Computational Biology

Integration of multiple molecular and cellular profiling datasets
  • The integrative analysis of multiple molecular profiling (omics) levels reveals complementary information
  • Biological systems require the interplay of various levels of functional molecules
  • Proteogenomics approaches and advanced bioinformatics capabilities can extract relevant information and support the discovery of multivariate and multi-omics biomarkers
  • Experimental strategies designed to enable comprehensive bioinformatics and statistical data analysis
  • Advanced data analyses include genomics, statistics, cluster analyses, machine learning approaches, feature selection, multivariate statistics, correlation analysis, Lasso/Elastic net procedures, pathway and network analyses and much more


Further reading

Huang, S.M., Abernethy, D.R., Wang, Y., Zhao, P., Zineh, I. (2013) The utility of modeling and simulation in drug development and regulatory review, J Pharm Sci, 102(9):2912-23 [Link]

Ritchie, M.D., Holzinger, E.R., Li, R., Pendergrass, S.A., and Kim, D. (2015) Methods of integrating data to uncover genotype-phenotype interactions, Nat Rev Genet, 16(2):85-97. [Link]


From genotype to phenotype
Systems Biology, Pharmacology and Medicine mandate the integration of molecular and cellular profiling datasets. Adapted from Huang, Abernethy, Wang, Zhao, Zineh, J Pharm Sci, 2013 102, 2912-2923