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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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Maxam-Gilbert Sequencing01:05

Maxam-Gilbert Sequencing

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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.
Challenges of the Maxam-Gilbert Method
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Evolutionary Relationships through Genome Comparisons02:54

Evolutionary Relationships through Genome Comparisons

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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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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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DNA Isolation01:24

DNA Isolation

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DNA isolation protocols can be fast and straightforward or complex and time-consuming depending on the type and quality of DNA required for further processing. For example, plasmid DNA extraction is a bit more complicated than genomic DNA extraction because of the need for an appropriate lysis method to separate plasmid DNA from gDNA during isolation. However, for specific applications, such as long-range DNA sequencing that require a good yield of high- quality DNA samples, we need to follow...
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Updated: May 5, 2026

G2-seq: A High Throughput Sequencing-based Technique for Identifying Late Replicating Regions of the Genome
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G2-seq: A High Throughput Sequencing-based Technique for Identifying Late Replicating Regions of the Genome

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High-throughput DNA sequence data compression.

Zexuan Zhu, Yongpeng Zhang, Zhen Ji

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    |December 5, 2013
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    Summary
    This summary is machine-generated.

    Genomic data compression is vital for managing large datasets. This review categorizes existing methods and explores future research directions for efficient genomic data analysis.

    Keywords:
    compressionnext-generation sequencingreference-based compressionreference-free compression

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    Area of Science:

    • Genomics
    • Bioinformatics
    • Data Science

    Background:

    • High-throughput DNA sequencing generates massive data, challenging storage, retrieval, and transmission.
    • Existing compression methods primarily focus on reducing storage size for genomic data (e.g., genomes, reads, quality scores).
    • The rapid generation of genomic data outpaces meaningful analysis, highlighting the need for compression that aids analysis.

    Purpose of the Study:

    • To categorize and comprehensively review existing compression methods for genomic data.
    • To present experimental results evaluating compression ratio, memory usage, and compression/decompression times.
    • To identify current challenges and propose future research directions in genomic data compression.

    Main Methods:

    • Systematic literature review of genomic data compression techniques.
    • Categorization of compression methods based on their approaches and applications.
    • Experimental evaluation of selected compression algorithms using key performance metrics.

    Main Results:

    • A comprehensive categorization of specialized genomic data compression methods.
    • Comparative experimental results on compression ratio, memory usage, and processing time.
    • Identification of trade-offs between different compression algorithms.

    Conclusions:

    • Effective genomic data compression is crucial for efficient data management and analysis.
    • Novel compression algorithms are needed to directly support genomic data analysis beyond storage and transmission.
    • Future research should focus on developing advanced compression techniques to address the growing challenges in genomics.