  Four chapters of the synthesis represent four major areas of my research
interests: 1) data analysis in molecular biology, 2) mathematical modeling of
biological networks, 3) genome evolution, and 4) cancer systems biology. The
first chapter is devoted to my work in developing non-linear methods of
dimension reduction (methods of elastic maps and principal trees) which extends
the classical method of principal components. Also I present application of
matrix factorization techniques to analysis of cancer data. The second chapter
is devoted to the complexity of mathematical models in molecular biology. I
describe the basic ideas of asymptotology of chemical reaction networks aiming
at dissecting and simplifying complex chemical kinetics models. Two
applications of this approach are presented: to modeling NFkB and apoptosis
pathways, and to modeling mechanisms of miRNA action on protein translation.
The third chapter briefly describes my investigations of the genome structure
in different organisms (from microbes to human cancer genomes). Unsupervised
data analysis approaches are used to investigate the patterns in genomic
sequences shaped by genome evolution and influenced by the basic properties of
the environment. The fourth chapter summarizes my experience in studying cancer
by computational methods (through combining integrative data analysis and
mathematical modeling approaches). In particular, I describe the on-going
research projects such as mathematical modeling of cell fate decisions and
synthetic lethal interactions in DNA repair network. The synthesis is concluded
by listing major challenges in computational systems biology, connected to the
topics of this text, i.e. dealing with complexity of biological systems.
