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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
Although all next-generation methods use different technologies, they all share a set of standard features....
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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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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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Statistical Software for Data Analysis and Clinical Trials01:12

Statistical Software for Data Analysis and Clinical Trials

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Statistical software is pivotal in data analysis and clinical trials by providing tools to analyze data, draw conclusions, and make predictions. These software packages range from simple data management applications to complex analytical platforms, supporting various statistical tests, models, and simulation techniques. Their significance lies in their ability to handle vast amounts of data with precision and efficiency, enabling researchers to validate hypotheses, identify trends, and make...
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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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Related Experiment Video

Updated: Aug 21, 2025

Targeted Next-generation Sequencing and Bioinformatics Pipeline to Evaluate Genetic Determinants of Constitutional Disease
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A Clinician's Guide to Bioinformatics for Next-Generation Sequencing.

Nicholas Bradley Larson1, Ann L Oberg2, Alex A Adjei3

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Journal of Thoracic Oncology : Official Publication of the International Association for the Study of Lung Cancer
|November 15, 2022
PubMed
Summary

Next-generation sequencing (NGS) provides high-throughput DNA sequencing for cancer research. This review covers NGS technology, bioinformatics, and applications, focusing on DNA-based methods for clinical care.

Keywords:
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Area of Science:

  • Genomics
  • Bioinformatics
  • Cancer Research

Background:

  • Next-generation sequencing (NGS) is a high-throughput DNA sequencing technology widely used in cancer research.
  • The extensive data from NGS requires advanced computational methods and bioinformatics expertise.

Purpose of the Study:

  • To provide background on NGS technology and bioinformatics for cancer researchers.
  • To focus on DNA-based NGS approaches and their applications in cancer research.

Main Methods:

  • Review of NGS principles, including library preparation, sequencing, alignment, and variant calling.
  • Discussion of variant annotations and applications for diverse molecular data types.

Main Results:

  • Introduction to fundamental NGS workflow steps.
  • Highlighting common variant annotations and broader NGS applications.

Conclusions:

  • NGS methods are valuable in non-small cell lung cancer (NSCLC) research.
  • Considerations for designing NGS studies for clinical care integration are discussed.