This article reviews the comparison of protein abundance and mRNA expression levels on a genomic scale, focusing on yeast. It discusses experimental techniques for determining protein abundance, such as two-dimensional gel electrophoresis and mass spectrometry, and merges available yeast protein-abundance datasets to find correlations between protein and mRNA expression. The authors note that while there has been recent progress in developing tools for measuring both mRNA and protein expression, these measurements are complementary and both are necessary for understanding cellular function. They also highlight that mRNA is translated into protein, so there should be some correlation between the two, although this may not always be the case. The article compares two high-throughput methods for measuring mRNA expression: microarrays and Affymetrix chips. It also discusses two methods for determining protein abundance: two-dimensional electrophoresis and mass spectrometry. The authors provide a brief review of these technologies and recent efforts to determine correlations between quantified protein abundances and mRNA expression. The article discusses various methods for determining protein levels, including two-dimensional electrophoresis, mass spectrometry, and isotope-coded affinity-tag-based protein profiling. It also discusses multidimensional protein identification technology (MudPit) and its use in analyzing protein abundance. The article compares mRNA and protein levels and finds that while mRNA expression values have shown usefulness in various applications, they are likely only correlative, not causative. The authors suggest that protein abundance and their interactions are the true causative forces in the cell. They also note that there are limited correlations between mRNA and protein expression levels, with some studies showing minimal or limited correlations. The article discusses protein and mRNA correlations in yeast, noting that many efforts have been conducted using two-dimensional electrophoresis techniques. It also discusses a new merged dataset that combines data from two-dimensional electrophoresis and MudPit datasets. The authors find that some localization categories, such as the nucleolus, have significantly higher correlations than the global correlation. Other localizations, such as the mitochondria, may present less correlation between mRNA and protein data. The article also discusses reasons for the absence of correlation between mRNA and protein levels, including complex post-transcriptional mechanisms, differences in protein half-lives, and significant error and noise in both experiments. It also discusses the codon adaptation index (CAI) and its potential to predict gene expression. The authors conclude that while there are some correlations between mRNA and protein levels, the degree of natural and manufactured systematic noise in these experiments is a major limitation. They suggest that more comprehensive correlation studies will soon be feasible with advances in technology, and that a better understanding of the dynamic processes involved in protein synthesis and degradation is needed to fully understand the relationship between mRNA and protein abundances.This article reviews the comparison of protein abundance and mRNA expression levels on a genomic scale, focusing on yeast. It discusses experimental techniques for determining protein abundance, such as two-dimensional gel electrophoresis and mass spectrometry, and merges available yeast protein-abundance datasets to find correlations between protein and mRNA expression. The authors note that while there has been recent progress in developing tools for measuring both mRNA and protein expression, these measurements are complementary and both are necessary for understanding cellular function. They also highlight that mRNA is translated into protein, so there should be some correlation between the two, although this may not always be the case. The article compares two high-throughput methods for measuring mRNA expression: microarrays and Affymetrix chips. It also discusses two methods for determining protein abundance: two-dimensional electrophoresis and mass spectrometry. The authors provide a brief review of these technologies and recent efforts to determine correlations between quantified protein abundances and mRNA expression. The article discusses various methods for determining protein levels, including two-dimensional electrophoresis, mass spectrometry, and isotope-coded affinity-tag-based protein profiling. It also discusses multidimensional protein identification technology (MudPit) and its use in analyzing protein abundance. The article compares mRNA and protein levels and finds that while mRNA expression values have shown usefulness in various applications, they are likely only correlative, not causative. The authors suggest that protein abundance and their interactions are the true causative forces in the cell. They also note that there are limited correlations between mRNA and protein expression levels, with some studies showing minimal or limited correlations. The article discusses protein and mRNA correlations in yeast, noting that many efforts have been conducted using two-dimensional electrophoresis techniques. It also discusses a new merged dataset that combines data from two-dimensional electrophoresis and MudPit datasets. The authors find that some localization categories, such as the nucleolus, have significantly higher correlations than the global correlation. Other localizations, such as the mitochondria, may present less correlation between mRNA and protein data. The article also discusses reasons for the absence of correlation between mRNA and protein levels, including complex post-transcriptional mechanisms, differences in protein half-lives, and significant error and noise in both experiments. It also discusses the codon adaptation index (CAI) and its potential to predict gene expression. The authors conclude that while there are some correlations between mRNA and protein levels, the degree of natural and manufactured systematic noise in these experiments is a major limitation. They suggest that more comprehensive correlation studies will soon be feasible with advances in technology, and that a better understanding of the dynamic processes involved in protein synthesis and degradation is needed to fully understand the relationship between mRNA and protein abundances.