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Related Concept Videos

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...
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.

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Related Experiment Video

Updated: May 19, 2026

Integration of Wet and Dry Bench Processes Optimizes Targeted Next-generation Sequencing of Low-quality and Low-quantity Tumor Biopsies
13:24

Integration of Wet and Dry Bench Processes Optimizes Targeted Next-generation Sequencing of Low-quality and Low-quantity Tumor Biopsies

Published on: April 11, 2016

Next-Generation Sequencing Dataset Downloader and In Silico Sequence Mining: Graphical-User-Interface-Based Tools for

Min Chan Kim1, Hye Ji Jung1, Min Chang Kang1

  • 1Department of Biological Sciences and Biotechnology, College of Natural Sciences, Chungbuk National University, Cheongju, Republic of Korea.

Computational and Structural Biotechnology Journal
|May 18, 2026
PubMed
Summary
This summary is machine-generated.

In Silico Sequence Mining (ISSM) offers rapid, probe-based screening of raw sequencing data, improving clinical bioinformatics efficiency. This tool accelerates triage and prioritization for downstream analyses, benefiting researchers with limited bioinformatics expertise.

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Last Updated: May 19, 2026

Integration of Wet and Dry Bench Processes Optimizes Targeted Next-generation Sequencing of Low-quality and Low-quantity Tumor Biopsies
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Integration of Wet and Dry Bench Processes Optimizes Targeted Next-generation Sequencing of Low-quality and Low-quantity Tumor Biopsies

Published on: April 11, 2016

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

Published on: April 4, 2018

Targeted DNA Methylation Analysis by Next-generation Sequencing
08:38

Targeted DNA Methylation Analysis by Next-generation Sequencing

Published on: February 24, 2015

Area of Science:

  • Bioinformatics
  • Genomics
  • Clinical Diagnostics

Background:

  • Next-generation sequencing (NGS) clinical applications are growing.
  • Current pipelines often delay critical decisions until after full data alignment and taxonomic analysis.
  • This delay can impact resource allocation and timely clinical insights.

Purpose of the Study:

  • To introduce In Silico Sequence Mining (ISSM), a user-friendly, graphical tool for rapid pre-alignment screening of raw sequencing data.
  • To enable probe-based target identification directly from FASTQ/FASTA files.
  • To enhance the efficiency of clinical bioinformatics workflows.

Main Methods:

  • ISSM employs probe-based matching on raw sequencing files (FASTQ/FASTA).
  • The workflow supports configurable match thresholds and data subsampling.
  • Performance was evaluated using diverse datasets including coronavirus, feline coronavirus (FCoV), HIV, and colorectal cancer samples.

Main Results:

  • ISSM accurately identified coronavirus targets using public panels, with a 95% threshold enhancing sensitivity.
  • The tool detected FCoV and HIV in relevant samples with minimal spurious matches.
  • ISSM facilitated preliminary KRAS mutation screening in cancer datasets and HIV subtyping.

Conclusions:

  • ISSM provides rapid post-sequencing triage and prioritizes confirmatory analyses.
  • It optimizes resource allocation for bioinformatics and downstream testing (e.g., qPCR, targeted sequencing).
  • ISSM offers an accessible solution for researchers and clinicians with limited bioinformatics expertise.