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Towards Novel Nonparametric Statistical Methods and Bioinformatics Tools for Clinical and Translational Sciences

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  • Wittkowski, Knut M.

Abstract

As the field of functional genetics and genomics is beginning to mature, we become confronted with new challenges. The constant drop in price for sequencing and gene expression profiling as well as the increasing number of genetic and genomic variables that can be measured makes it feasible to address more complex questions. The success with rare diseases caused by single loci or genes has provided us with a proof-of-concept that new therapies can be developed based on functional genomics and genetics. Common diseases, however, typically involve genetic epistasis, genomic pathways, and proteomic pattern. Moreover, to better understand the underlying biologi-cal systems, we often need to integrate information from several of these sources. Thus, as the field of clinical research moves toward complex diseases, the demand for modern data base systems and advanced statistical methods increases. The traditional statistical methods implemented in most of the bioinformatics tools currently used in the novel field of genetics and functional genomics are based on the linear model and, thus, have shortcomings when applied to nonlinear biological systems. The previous work on partially ordered data (Wittkowski 1988; 1992), when combined with theoretical results (Hoeffding 1948) and computational strategies (Deuchler 1914) has opened a new field of nonparametric statistics. With grid technology, new tools are now feasible when screening for interactions between genetics (Wittkowski, Liu 2002) and functional genomics (Wittkowski, Lee 2004). Having more complex study designs and more specific methods available increases the demand for decision support when selecting appropriate bioinformatics tools. With the advent of rapid prototyping systems for Web based database application, we have recently begun to complement previous work on knowledge based systems with graphical Web-based tools for acquisition of DESIGN and MODEL knowledge.

Suggested Citation

  • Wittkowski, Knut M., 2005. "Towards Novel Nonparametric Statistical Methods and Bioinformatics Tools for Clinical and Translational Sciences," MPRA Paper 5902, University Library of Munich, Germany.
  • Handle: RePEc:pra:mprapa:5902
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    References listed on IDEAS

    as
    1. Wittkowski, Knut M., 2003. "Novel Methods for Multivariate Ordinal Data applied to Genetic Diplotypes, Genomic Pathways, Risk Profiles, and Pattern Similarity," MPRA Paper 4570, University Library of Munich, Germany.
    2. Susser, E. & Desvarieux, M. & Wittkowski, K.M., 1998. "Reporting sexual risk behavior for HIV: A practical risk index and a method for improving risk indices," American Journal of Public Health, American Public Health Association, vol. 88(4), pages 671-674.
    3. Fong D.Y.T. & Kwan C.W. & Lam K.F. & Lam K.S.L., 2003. "Use of the Sign Test for the Median in the Presence of Ties," The American Statistician, American Statistical Association, vol. 57, pages 237-240, November.
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    More about this item

    Keywords

    Biostatistics Bioinformatics NIH NCRR ROADMAP;

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • I1 - Health, Education, and Welfare - - Health

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