Journal ArticleDOI
Fuzzy spectral clustering by PCCA+: application to Markov state models and data classification
Susanna Röblitz,Marcus Weber +1 more
TLDR
It is demonstrated in this paper that PCCA+ always delivers an optimal fuzzy clustering for nearly uncoupled, not necessarily reversible, Markov chains with transition states.Abstract:
Given a row-stochastic matrix describing pairwise similarities between data objects, spectral clustering makes use of the eigenvectors of this matrix to perform dimensionality reduction for clustering in fewer dimensions. One example from this class of algorithms is the Robust Perron Cluster Analysis (PCCA+), which delivers a fuzzy clustering. Originally developed for clustering the state space of Markov chains, the method became popular as a versatile tool for general data classification problems. The robustness of PCCA+, however, cannot be explained by previous perturbation results, because the matrices in typical applications do not comply with the two main requirements: reversibility and nearly decomposability. We therefore demonstrate in this paper that PCCA+ always delivers an optimal fuzzy clustering for nearly uncoupled, not necessarily reversible, Markov chains with transition states.read more
Citations
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Exploring Substrate Binding in the Extracellular Vestibule of MhsT by Atomistic Simulations and Markov Models.
TL;DR: Computational findings were validated by experimental mutagenesis studies and shed light on the ligand binding characteristics of the EV of NSS, which may facilitate development of allosteric ligands targeting NSS.
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Quantifying Energetic and Entropic Pathways in Molecular Systems.
TL;DR: In this article , a physics-based machine learning method called state predictive information bottleneck (SPIB) was used to find nonlinear reaction coordinates for three systems of varying complexity, including an analytical flat-energy double-well system and an analytical four-well systems, for a simulation of benzoic acid permeation through a lipid bilayer.
Journal ArticleDOI
EspcTM: Kinetic Transition Network Based on Trajectory Mapping in Effective Energy Rescaling Space.
TL;DR: A new method, named effective energy rescaling space trajectory mapping (EspcTM), is introduced to detect metastable states and construct transition networks based on the simulation trajectories of the complex biomolecular system.
Journal ArticleDOI
Exploration of the Misfolding Mechanism of Transthyretin Monomer: Insights From Hybrid-Resolution Simulations and Markov State Model Analysis
Shuangyan Zhou,Jie Cheng,Ting Yang,Mingyue Ma,Wenying Zhang,Shuai Yuan,Glenn V. Lo,Yusheng Dou +7 more
TL;DR: This work identified a potential misfolded state of the TTR monomer and elucidated the misfolding pathway for its conformational transition, which can provide a valuable theoretical basis for understanding of TTR aggregation and the pathogenesis of ATTR amyloidosis at the atomic level.
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Exploring the folding process of human βB2-crystallin using multiscale molecular dynamics and the Markov state model.
TL;DR: Light is shed on the molecular details of the folding mechanism of HβB2C in an aqueous environment and may contribute to interpreting different experimental findings, as well as the rational design of potential molecules to treat cataract disease.
References
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Journal ArticleDOI
Laplacian Eigenmaps for dimensionality reduction and data representation
Mikhail Belkin,Partha Niyogi +1 more
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