Zura Kakushadze

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We present a novel method for extracting cancer signatures by applying statistical risk models (http://ssrn.com/abstract=2732453) from quantitative finance to cancer genome data. Using 1389 whole genome sequenced samples from 14 cancers, we identify an " overall " mode of somatic mutational noise. We give a prescription for factoring out this noise and(More)
To my mother Ludmila (Mila) Kakushadze on the occasion of her upcoming birthday Abstract We propose a new index to quantify SSRN downloads. Unlike the SSRN downloads rank, which is based on the total number of an author's SSRN downloads, our index also reflects the author's productivity by taking into account the download numbers for the papers. Our index(More)
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