June 23, 2012

Novel Sequence Discovery by Subtractive Genomics
09:40

Novel Sequence Discovery by Subtractive Genomics

Published on: January 25, 2019

The ITS2 Database
16:17

The ITS2 Database

Published on: March 12, 2012

Area of Science:

  • Genomics
  • Bioinformatics
  • Computational Biology

Background:

  • Next-generation sequencing (NGS) has led to a dramatic increase in human genome data generation.
  • Existing computational infrastructure, particularly databases and query interfaces, struggles to manage petascale datasets.
  • Cloud computing offers a scalable solution for handling the demands of large-scale genomic data.

Purpose of the Study:

  • To develop a scalable database and query interface for managing and analyzing large-scale genomic data.
  • To provide a user-friendly platform for accessing and querying variant information from thousands of genomes.
  • To integrate with existing bioinformatics tools and genome browsers for seamless data exploration.

Main Methods:

  • Developed the SeqWare Query Engine using cloud computing technologies.
  • Implemented a NoSQL HBase database for the backend, leveraging the Hadoop project.
  • Created a web-based frontend with programmatic and interactive query capabilities.
  • Integrated with popular genome browsers and bioinformatics tools.

Main Results:

  • The SeqWare Query Engine successfully supports databasing and querying of information from thousands of genomes.
  • Users can load and query variants (SNVs, indels, translocations) with rich annotations, including coverage and functional consequences.
  • Proof-of-concept demonstrated with datasets including the U87MG cell line and a glioblastoma tumor/normal pair.
  • Performance profiling using Hadoop MapReduce framework was conducted.

Conclusions:

  • The SeqWare Query Engine simplifies access to genomic data for diverse users, accelerating research and tool development.
  • Its support for various data types, ease of querying, and integration capabilities enhance data exploration.
  • The cloud-based architecture ensures robust scalability for managing ever-increasing genome sequence datasets.