Knowledge-based assessment of gene expression data from chemiluminescence detection

J Biotechnol. 2002 Mar 14;94(1):23-35. doi: 10.1016/s0168-1656(01)00417-5.

Abstract

The first problem in gene expression profiling to be solved is choosing the appropriate gene array, detection procedure, image analysis and data generation depending on the organism of interest, equipment and budget. The next one is how to deduce biologically meaningful data. We assessed gene expression data from chemiluminescent detection and empirically found criteria for the reliable identification of biologically meaningful expression ratios. Current statistical assessments are often applied unreflectedly concerning problems occurring in practice. So interesting results are considered to be irrelevant. This requires a laborious data check. We suggest automation. Our empirically found criteria were transformed into and validated by a knowledge-based system. This system is adaptable to all other methods of expression profiling. We compared the experience-based and new knowledge-based assessment of the expression data from our chemiluminescent and additionally radioactive detection of several experiments with published data to evaluate our entire procedure. With our adaptation of chemiluminescence detection to commercially available Escherichia coli gene arrays we present a useful alternative to common procedures in gene expression monitoring. Moreover, with our consideration of plasmid-harbouring E. coli strains we provide the opportunity to monitor gene expression during processes requiring any plasmids (e.g. recombinant protein expression).

Publication types

  • Comparative Study

MeSH terms

  • Artificial Intelligence*
  • Biotechnology
  • Escherichia coli / genetics
  • False Negative Reactions
  • False Positive Reactions
  • Gene Expression Profiling / statistics & numerical data*
  • Genes, Bacterial
  • Luminescent Measurements
  • Plasmids / genetics