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Cancer-Critical Genes I: Proto-oncogenes01:33

Cancer-Critical Genes I: Proto-oncogenes

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Genes usually encode proteins necessary for the proper functioning of a healthy cell. Mutations can often cause changes to the gene expression pattern, thereby altering the phenotype.
When the function of certain critical genes, especially those involved in cell cycle regulation and cell growth signaling cascades, gets disrupted, it upsets the cell cycle progression. Such cells with unchecked cell cycles start proliferating uncontrollably and eventually develop into tumors.
Such genes that act...
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Cancer-Critical Genes I: Proto-oncogenes01:33

Cancer-Critical Genes I: Proto-oncogenes

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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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PI3K/mTOR/AKT Signaling Pathway01:22

PI3K/mTOR/AKT Signaling Pathway

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The mammalian target of rapamycin  (mTOR) is a serine/threonine kinase that regulates growth, proliferation, and cell survival in response to hormones, growth factors, or nutrient availability. This kinase exists in two structurally and functionally distinct forms: mTOR complex 1  (mTORC1) and mTOR complex 2  (mTORC2). The first form (mTORC1) is composed of a rapamycin-sensitive Raptor and proline-rich Akt substrate, PRAS40. In contrast,  mTORC2 consists of a...
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Cancer-Critical Genes II: Tumor Suppressor Genes01:05

Cancer-Critical Genes II: Tumor Suppressor Genes

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Cancer-Critical Genes II: Tumor Suppressor Genes01:05

Cancer-Critical Genes II: Tumor Suppressor Genes

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Genes usually encode proteins necessary for the proper functioning of a healthy cell. Mutations can often cause changes to the gene expression pattern, thereby altering the phenotype.
When the function of certain critical genes, especially those involved in cell cycle regulation and cell growth signaling cascades, gets disrupted, it upsets the cell cycle progression. Such cells with unchecked cell cycles start proliferating uncontrollably and eventually develop into tumors.
Such genes that act...
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Related Experiment Video

Updated: Mar 17, 2026

Integration of Bioinformatics Approaches and Experimental Validations to Understand the Role of Notch Signaling in Ovarian Cancer
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[Bioinformatics: a key role in oncology].

Timothée Olivier, Pierre Chappuis, Petros Tsantoulis

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    Bioinformatics integrates biology, computer science, and math to extract insights from complex clinical and biological data for improved cancer research and treatment. This field is crucial for advancing precision medicine and clinical decision-making.

    Area of Science:

    • Bioinformatics
    • Computational Biology
    • Oncology

    Context:

    • Clinical oncology and research heavily rely on bioinformatics for data analysis.
    • Bioinformatics integrates diverse data types, including poorly structured clinical and biological information.
    • Large-scale data analysis is a core component of modern bioinformatics applications.

    Purpose:

    • To derive actionable insights from extensive clinical and biological datasets.
    • To reclassify cancers based on molecular and biological characteristics for enhanced treatment selection.
    • To develop and validate molecular signatures for clinical practice.

    Summary:

    • Bioinformatics combines biology, computer science, and mathematics to analyze large-scale, often unstructured, clinical and biological data.

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  • It has led to cancer reclassification, improved treatment selection through validated molecular signatures, and holds potential for daily clinical practice enhancement.
  • Key applications include reducing errors and increasing precision in medical decision-making.
  • Impact:

    • Facilitates improved treatment selection and precision in oncology.
    • Enhances daily clinical practice by reducing errors and increasing decision-making accuracy.
    • Requires ethical evolution and multidisciplinary collaboration for continued advancement in healthcare.