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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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Genome-wide Association Studies-GWAS01:11

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Genome-wide association studies or GWAS are used to identify whether common SNPs are associated with certain diseases. Suppose specific SNPs are more frequently observed in individuals with a particular disease than those without the disease. In that case, those SNPs are said to be associated with the disease. Chi-square analysis is performed to check the probability of the allele likely to be associated with the disease.
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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.
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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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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.
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An undergraduate genome research course using "big data".

Evan N Bennett1, Shallee T Page1

  • 1College of Health and Natural Sciences, Franklin Pierce University, Rindge, New Hampshire, USA.

Biochemistry and Molecular Biology Education : a Bimonthly Publication of the International Union of Biochemistry and Molecular Biology
|July 9, 2022
PubMed
Summary

This course teaches advanced undergraduates how to analyze large biological datasets, focusing on genomic data analysis and programming in R. It equips students with essential bioinformatics skills for modern scientific research.

Keywords:
bioinformaticscourse-based (CUREs)curriculum design development and implementationgenome researchundergraduate researchundergraduate researchbig data

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Area of Science:

  • Bioinformatics
  • Genomics
  • Biochemistry

Background:

  • Modern science increasingly requires analysis of large datasets, particularly in biochemistry due to expanding biological databases.
  • Genomic data analysis is a critical skill for advanced science undergraduates.

Purpose of the Study:

  • To present a modular bioinformatics course for advanced undergraduates focused on genomic data analysis.
  • To provide hands-on research activities including genome scanning and sequence annotation.
  • To explore programming in R for biological data analysis.

Main Methods:

  • A modular course structure was developed for advanced undergraduate students.
  • Research activities included genome scanning for endogenous retroviruses and genomic sequence annotation.
  • Students were introduced to programming in R for data analysis.
  • A poster session was used for work dissemination.

Main Results:

  • The course successfully surveyed genomic data analysis techniques.
  • Students engaged in practical bioinformatics research activities.
  • The course design is suitable for remote or online instruction.

Conclusions:

  • The presented bioinformatics course effectively trains advanced undergraduates in essential genomic data analysis skills.
  • The modular and adaptable course structure supports diverse learning environments, including online delivery.
  • This curriculum addresses the growing need for big data analysis expertise in scientific research.