From ambiguities to insights: Query-based comparisons of high-dimensional data

Jeanne Kowalski, Conover Talbot, Hua L. Tsai, Nijaguna Prasad, Christopher Umbricht, Martha A. Zeiger

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Genomic technologies will revolutionize drug discovery and development; that much is universally agreed upon. The high dimension of data from such technologies has challenged available data analytic methods; that much is apparent. To date, large-scale data repositories have not been utilized in ways that permit their wealth of information to be efficiently processed for knowledge, presumably due in large part to inadequate analytical tools to address numerous comparisons of high-dimensional data. In candidate gene discovery, expression comparisons are often made between two features (e.g., cancerous versus normal), such that the enumeration of outcomes is manageable. With multiple features, the setting becomes more complex, in terms of comparing expression levels of tens of thousands transcripts across hundreds of features. In this case, the number of outcomes, while enumerable, become rapidly large and unmanageable, and scientific inquiries become more abstract, such as "which one of these (compounds, stimuli, etc.) is not like the others?" We develop analytical tools that promote more extensive, efficient, and rigorous utilization of the public data resources generated by the massive support of genomic studies. Our work innovates by enabling access to such metadata with logically formulated scientific inquires that define, compare and integrate query-comparison pair relations for analysis. We demonstrate our computational tool's potential to address an outstanding biomedical informatics issue of identifying reliable molecular markers in thyroid cancer. Our proposed query-based comparison (QBC) facilitates access to and efficient utilization of metadata through logically formed inquires expressed as query-based comparisons by organizing and comparing results from biotechnologies to address applications in biomedicine.

Original languageEnglish (US)
Title of host publicationComputational Models For Life Sciences (CMLS '07) - 2007 International Symposium
Pages305-314
Number of pages10
DOIs
StatePublished - Dec 1 2007
Event2007 International Symposium on Computational Models for Life Sciences, CMLS '07 - Gold Coast, QLD, Australia
Duration: Dec 17 2007Dec 19 2007

Publication series

NameAIP Conference Proceedings
Volume952
ISSN (Print)0094-243X
ISSN (Electronic)1551-7616

Other

Other2007 International Symposium on Computational Models for Life Sciences, CMLS '07
CountryAustralia
CityGold Coast, QLD
Period12/17/0712/19/07

Keywords

  • Gene expression
  • Query
  • Thyroid cancer

ASJC Scopus subject areas

  • Physics and Astronomy(all)

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    Kowalski, J., Talbot, C., Tsai, H. L., Prasad, N., Umbricht, C., & Zeiger, M. A. (2007). From ambiguities to insights: Query-based comparisons of high-dimensional data. In Computational Models For Life Sciences (CMLS '07) - 2007 International Symposium (pp. 305-314). (AIP Conference Proceedings; Vol. 952). https://doi.org/10.1063/1.2816635