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  139. N. Blöchliger, A. Caflisch, and A. Vitalis. Weighted distance functions improve analysis of high-dimensional data: Application to molecular dynamics simulations. J. Chem. Theory Comput. 11 (11), 5481-5492 (2015) (DOI)
  140. J. H. Prinz, H. Wu, M. Sarich, B. Keller, M. Senne, M. Held, J. D. Chodera, C. Schütte, and F. Noé. Markov models of molecular kinetics: Generation and validation. J. Chem. Phys., 134 (17), 174105 (2011) (DOI)
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  144. T. Zhou and A. Caflisch. Distribution of reciprocal of interatomic distances: A fast structural metric. J. Chem. Theory Comput., 8 (8), 2930-2937 (2012) (DOI)
  145. M. Bacci, A. Caflisch, and A. Vitalis. On the removal of initial state bias from simulation data. J. Chem. Phys., 150 (10), 104105 (2019) (DOI)
  146. A. Vitalis. An improved and parallel version of a scalable algorithm for analyzing time series data. ArXiv (June 2020) (ArXiv)
  147. F. Cocina, A. Vitalis, and A. Caflisch. SAPPHIRE-based clustering. J. Chem. Theory Comput., 16 (10), 6383-6396 (2020) (DOI
  148. J. J. Hunter. The computation of the mean first passage times for Markov chains. Linear Algebra and its Applications, 549, 100-122 (2018) (DOI
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  151. M. Bacci, J. Vymětal, M. Mihajlovic, A. Caflisch, and A. Vitalis. Amyloid β Fibril Elongation by Monomers Involves Disorder at the Tip. J. Chem. Theory Comput., 13 (10), 5117-5130 (2017) (DOI)

    Application examples using CAMPARI or its predecessors (list updated until ca. 2013)
  152. H. T. Tran, X. Wang, and R. V. Pappu. Reconciling Observations of Sequence-Specific Conformational Propensities with the Generic Polymeric Behavior of Denatured Proteins. Biochemistry 44 (34), 11369-11380 (2005) (DOI)
  153. H. T. Tran and R. V. Pappu. Toward an accurate theoretical framework for describing ensembles for proteins under strongly denaturing conditions. Biopys. J. 91, 1868-1886 (2006) (PDF)
  154. A. Vitalis, X. Wang, and R. V. Pappu. Quantitative characterization of intrinsic disorder in polyglutamine: insights from analysis based on polymer theories. Biophys. J. 93 (6), 1923-1937 (2007) (DOI)
  155. A. Vitalis, X. Wang, and R. V. Pappu. Atomistic Simulations of the Effects of Polyglutamine Chain Length and Solvent Quality on Conformational Equilibria and Spontaneous Homodimerization. J. Mol. Biol. 384 (1), 279-297 (2008) (DOI)
  156. A. Vitalis, N. Lyle, and R. V. Pappu. Thermodynamics of β-Sheet Formation in Polyglutamine. Biophys. J. 97 (1), 303-311 (2009) (DOI)
  157. T. E. Williamson, A. Vitalis, S. L. Crick, and R. V. Pappu. Modulation of Polyglutamine Conformations and Dimer Formation by the N-Terminus of Huntingtin. J. Mol. Biol. 396 (5), 1295-1309 (2010) (DOI)
  158. M. A. Wyczalkowski, A. Vitalis, and R. V. Pappu. New Estimators for Calculating Solvation Entropy and Enthalpy and Comparative Assessments of Their Accuracy and Precision. J. Phys. Chem. B 114 (24), 8166-8180 (2010) (DOI)
  159. A. H. Mao, S. L. Crick, A. Vitalis, C. L. Chicoine, and R. V. Pappu. Net charge per residue modulates conformational ensembles of intrinsically disordered proteins. Proc. Natl. Acad. Sci. USA 107 (18), 8183-8188 (2010) (DOI)
  160. A. Vitalis and A. Caflisch. Micelle-Like Architecture of the Monomer Ensemble of Alzheimer’s Amyloid-β Peptide in Aqueous Solution and Its Implications for Aβ Aggregation. J. Mol. Biol. 403 (1), 148-165 (2010) (DOI)
  161. R. Halfmann, S. Alberti, R. Krishnan, N. Lyle, C. W. O'Donnell, O. D. King, B. Berger, R. V. Pappu, and S. Lindquist. Opposing Effects of Glutamine and Asparagine Govern Prion Formation by Intrinsically Disordered Proteins. Mol. Cell 73, 72-84 (2011) (DOI)
  162. A. Vitalis and A. Caflisch. 50 Years of Lifson–Roig Models: Application to Molecular Simulation Data. J. Chem. Theory Comput. 8 (1), 363-373 (2012) (DOI)
  163. R. K. Das, S. L. Crick, and R. V. Pappu. N-Terminal Segments Modulate the α-Helical Propensities of the Intrinsically Disordered Basic Regions of bZIP Proteins. J. Mol. Biol. 416 (2), 287-299 (2012) (DOI)
  164. A. Radhakrishnan, A. Vitalis, A. H. Mao, A. T. Steffen, and R. V. Pappu. Improved Atomistic Monte Carlo Simulations Demonstrate That Poly-l-Proline Adopts Heterogeneous Ensembles of Conformations of Semi-Rigid Segments Interrupted by Kinks. J. Phys. Chem. B 116 (23), 6862-6871(2012) (DOI)
  165. R. Scalco and A. Caflisch. Ultrametricity in protein folding dynamics. J. Chem. Theory Comput. 8 (5), 1580-1588 (2012) (DOI)
  166. W. Meng, N. Lyle, B. Luan, D. P. Raleigh, and R. V. Pappu. Experiments and simulations show how long-range contacts can form in expanded unfolded proteins with negligible secondary structure. Proc. Natl. Acad. Sci. USA 110 (6), 2123-2128 (2013) (DOI)
  167. R. K. Das and R. V. Pappu. Conformations of intrinsically disordered proteins are influenced by linear sequence distributions of oppositely charged residues. Proc. Natl. Acad. Sci. USA 110 (33), 13392-13397 (2013) (DOI)
  168. N. Lyle, R. K. Das, and R. V. Pappu. A quantitative measure for protein conformational heterogeneity. J. Chem. Phys. 139 (12), 121907 (2013) (DOI)
  169. A. Magno, S. Steiner, and A. Caflisch. Mechanisms and kinetics of acetyl-lysine binding to bromodomains. J. Chem. Theory Comput. 9 (9), 4225-4232 (2013) (DOI)
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