Systems biology aims to describe the emergence of biological complexity through integration of biophysical, biochemical, genetic, and genomic data. In the past few years, we have witnessed a near exponential rise in biological data output, transforming the biological sciences from a “data-poor” to a “data-rich” discipline. A successful integration of these large and diverse data sets typically involves development of quantitative and predictive computable network models that allow generation of new testable hypotheses.

During the past few years, a focus of Salehi-Ashtiani’s group, in collaboration with other researchers, has been on defining the metabolic network of the green alga Chlamydomonas reinhardtii, a model organism for the study of biofuel production. Salehi-Ashtiani has pioneered a number of combinatorial and large-scale genomic methodologies, culminating in the development of an integrated gene annotation and computational modelling platform. This platform was recently used to reconstruct the first genome-scale algal metabolic network, offering both computational and biological resources for carrying out further research on metabolism of algal species. With the experimental and computational resources that Salehi-Ashtiani’s group has developed, his laboratory is engaged in further integrating wet and dry bench experiments to decipher genotype-phenotype relationships, define metabolic regulatory networks, and carry out metabolic engineering experiments towards improving algal biomass composition for biofuel production.

Prior to joining NYU Abu Dhabi, Dr. Salehi-Ashtiani served as a Principal Investigator on a number of US federally funded projects supported from the US National Institutes of Health and the US Department of Energy.

Highlighted Interests