Andrey Alexeyenko is an expert in systems biology. He developed methods for integrating heterogeneous high-throughput, experimental, and literature data into global networks of functional coupling, and for applying the network to exploratory and predictive analyses of experimental and clinical data. The approach enables statistically sound interpretation of various data types, such as differential expression, methylation etc. The systems integration based on gene interaction networks has the following strengths:
- all major types of molecular interactions are present in the global network of functional coupling between genes, proteins, and small molecules,
- alterations of genomic sequence, methylation, transcription, protein abundance are rendered into the space of pathways and processes, and
- the pathway- and network-based view enables efficient, low-dimensional statistical analysis and is transparent for biological interpretation of the data.
Other existing methods in this field are e.g. Gene Set Enrichment Analysis and commercial products by GeneGO, geneXplain, and Ingenuity (IPA). Assistance in using these tools and results interpretation can be provided. Andrey can also help with related issues in high-throughput data management, biostatistics, functional interpretation of genome variation, and bridging gaps between different sides of analysis.
Frings, O., Alexeyenko, A., and Sonnhammer, E. L. (2013) MGclus: network clustering employing shared neighbors. Mol Biosyst
Alexeyenko, A., Lee, W., Pernemalm, M., Guegan, J., Dessen, P., Lazar, V., Lehtio, J., and Pawitan, Y. (2012) Network enrichment analysis: extension of gene-set enrichment analysis to gene networks. BMC Bioinformatics
Alexeyenko, A., Wassenberg, D. M., Lobenhofer, E. K., Yen, J., Linney, E., Sonnhammer, E. L., and Meyer, J. N. (2010) Dynamic zebrafish interactome reveals transcriptional mechanisms of dioxin toxicity. PLoS ONE
Alexeyenko, A. and Sonnhammer, E. L. (2009) Global networks of functional coupling in eukaryotes from comprehensive data integration. Genome Res.