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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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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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DNA Microarrays02:34

DNA Microarrays

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Microarrays are high-throughput and relatively inexpensive assays that can be automated to analyze large quantities of data at a time. They are used in genome-wide studies to compare gene or protein expression under two varied conditions, such as healthy and diseased states. Microarrays consist of glass or silica slides on which probe molecules are covalently attached through surface functionalization. Most commonly, the slides are prepared through the chemisorption of silanes to silica...
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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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Updated: Jun 29, 2025

Integration of Wet and Dry Bench Processes Optimizes Targeted Next-generation Sequencing of Low-quality and Low-quantity Tumor Biopsies
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A cloud-based precision oncology framework for whole genome sequence analysis.

Saloni Tandon1, Medha Sharma1, Pratik Kasar1

  • 1Celebal Technologies Private Limited, 7th Floor Corporate tower, JLN Marg, Near Jawahar Circle, Malviya Nagar, Jaipur, Rajasthan 302017, India.

Computational Biology and Chemistry
|March 30, 2024
PubMed
Summary
This summary is machine-generated.

Precision oncology uses whole genome sequencing for rapid cancer analysis. This framework identifies targetable alterations for personalized cancer treatment and biomarker discovery.

Keywords:
AzureCancer detectionMSI analysisMicrosoft genomic servicesPrecision oncologyTMB analysisWhole genome analysis

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Area of Science:

  • Genomics
  • Oncology
  • Bioinformatics

Background:

  • Cancer poses a significant global health challenge with high mortality rates.
  • Early detection and precise treatment are crucial for improving patient outcomes.
  • Genomic analysis offers a pathway to personalized cancer therapies, minimizing side effects.

Purpose of the Study:

  • To develop a fast, robust, and efficient precision oncology framework.
  • To enable comprehensive genomic analysis from raw sequencing data to interpretation.
  • To facilitate molecular profiling of tumors for identifying targetable alterations.

Main Methods:

  • Whole genome sequencing (WGS) of individual DNA.
  • A computational framework processing FASTQ or BAM input files.
  • Quality assessment, variant annotation, functional prediction, and interpretation of genomic data.

Main Results:

  • The framework performs end-to-end genomic analysis.
  • It generates primary and detailed secondary reports, including variant details, TMB, and MSI.
  • Identifies molecular profiles of tumors, including targetable genetic alterations.

Conclusions:

  • The developed framework supports precision cancer treatment guidance.
  • It aids in the identification and validation of novel cancer biomarkers.
  • The platform is valuable for oncology research, development, and gene manipulation.