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  6. MuTrack: a genome analysis system for large-scale mutagenesis in the mouse
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MuTrack: a genome analysis system for large-scale mutagenesis in the mouse

Date Issued
February 3, 2004
Author(s)
Baker, Erich J.
Galloway, Leslie
Jackson, Barbara
Schmoyer, Denise
Snoddy, Jay
Permanent URI
https://trace.tennessee.edu/handle/20.500.14382/16997
Abstract

Abstract

Background


Modern biological research makes possible the comprehensive study and development of heritable mutations in the mouse model at high-throughput. Using techniques spanning genetics, molecular biology, histology, and behavioral science, researchers may examine, with varying degrees of granularity, numerous phenotypic aspects of mutant mouse strains directly pertinent to human disease states. Success of these and other genome-wide endeavors relies on a well-structured bioinformatics core that brings together investigators from widely dispersed institutions and enables them to seamlessly integrate data, observations and discussions.

Description

MuTrack was developed as the bioinformatics core for a large mouse phenotype screening effort. It is a comprehensive collection of on-line computational tools and tracks thousands of mutagenized mice from birth through senescence and death. It identifies the physical location of mice during an intensive phenotype screening process at several locations throughout the state of Tennessee and collects raw and processed experimental data from each domain. MuTrack's statistical package allows researchers to access a real-time analysis of mouse pedigrees for aberrant behavior, and subsequent recirculation and retesting. The end result is the classification of potential and actual heritable mutant mouse strains that become immediately available to outside researchers who have expressed interest in the mutant phenotype.

Conclusion

MuTrack demonstrates the effectiveness of using bioinformatics techniques in data collection, integration and analysis to identify unique result sets that are beyond the capacity of a solitary laboratory. By employing the research expertise of investigators at several institutions for a broad-ranging study, the TMGC has amplified the effectiveness of any one consortium member. The bioinformatics strategy presented here lends future collaborative efforts a template for a comprehensive approach to large-scale analysis.

Disciplines
Ecology and Evolutionary Biology
Recommended Citation
BMC Bioinformatics 2004, 5:11 doi:10.1186/1471-2105-5-11
Embargo Date
July 12, 2013
File(s)
Thumbnail Image
Name

1471_2105_5_11.pdf

Size

935.71 KB

Format

Adobe PDF

Checksum (MD5)

1b830e1a6dad89d224ef0092c474b62d

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