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The emerging field of bioinformatics in proteomics is introducing new algorithms in order to handle large and heterogeneous datasets and improve the knowledge-discovery process. Management systems, software construction and application, database population and leverage, as well as computed prediction, have crafted bioinformatics into a valuable tool for basic research. Human reproduction is one of many fields proteomics has been extensively studying over the last decade, accumulating complex experimental data at a rate far exceeding the ability to assimilate them. Transformation of the rapidly proliferating quantities of experimental information into a usable form in order to facilitate their analysis is a challenging task. On this track, bioinformatics, an essential part of proteomics research, aspires to amend inquiries into a better manipulated, a better handled and a better understood form so as to enhance existing knowledge expansion.
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Anagnostopoulos et al. (2011) studied this question.
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