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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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Maxam-Gilbert Sequencing01:05

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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.
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Updated: Apr 20, 2026

Targeted Next-generation Sequencing and Bioinformatics Pipeline to Evaluate Genetic Determinants of Constitutional Disease
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SMITH: a LIMS for handling next-generation sequencing workflows.

Francesco Venco, Yuriy Vaskin, Arnaud Ceol

    BMC Bioinformatics
    |December 5, 2014
    PubMed
    Summary
    This summary is machine-generated.

    SMITH, a new tool for Next Generation Sequencing (NGS) data, automates workflows and standardizes data management. This facilitates meta-analysis and improves efficiency in life-science laboratories.

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    Area of Science:

    • Genomics and Bioinformatics
    • Molecular Biology
    • Computational Biology

    Background:

    • Next Generation Sequencing (NGS) is increasingly used in life sciences, replacing older methods for gene expression and protein-DNA interaction studies.
    • Specialized facilities manage NGS requests, sample tracking, quality control, and data access.
    • Existing Laboratory Information Management Systems (LIMS) are often costly and lack flexibility for evolving protocols.

    Purpose of the Study:

    • To develop an integrated tool for managing Next Generation Sequencing (NGS) data flow.
    • To address the limitations of cost, flexibility, and scalability in current LIMS solutions.
    • To streamline operations at the Genomic Unit of the Italian Institute of Technology (IIT).

    Main Methods:

    • Developed SMITH (Sequencing Machine Information Tracking and Handling), a web application with a MySQL backend.
    • Designed a database schema to store comprehensive NGS experiment information, including protocols and algorithms.
    • Implemented an attribute-value table for flexible metadata creation, enabling database searching and statistical analysis.

    Main Results:

    • SMITH automates most processes, reducing direct human interaction to administrative tasks.
    • Standardized data-delivery procedures simplify data navigation for biologists and analysts.
    • Automated workflows, managed via an API, handle tasks like de-multiplexing, quality control, and alignments.

    Conclusions:

    • SMITH standardizes, automates, and accelerates sequencing workflows.
    • Key-value pair data annotation enhances meta-analysis capabilities.
    • The tool improves efficiency and data quality in NGS data management.