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Behavioral Phenotyping of Murine Disease Models with the Integrated Behavioral Station (INBEST)
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Model organism databases in behavioral neuroscience.

Mary Shimoyama1, Jennifer R Smith, G Thomas Hayman

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International Review of Neurobiology
|December 1, 2012
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Summary
This summary is machine-generated.

Model Organism Databases (MODs) provide curated genetic, genomic, and phenotype data for researchers. These essential informatics tools ensure data integrity and support biological research through comprehensive datasets and analysis tools.

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Area of Science:

  • Bioinformatics
  • Genomics
  • Computational Biology

Background:

  • Model Organism Databases (MODs) are crucial informatics resources for life science research.
  • They offer organism-specific genetic, genomic, and phenotype data.
  • MODs play a vital role in data standardization and accessibility.

Purpose of the Study:

  • To highlight the importance and functionalities of Model Organism Databases.
  • To emphasize the role of MODs in data curation and integration.
  • To showcase the utility of MODs in advancing biological research.

Main Methods:

  • Data curation from scientific literature.
  • Integration of genetic, genomic, and phenotype information.
  • Development and provision of data access and analysis software tools.

Main Results:

  • MODs provide comprehensive, curated datasets for various model organisms.
  • Official nomenclature for genes, QTLs, and strains is maintained.
  • Data from MODs are integrated into larger genomic databases and publications.

Conclusions:

  • MODs are indispensable tools for researchers, ensuring data accuracy and integrity.
  • They facilitate data discovery, analysis, and interpretation.
  • MODs significantly contribute to the advancement of biological and biomedical research.