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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.
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...
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...
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.
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...

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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

Now and next-generation sequencing techniques: future of sequence analysis using cloud computing.

Radhe Shyam Thakur1, Rajib Bandopadhyay, Bratati Chaudhary

  • 1Department of Biotechnology, Birla Institute of Technology Mesra, Ranchi, India.

Frontiers in Genetics
|December 19, 2012
PubMed
Summary
This summary is machine-generated.

Cloud computing offers a solution to the massive data challenges in genomics. It provides scalable, pay-as-you-go resources for complex sequence analysis and database management.

Keywords:
DNA cloudcloud computingnext-generation sequencing

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Last Updated: May 15, 2026

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Targeted Next-generation Sequencing and Bioinformatics Pipeline to Evaluate Genetic Determinants of Constitutional Disease

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Area of Science:

  • Bioinformatics
  • Computational Biology
  • Genomics

Background:

  • Sequencing technologies generate vast datasets, overwhelming traditional computing resources.
  • Database maintenance, data mining, and sequence analysis pose significant computational challenges.

Purpose of the Study:

  • To introduce cloud computing as a solution for large-scale biological data analysis.
  • To analyze the fundamentals, prerequisites, and operational aspects of cloud computing.
  • To discuss the applications of cloud computing in comparative genomics, genome informatics, and SNP detection.

Main Methods:

  • Exploration of cloud computing principles and architecture.
  • Analysis of resource virtualization and pay-as-you-go models.
  • Review of cloud applications in biological data analysis workflows.

Main Results:

  • Cloud computing provides scalable and efficient solutions for handling large sequence datasets.
  • It shifts computational workload and infrastructure management to cloud providers.
  • Virtual environments are created on-demand for specific computational tasks.

Conclusions:

  • Cloud computing effectively addresses the computational and storage demands of modern genomics.
  • It offers a flexible and cost-effective alternative to traditional standalone computing for biological research.
  • Applications in comparative genomics, genome informatics, and SNP detection demonstrate its utility.