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Related Concept Videos

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.
Evolutionary Relationships through Genome Comparisons02:54

Evolutionary Relationships through Genome Comparisons

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...
Genome Annotation and Assembly03:36

Genome Annotation and Assembly

The genome refers to all of the genetic material in an organism. It can range from a few million base pairs in microbial cells to several billion base pairs in many eukaryotic organisms. Genome assembly refers to the process of taking the DNA sequencing data and putting it all back together in a correct order to create a close representation of the original genome. This is followed by the identification of functional elements on the newly assembled genome, a process called genome annotation.
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...
Modern Molecular Taxonomy01:29

Modern Molecular Taxonomy

Advancements in molecular biology have revolutionized the identification and characterization of bacteria, with multiple methods leveraging DNA sequencing for enhanced precision. As sequencing technologies improve and costs decline, these approaches are increasingly used in clinical, environmental, and evolutionary studies.Multilocus Sequence Typing (MLST) examines several housekeeping genes, essential chromosomal genes encoding cellular functions, to distinguish strains. Approximately...
Genomics02:02

Genomics

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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Collection and Extraction of Saliva DNA for Next Generation Sequencing
06:58

Collection and Extraction of Saliva DNA for Next Generation Sequencing

Published on: August 27, 2014

Bioinformatics tools and databases for analysis of next-generation sequence data.

Hong C Lee, Kaitao Lai, Michal Tadeusz Lorenc

    Briefings in Functional Genomics
    |December 21, 2011
    PubMed
    Summary
    This summary is machine-generated.

    Next-generation sequencing generates massive data, posing analysis challenges. This review highlights key bioinformatics tools and databases essential for interpreting this genomic information effectively.

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    Area of Science:

    • Genomics
    • Bioinformatics
    • Computational Biology

    Background:

    • Next-generation sequencing (NGS) technologies have dramatically increased the volume and reduced the cost of genome sequencing.
    • The exponential growth in sequencing data presents a significant challenge for data analysis and biological interpretation.
    • The field of bioinformatics has rapidly developed to address these challenges.

    Purpose of the Study:

    • To provide an overview of commonly utilized bioinformatics tools and databases for analyzing next-generation sequencing data.
    • To comment on the utility and applicability of these resources in the context of large-scale genomic data analysis.

    Main Methods:

    • Literature review of established and emerging bioinformatics software.
    • Survey of prominent biological databases relevant to next-generation sequence data.
    • Qualitative assessment of tool and database utility based on common analytical workflows.

    Main Results:

    • Identification of a range of software tools for sequence alignment, variant calling, and data visualization.
    • Discussion of key databases for genomic annotation, functional analysis, and data storage.
    • Commentary on the strengths and limitations of selected tools and databases for specific research questions.

    Conclusions:

    • Effective analysis of next-generation sequencing data relies on a curated selection of bioinformatics tools and databases.
    • Continuous evolution of bioinformatics resources is crucial to keep pace with advancements in sequencing technology.
    • Understanding the utility of different bioinformatics resources empowers researchers to extract meaningful biological insights from large-scale genomic datasets.