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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Journal ArticleDOI
FSATOOL: A useful tool to do the conformational sampling and trajectory analysis work for biomolecules.
TL;DR: This article provides a convenient and user‐friendly tool that is compatible to AMBER, called fast sampling and analysis tool (FSATOOL), which extracts the dominant transition pathways automatically from the folding network by Markov state model.
Posted ContentDOI
Differences in interactions between transmembrane domains tune the activation of metabotropic glutamate receptors
Jordana K. Thibado,Jean-Yves Tano,Joon Lee,Leslie A. Salas-Estrada,Davide Provasi,Alexa Strauss,Joao Marcelo Lamim Ribeiro,Guoqing Xiang,Johannes Broichhagen,Marta Filizola,Martin J. Lohse,Joshua Levitz +11 more
TL;DR: In this article, a combination of single molecule fluorescence, molecular dynamics, functional assays, and conformational sensors is used to reveal that distinct TMD assembly properties drive differences between mGluR subtypes.
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Kernel Embedding Based Variational Approach for Low-Dimensional Approximation of Dynamical Systems
Wenchong Tian,Hao Wu +1 more
TL;DR: In this paper, a kernel embedding-based variational approach for dynamical systems (KVAD) is proposed to solve the problem of low-dimensional feature mappings from data.
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CATBOSS: Cluster Analysis of Trajectories Based on Segment Splitting.
TL;DR: In this paper, a new method, cluster analysis of trajectories based on segment splitting (CATBOSS), applies density-peak-based clustering to classify trajectory segments learned by change detection.
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Hormonal regulation of ovarian follicle growth in humans: Model-based exploration of cycle variability and parameter sensitivities.
TL;DR: In this article , the authors present a modelling and simulation framework for the dynamics of ovarian follicles and key hormones along the hypothalamic-pituitary-gonadal axis throughout consecutive human menstrual cycles.
References
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Journal ArticleDOI
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