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Items: 4

1.

Bayesian network reconstruction using systems genetics data: comparison of MCMC methods.

Tasaki S, Sauerwine B, Hoff B, Toyoshiba H, Gaiteri C, Chaibub Neto E.

Genetics. 2015 Apr;199(4):973-89. doi: 10.1534/genetics.114.172619. Epub 2015 Jan 28.

2.

Improving breast cancer survival analysis through competition-based multidimensional modeling.

Bilal E, Dutkowski J, Guinney J, Jang IS, Logsdon BA, Pandey G, Sauerwine BA, Shimoni Y, Moen Vollan HK, Mecham BH, Rueda OM, Tost J, Curtis C, Alvarez MJ, Kristensen VN, Aparicio S, Børresen-Dale AL, Caldas C, Califano A, Friend SH, Ideker T, Schadt EE, Stolovitzky GA, Margolin AA.

PLoS Comput Biol. 2013;9(5):e1003047. doi: 10.1371/journal.pcbi.1003047. Epub 2013 May 9.

3.

Systematic analysis of challenge-driven improvements in molecular prognostic models for breast cancer.

Margolin AA, Bilal E, Huang E, Norman TC, Ottestad L, Mecham BH, Sauerwine B, Kellen MR, Mangravite LM, Furia MD, Vollan HK, Rueda OM, Guinney J, Deflaux NA, Hoff B, Schildwachter X, Russnes HG, Park D, Vang VO, Pirtle T, Youseff L, Citro C, Curtis C, Kristensen VN, Hellerstein J, Friend SH, Stolovitzky G, Aparicio S, Caldas C, Børresen-Dale AL.

Sci Transl Med. 2013 Apr 17;5(181):181re1. doi: 10.1126/scitranslmed.3006112.

4.

Kinetic Monte Carlo method applied to nucleic acid hairpin folding.

Sauerwine B, Widom M.

Phys Rev E Stat Nonlin Soft Matter Phys. 2011 Dec;84(6 Pt 1):061912. Epub 2011 Dec 19.

PMID:
22304121

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