TY - GEN
T1 - From ambiguities to insights
T2 - 2007 International Symposium on Computational Models for Life Sciences, CMLS '07
AU - Kowalski, Jeanne
AU - Talbot, Conover
AU - Tsai, Hua L.
AU - Prasad, Nijaguna
AU - Umbricht, Christopher
AU - Zeiger, Martha A.
PY - 2007
Y1 - 2007
N2 - 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.
AB - 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.
KW - Gene expression
KW - Query
KW - Thyroid cancer
UR - http://www.scopus.com/inward/record.url?scp=71449121238&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=71449121238&partnerID=8YFLogxK
U2 - 10.1063/1.2816635
DO - 10.1063/1.2816635
M3 - Conference contribution
AN - SCOPUS:71449121238
SN - 9780735404663
T3 - AIP Conference Proceedings
SP - 305
EP - 314
BT - Computational Models For Life Sciences (CMLS '07) - 2007 International Symposium
Y2 - 17 December 2007 through 19 December 2007
ER -