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Related Concept Videos

Genomics02:02

Genomics

37.3K
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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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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Using large databases to study cancer genomics in an undergraduate classroom.

Patricia G Melloy1, Brian Chiswell2, Celeste Peterson3

  • 1Department of Biological Sciences, Fairleigh Dickinson University, Madison, New Jersey, USA.

Biochemistry and Molecular Biology Education : a Bimonthly Publication of the International Union of Biochemistry and Molecular Biology
|July 21, 2022
PubMed
Summary

Students explore cancer databases to analyze driver mutations and patient data. This lab experience examines gene expression, tumor suppressors, oncogenes, and actionable mutations impacting cancer survival.

Keywords:
cancer genomicsclinical outcomesdata miningglobal genetic makeup

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Area of Science:

  • Oncology
  • Bioinformatics
  • Genetics

Background:

  • Cancer databases offer valuable resources for global analysis of patient data and original studies.
  • Educational curricula often lack hands-on experience with these powerful cancer research databases.
  • Understanding driver mutations is crucial for cancer research and personalized medicine.

Purpose of the Study:

  • To develop a laboratory module enabling students to explore original cancer study databases.
  • To investigate the expression and incidence of cancer driver mutations using real-world data.
  • To enhance student understanding of genetic alterations in cancer and their clinical implications.

Main Methods:

  • Students analyze specific patient demographic data and cancer types.
  • mRNA expression levels associated with gene mutations are examined.
  • Determination of whether mutations act as tumor suppressors or oncogenes.
  • Identification of actionable mutations and their correlation with patient survival.

Main Results:

  • Students gain experience in analyzing large-scale cancer genomic and clinical datasets.
  • The module facilitates understanding of global trends in cancer driver mutations.
  • Students learn to differentiate between tumor suppressors and oncogenes based on expression data.
  • Actionable mutations and their prognostic significance are explored.

Conclusions:

  • This lab module provides a practical approach to learning about cancer genomics.
  • It empowers students to analyze driver mutations and patient-specific features from global databases.
  • The experience bridges the gap between theoretical knowledge and practical application in cancer research.