Computational Biology

Modern analytical methods can identify compounds at molecular level, generating new experimental data that is changing our understanding of biology, leading to a breakthrough in biological sciences. The omics areas of research (genomics, metagenomics, transcriptomics, proteomics, metabolomics, ...) combine this new data with suitable bioinformatics/biostatistics tools to produce new knowledge in molecular biology and, in turn, in related areas like health, evolution or ecology.

The CoDaS Lab is specialized in biostatistics, machine learning and multivariate analysis in omics data and other sources of complex data. We provide:

  • Techniques, software tools and computing power for data analysis, design of experiments, sample size computation, visualization, interpretation of results, identification of biomarkers, estimation of statistical significance and other similar capabilities for the treatment of omics and related data.

  • The ability to use state-of-the-art analysis tools, like PCA/PLS-DA, ANOVA, sparse methods, variable selection, ASCA, PERMANOVA, Design of Experiments, etc., or to design new algorithms tailored to the analysis problem at hand.

  • The statistical design of clinical studies, analysis of samples and interpretation of omics data.

  • We are proactive and we like to be involved from the derivation of the project idea and the design of the experiment/clinical trial.


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