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Discovering functional relationships between RNA expression and chemotherapeutic susceptibility using relevance networks

Discovering functional relationships between RNA expression and chemotherapeutic susceptibility using relevance networks,10.1073/pnas.220392197,Procee

Discovering functional relationships between RNA expression and chemotherapeutic susceptibility using relevance networks   (Citations: 226)
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In an effort to find gene regulatory networks and clusters of genes that affect cancer susceptibility to anticancer agents, we joined a database with baseline expression levels of 7,245 genes measured by using microarrays in 60 cancer cell lines, to a database with the amounts of 5,084 anticancer agents needed to inhibit growth of those same cell lines. Comprehensive pair-wise correlations were calculated between gene expression and measures of agent sus-ceptibility. Associations weaker than a threshold strength were removed, leaving networks of highly correlated genes and agents called relevance networks. Hypotheses for potential single-gene determinants of anticancer agent susceptibility were constructed. The effect of random chance in the large number of calculations performed was empirically determined by repeated random per-mutation testing; only associations stronger than those seen in multiply permuted data were used in clustering. We discuss the advantages of this methodology over alternative approaches, such as phylogenetic-type tree clustering and self-organizing maps.
Journal: Proceedings of The National Academy of Sciences - PNAS , vol. 97, no. 22, pp. 12182-12186, 2000
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