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Proteins are responsible for performing the vast majority of cellular functions which are critical to a cell's survival. The knowledge of the subcellular localization of proteins can provide valuable information about their molecular functions. Therefore, one of the fundamental goals in cell biology and proteomics is to analyze the subcellular localizations and functions of these proteins. Recent large-scale human genomics and proteomics studies have made it possible to characterize human proteins at a subcellular localization level. In this study, according to the annotation in Swiss-Prot, 8842 human proteins were classified into seven subcellular localizations. Human proteins in the seven subcellular localizations were compared by using topological properties, biological properties, codon usage indices, mRNA expression levels, protein complexity and physicochemical properties. All these properties were found to be significantly different in the seven categories. In addition, based on these properties and pseudo-amino acid compositions, a machine learning classifier was built for the prediction of protein subcellular localization. The study presented here was an attempt to address the aforementioned properties for comparing human proteins of different subcellular localizations. We hope our findings presented in this study may provide important help for the prediction of protein subcellular localization and for understanding the general function of human proteins in cells. [ABSTRACT FROM AUTHOR]

Based on the requirements for an organism's viability, genes can be classified into essential genes and non-essential genes. Non-essential genes can be further classified into toxicity-modulating genes and no-phenotype genes based on the fitness phenotype of yeast cells when the gene is deleted under DNA-damaging conditions. In this study, graph theoretical approaches were used to characterize essential, toxicity-modulating and no-phenotype genes for S. cerevisiae in the physical interaction (PI) network and the perturbation sensitivity (PS) network. We also gained previously published biological datasets to gain a more complete understanding of the differences and relationships between essential, toxicity-modulating genes and no-phenotype genes. The analysis results indicate that toxicity-modulating genes have similar properties as essential genes, and toxicity-modulating genes might represent a middle ground between essential genes and no-phenotype genes, suggesting that cells initiate highly coordinated responses to damage that are similar to those needed for vital cellular functions. These findings may elucidate the mechanisms for understanding toxicity-modulating processes relevant to certain diseases. [ABSTRACT FROM AUTHOR]

Housekeeping genes are genes that are turned on most of the time in almost every tissue to maintain cellular functions. Tissue-selective genes are predominantly expressed in one or a few biologically relevant tissue types. Benefitting from the massive gene expression microarray data obtained over the past decades, the properties of housekeeping and tissue-selective genes can now be investigated on a large-scale manner. In this study, we analyzed the topological properties of housekeeping and tissue-selective genes in the protein-protein interaction (PPI) network. Furthermore, we compared the biological properties and amino acid usage between these two gene groups. The results indicated that there were significant differences in topological properties between housekeeping and tissue-selective genes in the PPI network, and housekeeping genes had higher centrality properties and may play important roles in the complex biological network environment. We also found that there were significant differences in multiple biological properties and many amino acid compositions. The functional genes enrichment and subcellular localizations analysis was also performed to investigate the characterization of housekeeping and tissue-selective genes. The results indicated that the two gene groups showed significant different enrichment in drug targets, disease genes and toxin targets, and located in different subcellular localizations. At last, the discriminations between the properties of two gene groups were measured by the F-score, and expression stage had the most discriminative index in all properties. These findings may elucidate the biological mechanisms for understanding housekeeping and tissue-selective genes and may contribute to better annotate housekeeping and tissue-selective genes in other organisms. [ABSTRACT FROM AUTHOR]