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Related Concept Videos

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Measurement is an indispensable part of analytical chemistry. The result of measurement helps quantify a substance's physical property and compare it with the physical property of another substance. Each measurement comprises two components - a number indicating the magnitude and a unit of measurement as a standard for comparison. Further, the same quantity can be measured using different units of measurement, which leads to differences in magnitude.
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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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The ITS2 Database
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Mouse Genome Database (MGD) 2019.

Carol J Bult1, Judith A Blake1, Cynthia L Smith1

  • 1The Jackson Laboratory, 600 Main Street, Bar Harbor, ME 04609, USA.

Nucleic Acids Research
|November 9, 2018
PubMed
Summary
This summary is machine-generated.

The Mouse Genome Database (MGD) now offers enhanced tools for researchers studying mouse genetics and disease models. New features include genome viewers and phenotype-gene expression comparisons for better data exploration.

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Area of Science:

  • Genomics
  • Bioinformatics
  • Mammalian Genetics

Background:

  • The Mouse Genome Database (MGD) is a key resource for mouse genetics and genomics.
  • It provides authoritative data on mouse genes, phenotypes, and models of human disease.
  • MGD also manages official nomenclature for mouse genes, alleles, and strains.

Purpose of the Study:

  • To report significant enhancements to the Mouse Genome Database.
  • To introduce new graphical user interfaces for improved data exploration.
  • To detail updates in data integration and curation processes.

Main Methods:

  • Development of the Multi Genome Viewer for comparative strain analysis.
  • Creation of the Phenotype-Gene Expression matrix in collaboration with GXD.
  • Improvements in literature curation efficiency and integration of FANTOM 5 TSS annotations.

Main Results:

  • Introduction of two novel graphical user interfaces: Multi Genome Viewer and Phenotype-Gene Expression matrix.
  • Enhanced efficiency in literature curation processes.
  • Integration of Transcriptional Start Site (TSS) annotations from the FANTOM 5 initiative.

Conclusions:

  • The recent MGD enhancements provide researchers with advanced tools for exploring mouse genomic and phenotypic data.
  • New interfaces facilitate comparative genomics and integrated analysis of gene expression and phenotypes.
  • These updates improve MGD's utility as a central resource for the mouse research community.