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Filtering Microarray Correlations by Statistical Literature Analysis Yields Potential Hypotheses for Lactation Research (0901.0213v1)

Published 2 Jan 2009 in cs.DL and cs.DB

Abstract: Our results demonstrated that a previously reported protein name co-occurrence method (5-mention PubGene) which was not based on a hypothesis testing framework, it is generally statistically more significant than the 99th percentile of Poisson distribution-based method of calculating co-occurrence. It agrees with previous methods using natural language processing to extract protein-protein interaction from text as more than 96% of the interactions found by natural language processing methods to overlap with the results from 5-mention PubGene method. However, less than 2% of the gene co-expressions analyzed by microarray were found from direct co-occurrence or interaction information extraction from the literature. At the same time, combining microarray and literature analyses, we derive a novel set of 7 potential functional protein-protein interactions that had not been previously described in the literature.

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Authors (3)
  1. Maurice HT Ling (17 papers)
  2. Christophe Lefevre (6 papers)
  3. Kevin R. Nicholas (3 papers)
Citations (3)

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