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Analyzing Ensembles of Amyloid Proteins Using Bayesian Statistics.

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Title: Analyzing Ensembles of Amyloid Proteins Using Bayesian Statistics.
Authors: Gurry T; Computational and Systems Biology Initiative, Massachusetts Institute of Technology, Cambridge, MA, 02139-4307, USA.; Research Laboratory of Electronics, Massachusetts Institute of Technology, Cambridge, MA, 02139-4307, USA., Fisher CK; Physics Department, Boston University, Boston, MA, 02215, USA., Schmidt M; Research Laboratory of Electronics, Massachusetts Institute of Technology, Cambridge, MA, 02139-4307, USA.; Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA, 02139-4307, USA., Stultz CM; Computational and Systems Biology Initiative, Massachusetts Institute of Technology, Cambridge, MA, 02139-4307, USA. cmstultz@mit.edu.; Research Laboratory of Electronics, Massachusetts Institute of Technology, Cambridge, MA, 02139-4307, USA. cmstultz@mit.edu.; Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA, 02139-4307, USA. cmstultz@mit.edu.; The Institute for Medical Engineering and Science, Massachusetts Institute of Technology, Cambridge, MA, 02139-4307, USA. cmstultz@mit.edu.
Source: Methods in molecular biology (Clifton, N.J.) [Methods Mol Biol] 2016; Vol. 1345, pp. 269-80.
Publication Type: Journal Article
Journal Info: Publisher: Humana Press Country of Publication: United States NLM ID: 9214969 Publication Model: Print Cited Medium: Internet ISSN: 1940-6029 (Electronic) Linking ISSN: 10643745 NLM ISO Abbreviation: Methods Mol Biol Subsets: MEDLINE
Database: MEDLINE Ultimate
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