In this "omics" era, signaling molecule families are being defined and the complexities of the control of signal transduction are now becoming apparent. Genome projects are currently producing many thousands of gene sequences from which protein amino acid sequences may be deduced. The deposition of such data in public databases before a paper can be published allows proteome bioinformaticians to perform in silico analyses based on very large data sets, increasing prediction confidence and inference power that were previously impaired by either unbalanced organism source or poor data sets. Experimental research on different organisms and taxonomic lineages has provided functional evidence concerning a high number of genes and proteins, as well as molecular and cellular pathways. Most often, the characterization of genes and proteins from different organisms is asynchronous. For instance, when considering two genes "X" and "Y," it may happen that the function of gene "X" may be unraveled by the characterization of a Drosophila mutant, while the enzymatic activity of protein encoded by gene "Y" of Arabidopsis is reported. Although functional evidence is not simply forwardable from a gene/protein to the orthologous genes or proteins, the asynchronous flow of discoveries has already allowed several scientists to perform comparative analyses aimed at enhancing the elucidation of important mechanisms. Thus, computational analysis can be exploited to fuel hypothesis-driven experimental research through the exploration of online databases; and in the last decade of the 20th century as well as in recent years, a progressively increasing number of genome/proteome-wide comparative analyses resulted in both defining novel sequence marks and identifying genomic/proteomic complements.
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