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Columbia University’s Data Science Institute Presents:

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Wednesday, April 6 • 2:00pm - 4:30pm
Connectivity Homology Enables Inter-Species Network Models of Synthetic Lethality [P4]

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Synthetic lethality (SL) is an interaction where two nonessential genes lead to cellular inviability when knocked out simultaneously. Recent work suggests it may be useful in cancer therapy. It may also predict novel drug-drug interactions and suggest mechanisms of adverse drug reactions. Few SL interactions have been found in humans to date, but many are known in yeast. Here, we present Species INdependent TRAnslation (SINaTRA), an algorithm that predicts SL in translation between species using protein-protein interaction (PPI) networks and connectivity homology. We validate SINaTRA using S. cerevisiae and S. pombe and find that model performance improves significantly with the use of SINaTRA. In addition, SINaTRA outperforms other methods of predicting SL, including genetic homology. We then apply our model to the human PPI network. After genetic filtering using 1000 Genomes data, we provide 100 million human gene pairs with measures of their predicted synthetic lethality (SINaTRA scores)

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avatar for Alexandra Jacunski

Alexandra Jacunski

PhD Candidate in Systems Biology, College of Physicians and Surgeons
Alexandra is a PhD candidate in the Tatonetti Lab. Her  research focuses on utilizing and understanding biological networks, especially in the contexts of drug-drug interactions (DDIs) and human disease. Part of her research pertains to the development of methods that allow for the direct comparison of biological networks between species, which have allowed her to create inter-species models of biological processes.

Wednesday April 6, 2016 2:00pm - 4:30pm
Roone Arledge Auditorium Lerner Hall, Columbia University 2920 Broadway, New York, NY 10040