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Video Bioinformatics Analysis of Human Embryonic Stem Cell Colony Growth
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Datalog Extensions for Bioinformatic Data Analysis.

Jiwon Seo

    Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
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    Summary
    This summary is machine-generated.

    B-Log is a new query language that simplifies genomic and proteomic data analysis for nonexpert programmers. It enables quick exploratory analyses of large bioinformatic datasets.

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    Area of Science:

    • Bioinformatics
    • Computational Biology
    • Genomics

    Background:

    • Public bioinformatic databases are growing, enabling genomic and proteomic data analysis.
    • Large datasets pose challenges for nonexpert programmers.
    • Efficient tools are needed for exploratory data analysis.

    Purpose of the Study:

    • Introduce B-Log, a high-level query language for bioinformatic data analysis.
    • Simplify complex data analysis for nonexpert users.
    • Facilitate quick exploratory analyses and prototyping.

    Main Methods:

    • Developed B-Log, a Datalog-based query language.
    • Extended B-Log with nested tables, recursive aggregations, and foreign functions.
    • Implemented analysis algorithms and a prototype system for the TCGA dataset.

    Main Results:

    • B-Log effectively expresses graph analysis algorithms.
    • The language supports nested tables and recursive aggregations for complex queries.
    • A prototype system demonstrated B-Log's utility on the TCGA dataset.

    Conclusions:

    • B-Log is a valuable tool for exploratory bioinformatic data analysis.
    • The language facilitates rapid prototyping of analysis algorithms.
    • B-Log enhances accessibility to large-scale genomic and proteomic data.