The past decade has witnessed dramatic new insights in the field of genomics, brought about by the development of large-scale data aquisition and analysis techniques. These discoveries are posing new challenges in the development of modelling techniques aimed at interpreting genomic data and viewing the functioning genome as a global system. This proposal presents a new, topological approach to modelling and encoding functional genomic information. It is expected that the candidate's background in independent research in pure mathematics, when augmented with mentored training in genetics and bioinformatics, will produce technological advances in this exciting area at the interface of biology and mathematics. The didactic period of this mentored scientist grant will focus on building the necessary solid foundation in genetics, modern laboratory techniques, and bioinformatics. The initial aims of the research portion are to: (a) fully develop the mathematical modelling techniques presented in the body of this proposal, with a special focus on the actin cytoskeleton of yeast; (b) develop algorithmic methods for encoding the mathematical model information; (c) incorporate large-scale data analysis techniques into the models, with a particular emphasis on the analysis of cDNA arrays. During the duration of the grant, the candidate will work closely with members of the Stanford Department of Genetics, and the Berkeley and Stanford Statistics Departments.
Han, Wonshik; Nicolau, Monica; Noh, Dong-Young et al. (2010) Characterization of molecular subtypes of Korean breast cancer: an ethnically and clinically distinct population. Int J Oncol 37:51-9 |
Dairkee, S H; Nicolau, M; Sayeed, A et al. (2007) Oxidative stress pathways highlighted in tumor cell immortalization: association with breast cancer outcome. Oncogene 26:6269-79 |