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Related Concept Videos

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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Evolutionary Relationships through Genome Comparisons02:54

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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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Modern Molecular Taxonomy01:29

Modern Molecular Taxonomy

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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...
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Genome Size and the Evolution of New Genes03:21

Genome Size and the Evolution of New Genes

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While every living organism has a genome of some kind (be it RNA, or DNA), there is considerable variation in the sizes of these blueprints. One major factor that impacts genome size is whether the organism is prokaryotic or eukaryotic. In prokaryotes, the genome contains little to no non-coding sequence, such that genes are tightly clustered in groups or operons sequentially along the chromosome. Conversely, the genes in eukaryotes are punctuated by long stretches of non-coding sequence.
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Genome Size and the Evolution of New Genes03:21

Genome Size and the Evolution of New Genes

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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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Related Experiment Video

Updated: Mar 27, 2026

Integration of Bioinformatics Approaches and Experimental Validations to Understand the Role of Notch Signaling in Ovarian Cancer
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Bioinformatics: Novel Insights from Genomic Information.

Robert E W Hancock

    Nestle Nutrition Institute Workshop Series
    |January 15, 2016
    PubMed
    Summary

    Computational tools are essential for analyzing large genome-wide datasets in biology. These tools help uncover novel patterns and generate new hypotheses in areas like infection and immunity.

    Area of Science:

    • Bioinformatics and Computational Biology
    • Genomics and Systems Biology
    • Infection and Immunity Research

    Background:

    • Traditional scientific methods struggle with the complexity of biological systems.
    • There is a growing need for unbiased research using large-scale, genome-wide data.
    • Analyzing complex biological data requires advanced computational tools.

    Purpose of the Study:

    • To describe novel computational tools for analyzing genome-wide biological data.
    • To illustrate the application of these tools in infection and innate immunity research.
    • To demonstrate how data analysis can generate new hypotheses and insights.

    Main Methods:

    • Development of computational tools for data collation and analysis.
    • Utilizing databases for biomolecular interaction information.

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  • Employing supervised (pathway analysis, gene ontology) and unsupervised (clustering, network analysis) methods.

    • Main Results:

    • The developed tools facilitate the extraction of novel patterns from complex datasets.
    • Analysis revealed new hypotheses regarding disease mechanisms and immunomodulatory interventions.
    • Identified potential for mechanism-based biomarkers and drug repurposing.

    Conclusions:

    • Computational tools are crucial for advancing biological research, particularly in complex fields like immunity.
    • Unbiased, data-driven approaches enable the generation of testable hypotheses and novel insights.
    • These methods support the development of new diagnostics and therapeutic strategies.