Nicola Luigi Bragazzi and Claudio Nicolini
Nanogenomics, being the interplay of nanobiotechnologies and bioinformatics, is emerging as an intriguing approach in the field of nowadays biomedicine. Microarrays can produce a wealth of data and details, but they need an algorithm for data reduction to be clearly understood and exploited. The Leader Genes approach, integrating the different available databases and genomics tools, enables the user to search for genes linked to a disease or a cellular process, and to visualize the class of the most important genes, that is to say those having the highest number of interconnections. In this manuscript, we will review the algorithm which has been validated with both experimental and clinical studies. We will describe the different steps that lead to its final version, and we will discuss future perspectives and developments.
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Journal of Computer Science & Systems Biology received 2279 citations as per Google Scholar report