Pınar Pir

Pnar PirPınar Pir studied chemical engineering at the Boğaziçi University in Istanbul, and focused on systems biology of respiratory deficient mutant strains of yeast Saccharomyces cerevisiae in her PhD studies. She joined Prof. Stephen G. Oliver's group at the University of Manchester (Faculty of Life Sciences) in 2006 as a postdoctoral research associate, and continued her work on genetic control of growth rate in S.cerevisiae at the University of Cambridge (Cambridge Systems Biology Center). She took part in Robot Scientist (Adam and Eve) projects in collaboration with Prof. Ross King's research group, contributed to further improvements on genome-wide yeast metabolic model Yeast 4 in collaboration with Prof. Pedro Mendes` research group. She worked for BioSyntha Technology Limited (previously part of Novacta Biosystems Limited) on metabolic engineering of microorganisms for production of biofuels. 


Pınar joined the Le Novère Lab in October 2012 as a senior postdoctoral research associate. She has two main research interests:

1. Developing interfaces and algoritms for parallel simulation of modular models of cellular processes 

Functions carried out by the cells are often modular in terms of type of interactions. This natural modularity results in construction and validation of models for small modules using a case-specific programming language and simulator. Building larger models by re-using the small modules is highly desirable to save time and resources. The interface Pınar works on is implemented in a programming language which can interact with most of the popular simulators (i.e. Python). The algorithm aims to efficiently facilitate the parallel simulation of modules and the exchange of information between modules during the simulations. Three published models of calcium dynamics in dendritic spines were used to test the interface and its algorithm.

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2. Developing modular models of cell differentiation and re-programming

The signalling pathways in stem cells propagate the external signals to transcriptional networks and mediate the cell fate decisions. Pnar has implemented dynamic models of transcriptional networks that respond to signals LIF, FGF and HIPPO and regulate the differentiation of mouse blastocyst cells into TE, ICM, EPI and PE cells. She aims to develop modular models of signalling pathways, transcriptional networks and DNA/Chromatin modifications (epigenetics) in differentiation and reprogramming of embryonic cells. Parallel simulation of these model will provide a better understanding of dynamics of cell fate decisions. Read more about stem cells and modular modelling.

Pnar_TFnetwork_website.png      Pnar_epigenetics_website.png


Visit Pınar`s Google Scholar Citations page here.