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      RodentSQL: a software suite for colony management of animal protocols

      brief-report
      * , 1 , 2 , 3
      Future Science OA
      Future Science Ltd
      colony management, recordkeeping, rodent, SQL database, transgenic

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          Abstract

          Aim:

          Animal experiments tend to generate large-scale data. Some existing tools like Microsoft Excel and colony management cloud-based tools are either cumbersome or expensive. There is a need for an inexpensive and uncomplicated colony management software with specific individual database solutions.

          Methods:

          We have developed a database application named RodentSQL to meet most of the requirements of such animal colony management programs.

          Results:

          We present a user-friendly secure system for managing records of phenotype, genotype and metadata for comprehensive data analysis and mining. RodentSQL can be altered based upon user needs. We have successfully tested its usage in beta users for managing data of hamsters and mice.

          Conclusion:

          A central facility can share and benefit from this colony management system. RodentSQL can increase workflow efficiency and data security leading to significant cost savings and enhanced scientific results. RodentSQL is offered to the scientific community as an open source software.

          Lay abstract

          Animal experiments tend to generate large-scale data. Some existing tools like Microsoft ® Excel (WA, USA) and colony management cloud-based tools are either cumbersome or expensive. Addressing this concern, we have developed a database application named RodentSQL to meet most of the requirements of such animal colony management programs, which can lead to significant cost savings and enhanced scientific results.

          Most cited references8

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          Behavioral and functional analysis of mouse phenotype: SHIRPA, a proposed protocol for comprehensive phenotype assessment

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            Behavioral and functional analysis of mouse phenotype: SHIRPA, a proposed protocol for comprehensive phenotype assessment.

            For an understanding of the aberrant biology seen in mouse mutations and identification of more subtle phenotype variation, there is a need for a full clinical and pathological characterization of the animals. Although there has been some use of sophisticated techniques, the majority of behavioral and functional analyses in mice have been qualitative rather than quantitative in nature. There is, however, no comprehensive routine screening and testing protocol designed to identify and characterize phenotype variation or disorders associated with the mouse genome. We have developed the SHIRPA procedure to characterize the phenotype of mice in three stages. The primary screen utilizes standard methods to provide a behavioral and functional profile by observational assessment. The secondary screen involves a comprehensive behavioral assessment battery and pathological analysis. These protocols provide the framework for a general phenotype assessment that is suitable for a wide range of applications, including the characterization of spontaneous and induced mutants, the analysis of transgenic and gene-targeted phenotypes, and the definition of variation between strains. The tertiary screening stage described is tailored to the assessment of existing or potential models of neurological disease, as well as the assessment of phenotypic variability that may be the result of unknown genetic influences. SHIRPA utilizes standardized protocols for behavioral and functional assessment that provide a sensitive measure for quantifying phenotype expression in the mouse. These paradigms can be refined to test the function of specific neural pathways, which will, in turn, contribute to a greater understanding of neurological disorders.
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              Recommendations for the health monitoring of rodent and rabbit colonies in breeding and experimental units.

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                Author and article information

                Journal
                Future Sci OA
                Future Sci OA
                FSOA
                Future Science OA
                Future Science Ltd (London, UK )
                2056-5623
                September 2018
                27 July 2018
                : 4
                : 9
                : FSO330
                Affiliations
                [1 ]Department of Computer Science, Georgia State University, 34 Peachtree Street, Atlanta, GA, 30303, USA
                [2 ]Department of Biology, Georgia State University, 34 Peachtree Street, Atlanta, GA, 30303, USA
                [3 ]Neuroscience Institute & Center for Behavioral Neuroscience, Georgia State University, 789 Petit Science Center Atlanta, GA, 30303, USA
                Author notes
                *Author for correspondence: Tel.: +1 404 431 0213; spawar2@ 123456student.gsu.edu
                Article
                10.4155/fsoa-2018-0054
                6153456
                21452771-6d35-481f-933b-7a19bc3af3bb
                © 2018 Shrikant Pawar

                This work is licensed under a Creative Commons Attribution 4.0 License

                History
                : 15 May 2018
                : 05 June 2018
                : 27 July 2018
                Categories
                Short Communication

                colony management,recordkeeping,rodent,sql database,transgenic

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