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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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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.
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Cancer survival analysis focuses on quantifying and interpreting the time from a key starting point, such as diagnosis or the initiation of treatment, to a specific endpoint, such as remission or death. This analysis provides critical insights into treatment effectiveness and factors that influence patient outcomes, helping to shape clinical decisions and guide prognostic evaluations. A cornerstone of oncology research, survival analysis tackles the challenges of skewed, non-normally...
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Mice have long served as models for studying human biology and pathology because of their phylogenetic and physiological similarity with humans. They are also easy to maintain and breed in the laboratory, and hence, many inbred strains are now available for research. Studies on mice have contributed immeasurably to our understanding of cancer biology.
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Microarrays are high-throughput and relatively inexpensive assays that can be automated to analyze large quantities of data at a time. They are used in genome-wide studies to compare gene or protein expression under two varied conditions, such as healthy and diseased states. Microarrays consist of glass or silica slides on which probe molecules are covalently attached through surface functionalization. Most commonly, the slides are prepared through the chemisorption of silanes to silica...
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Related Experiment Video

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Performing Data Mining And Integrative Analysis Of Biomarker in Breast Cancer Using Multiple Publicly Accessible Databases
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OncoDB 2.0: a comprehensive platform for integrated pan-cancer omics analysis.

Minsu Cho1,2, Gongyu Tang1, Charles S Rogers1

  • 1Department of Pharmacology and Regenerative Medicine, University of Illinois at Chicago, Chicago, IL 60612, United States.

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OncoDB 2.0 enhances cancer research by integrating multi-omics data, including somatic mutations and proteomic profiles. This expanded platform aids in exploring complex cancer biology and identifying novel therapeutic targets.

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Area of Science:

  • Genomics
  • Proteomics
  • Cancer Biology

Background:

  • The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx) datasets provide valuable multi-omics data for cancer research.
  • Previous versions of OncoDB integrated RNA expression, DNA methylation, and clinical data.
  • A comprehensive, integrated platform is needed to explore complex cancer omics data.

Purpose of the Study:

  • To present OncoDB 2.0, an expanded platform for integrated cancer multi-omics analysis.
  • To incorporate somatic mutation, proteomic, and chromatin accessibility data.
  • To provide advanced analysis modules for exploring cross-omic relationships.

Main Methods:

  • Integrated RNA sequencing, DNA sequencing, and DNA methylation data.
  • Incorporated proteomic data from the Clinical Proteomic Tumor Analysis Consortium (CPTAC).
  • Added chromatin accessibility data from TCGA.
  • Developed advanced multi-omics analysis modules.

Main Results:

  • OncoDB 2.0 provides an atlas of somatic mutations across tumor types.
  • The platform enables investigation of mutation patterns and clinical feature associations.
  • New dimensions for oncogene regulation studies are offered through integrated proteomic and chromatin accessibility data.
  • Advanced modules facilitate combined exploration of RNA expression, DNA methylation, and somatic mutations.

Conclusions:

  • OncoDB 2.0 offers a comprehensive and integrated view of cancer omics data.
  • The platform facilitates in-depth investigation of mutation patterns and their clinical relevance.
  • OncoDB 2.0 is a robust tool for cancer research, enabling deeper exploration of cross-omic relationships.
  • The platform is freely available to the research community.