@inproceedings{51d229d432be4bfabb6fb92bdf30e21b,

title = "Discovering statistical vulnerabilities in highly mutable viruses: A random matrix approach",

abstract = "The advancement in fast DNA sequencing technologies has opened up new opportunities to explore a diverse set of questions in biomedical research. In this paper, we review a general method which utilizes the available sequence data to determine potential weaknesses in highly mutable viruses, and which has shown promise in the design of vaccines. A key computational part of this method employs concepts from random matrix theory to obtain a robust estimate of a large covariance matrix. We apply this general method on hepatitis C virus as an example, and verify its usefulness by linking with the existing experimental and structural data.",

keywords = "Random matrices, estimation, hepatitis C virus",

author = "Quadeer, {A. A.} and Louie, {R. H.Y.} and K. Shekhar and Chakraborty, {A. K.} and I. Hsing and McKay, {M. R.}",

year = "2014",

doi = "10.1109/SSP.2014.6884561",

language = "אנגלית",

isbn = "9781479949755",

series = "IEEE Workshop on Statistical Signal Processing Proceedings",

publisher = "IEEE Computer Society",

pages = "5--8",

booktitle = "2014 IEEE Workshop on Statistical Signal Processing, SSP 2014",

address = "ארצות הברית",

note = "2014 IEEE Workshop on Statistical Signal Processing, SSP 2014 ; Conference date: 29-06-2014 Through 02-07-2014",

}