A METHOD AND SYSTEM FOR ANALYZING GENE EXPRESSION DATA USING A SMOOTH RESPONSE SURFACE ALGORITHM

A Smooth Response Surface (SRS) algorithm is provided as a more elaborate data mining technique for analyzing gene expression data, as well as computationally constructing a gene regulatory network. A three-dimensional smooth response surface is generated to capture the biological relationship betwe...

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Hauptverfasser:	XU, HONGQUAN, WANG, YIXIN, WU, PEIRU, WU, CHIEN-FU JEFF, TIDWELL, CARL
Format:	Patent
Sprache:	eng ; fre
Schlagworte:	APPARATUS FOR ENZYMOLOGY OR MICROBIOLOGY BEER BIOCHEMISTRY CALCULATING CHEMISTRY COMPOSITIONS OR TEST PAPERS THEREFOR COMPOSITIONS THEREOF COMPUTING CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL ORENZYMOLOGICAL PROCESSES COUNTING CULTURE MEDIA ELECTRIC DIGITAL DATA PROCESSING ENZYMOLOGY INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTEDFOR SPECIFIC APPLICATION FIELDS MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEICACIDS OR MICROORGANISMS METALLURGY MICROBIOLOGY MICROORGANISMS OR ENZYMES MUTATION OR GENETIC ENGINEERING PHYSICS PROCESSES OF PREPARING SUCH COMPOSITIONS PROPAGATING, PRESERVING OR MAINTAINING MICROORGANISMS SPIRITS VINEGAR WINE
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Beschreibung
Zusammenfassung:	A Smooth Response Surface (SRS) algorithm is provided as a more elaborate data mining technique for analyzing gene expression data, as well as computationally constructing a gene regulatory network. A three-dimensional smooth response surface is generated to capture the biological relationship between the target and activator-repressor. This novel technique is applied to functionally describe triplets of activators, repressors and targets, and their regulations in gene expression data. A diagnostic strategy is built into the SRS algorithm to evaluate the scores of the triplets so that those with low scores are kept and a regulatory network is constructed based on this information and existing biological knowledge. The predictions based on the identified triplets in two yeast expression data agree with experimental data in the literature. The invention provides a novel model with attractive mathematical and statistical features that make the algorithm valuable for mining expression or concentration information in gene expression analysis for determining the function of uncharacterized proteins, as well as for developing a more accurate understanding of coherent regulatory pathways.