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The group's work is aimed at developing computational and mathematical-statistical methods for the analysis and interpretation of biological information. We apply systems biology approaches, integrating data from various aspects of cellular functions and representing them as networks of functional relationships between biological entities.
An important part of our work is the development of tools for proteomics data analysis, particularly mass spectra. The application of mathematical algorithms to the interpretation of mass spectra and to the quantification of the relative abundance between samples.
In parallel we conduct educational activities and training of specialists in bioinformatics. |
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Network representation of functional relations between biomolecules is a research subject comprised by in silico Systems Biology. In this kind of representation, genes and proteins are represented as nodes and functional relations are represented in the form of edges that connect the corresponding nodes. The BisoGenet project has several components: integration of data from different sources, construction of gene and protein networks from the integrated information, as well as networks visualization and analysis. |
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Development of computer tools and statistical methods for Proteomics data analysis, experiments design, and integration of Genomics data, as well as other biological data. |
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DNA microarray data analysis |
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DNA microarrays have emerged as the most used technology in the mass quantification of genes expression and have been applied in a wide range of biological research in recent years. The work of our group has focused on the experimental design of microarrays and the statistical analysis & interpretation of expression profiles. |
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