Refine
Year of publication
Document Type
- Article (212)
- ZIB-Report (70)
- In Proceedings (23)
- In Collection (9)
- Book chapter (7)
- Book (2)
- Doctoral Thesis (2)
- Other (2)
- Poster (2)
- Habilitation (1)
- Research data (1)
- Software (1)
Is part of the Bibliography
- no (332)
Keywords
- metastability (8)
- cycle decomposition (3)
- rare events (3)
- reaction coordinate (3)
- Bayesian inference (2)
- Clustering (2)
- DS-MLE (2)
- EM algorithm (2)
- Jeffreys prior (2)
- MPLE (2)
- Markov chain (2)
- Markov operator (2)
- Markov state model (2)
- Mathematical modeling (2)
- Model Selection, (2)
- NPMLE (2)
- Networks (2)
- Real-time cell analyzer (2)
- Stochastic Block Model (2)
- Toxicity (2)
- Variational Bayes EM (2)
- canonical ensemble (2)
- change of measure (2)
- coarse graining (2)
- conformation (2)
- cross-entropy method (2)
- directed networks (2)
- effective dynamics (2)
- essential degrees of freedom (2)
- hybrid Monte Carlo (2)
- hyperparameter (2)
- hyperprior (2)
- importance sampling (2)
- metadynamics (2)
- metastable sets (2)
- molecular dynamics (2)
- neural networks (2)
- non-equilibrium molecular dynamics (2)
- nonequilibrium molecular dynamics (2)
- optimal control (2)
- principle of maximum entropy (2)
- rare event simulation (2)
- reference prior (2)
- stochastic control (2)
- stochastic optimal control (2)
- transfer operator (2)
- transition manifold (2)
- unsupervised classification (2)
- $n$-pentane molecule (1)
- Alanine dipeptide (1)
- Bayesian hierarchical modeling (1)
- Bayesian hierarchical modelling (1)
- Coarse graining (1)
- Complex networks (1)
- Donsker-Varadhan principle (1)
- Electric field (1)
- Epidemiology (1)
- Ergodic diffusion (1)
- Floquet theory (1)
- Fokker--Planck equation (1)
- Galerkin method (1)
- Girsanov (1)
- Girsanov Theorem (1)
- Girsanov transformation (1)
- Ha (1)
- Hamiltonian dynamics (1)
- Hamiltonian system (1)
- IC_{50} (1)
- Importance Sampling (1)
- Importance sampling (1)
- Infectious Diseases (1)
- MSM (1)
- Markov process (1)
- Markov state models (1)
- Markov states model (1)
- Markow State Methods (1)
- Microbiology (1)
- Module identification and classification (1)
- Monte Carlo (1)
- Monte Carlo methods (1)
- Noise (1)
- Non-equilibrium (1)
- Opioid, Ligand-Receptor Interaction, Binding Kinetics, Molecular Dynamics, Metadynamics, SQRA (1)
- Parameter estimation (1)
- Parasitology (1)
- Perron cluster an (1)
- Perron root (1)
- Perron- (1)
- Public Health, Environmental and Occupational Health (1)
- QCMD (1)
- Reweighting (1)
- Schrödinger equation (1)
- Schur decomposition (1)
- Smoluchowski dynamics (1)
- Smoluchowski equation (1)
- Stochastic Differential Equation (1)
- Transfer operator (1)
- Virology (1)
- Wigner transform (1)
- Windkessel model (1)
- adaptive resolution (1)
- adiabatic limit (1)
- almost invariant aggregates (1)
- almost invariant set (1)
- almost invariant sets (1)
- alternating linear scheme (1)
- anastomosis (1)
- application in statistical physics (1)
- asymptotic expansion (1)
- bellmann equation (1)
- biochemical conformation (1)
- biomolecular conformations (1)
- bridge sampling (1)
- cardiovascular parameters (1)
- chemical master equation (1)
- chemical potential (1)
- cluster method (1)
- coherent set, (1)
- communication (1)
- computational cardiovascular model (1)
- conformation dynamics (1)
- conformational dynamics (1)
- conformational ensemble (1)
- cross entropy (1)
- cross-correlation (1)
- cumulant generating function (1)
- data-driven (1)
- diagnostic frequency (1)
- directed networks, modules, cycle decomposition, measure of node communication (1)
- dynamic programming (1)
- embedding (1)
- equation-free (1)
- essential molecular dynamics (1)
- first exit time (1)
- half time perio (1)
- heterogeneous catalysis (1)
- heterogeneous multiscale method (1)
- hidden state (1)
- hierarchical annealing (1)
- highly oscillatory phase (1)
- hitting times (1)
- important sampling (1)
- information costs (1)
- kinetic Monte Carlo (1)
- linear reaction networks (1)
- linear response (1)
- long timescales (1)
- master equation (1)
- meshfree basis (1)
- mesoscale spreading process (1)
- mesoscale spreading process, network inference, time-evolving network, romanization spreading, scarce data (1)
- minimum discrimination information (1)
- model reduction (1)
- molecular transition networks (1)
- moleculare dynamics (1)
- nearly completely decomposable (1)
- nearly reducible (1)
- nearly uncoupled Markov chain (1)
- network inference (1)
- neurotransmission (1)
- non-adiabatic processes (1)
- non-linear dynamics (1)
- non-reversible Markov chain (1)
- non-stationary forcing (1)
- nonadiabatic effects (1)
- nonreversible Markov processes (1)
- optimal pathways (1)
- optimal therapeutic policies (1)
- parameter estimation (1)
- peptide aggregation dynamics (1)
- quantum adiabati (1)
- quantum-classical Liouville equation (1)
- quantum-classical molecular dynamics (1)
- quasi-compact operator (1)
- random walk (1)
- ratio of normalizing co (1)
- reaction-diffusion (1)
- reactive trajectories (1)
- recurrence quantification analysis (1)
- representative (1)
- resource-poor (1)
- resource-rich (1)
- reweighting (1)
- romanization spreading (1)
- scarce data (1)
- semigroup of Markov operators (1)
- sensitivity analysis (1)
- slow dynamics (1)
- small noise (1)
- stochastic approximation (1)
- stochastic chemical kinetics (1)
- structural and dynamical similarity (1)
- surface hopping (1)
- tensor decompositions (1)
- tensor train format (1)
- thermodynamic free energy (1)
- threshold (1)
- time series analysis (1)
- time-evolving network (1)
- trans (1)
- transfer operations (1)
- transi (1)
- transition path theory (1)
- transition probabilities (1)
- transition prohability (1)
- two timescale master equation (1)
Institute
- Numerical Mathematics (151)
- Modeling and Simulation of Complex Processes (58)
- ZIB Allgemein (29)
- Visual and Data-centric Computing (23)
- Computational Systems Biology (18)
- Computational Molecular Design (13)
- Visual Data Analysis (13)
- Mathematics for Life and Materials Science (5)
- Bioinformatics in Medicine (3)
- AI in Society, Science, and Technology (1)
We employ the adaptive resolution approach AdResS, in its recently developed Grand Canonicallike version (GC-AdResS) [Wang et al. Phys.Rev.X 3, 011018 (2013)], to calculate the excess chemical potential, $μ^{ex}$, of various liquids and mixtures. We compare our results with those obtained from full atomistic simulations using the technique of thermodynamic integration and show a satisfactory agreement. In GC-AdResS the procedure to calculate $μ^{ex}$ corresponds to the process of standard initial equilibration of the system; this implies that, independently of the specific aim of the study, $μ^{ex}$, for each molecular species, is automatically calculated every time a GC-AdResS simulation is performed.
Inferring Proteolytic Processes from Mass Spectrometry Time Series Data Using Degradation Graphs
(2012)
We present a comprehensive theory for analysis and understanding of transition events between an initial set A and a target set B for general ergodic finite-state space Markov chains or jump processes, including random walks on networks as they occur, e.g., in Markov State Modelling in molecular dynamics. The theory allows us to decompose the probability flow generated by transition events between the sets A and B into the productive part that directly flows from A to B through reaction pathways and the unproductive part that runs in loops and is supported on cycles of the underlying network. It applies to random walks on directed networks and nonreversible Markov processes and can be seen as an extension of Transition Path Theory. Information on reaction pathways and unproductive cycles results from the stochastic cycle decomposition of the underlying network which also allows to compute their corresponding weight, thus characterizing completely which structure is used how often in transition events. The new theory is illustrated by an application to a Markov State Model resulting from weakly damped Langevin dynamics where the unproductive cycles are associated with periodic orbits of the underlying Hamiltonian dynamics.
We investigate the problem of finding modules (or clusters, communities) in directed networks. Until now, most articles on this topic have been oriented towards finding complete network partitions despite the fact that this often is unwanted. We present a novel random walk based approach for non-complete partitions of the directed network into modules in which some nodes do not belong to only one of the modules but to several or to none at all. The new random walk process is reversible even for directed networks but inherits all necessary information about directions and structure of the original network. We demonstrate the performance of the new method in application to a real-world earthquake network.
Before the onset of sprouting angiogenesis, the endothelium is prepatterned for the positioning of tip and stalk cells. Both cell identities are not static, as endothelial cells (ECs) constantly compete for the tip cell position in a dynamic fashion. Here, we show that both bone morphogenetic protein (BMP) 2 and BMP6 are proangiogenic in vitro and ex vivo and that the BMP type I receptors, activin receptor-like kinase (ALK)3 and ALK2, play crucial and distinct roles in this process. BMP2 activates the expression of tip cell–associated genes, such as DLL4 (delta-like ligand 4) and KDR (kinase insert domain receptor), and p38-heat shock protein 27 (HSP27)–dependent cell migration, thereby generating tip cell competence. Whereas BMP6 also triggers collective cell migration via the p38-HSP27 signaling axis, BMP6 induces in addition SMAD1/5 signaling, thereby promoting the expression of stalk cell–associated genes, such as HES1 (hairy and enhancer of split 1) and FLT1 (fms-like tyrosine kinase 1). Specifically, ALK3 is required for sprouting from HUVEC spheroids, whereas ALK2 represses sprout formation. We demonstrate that expression levels and respective complex formation of BMP type I receptors in ECs determine stalk vs. tip cell identity, thus contributing to endothelial plasticity during sprouting angiogenesis. As antiangiogenic monotherapies that target the VEGF or ALK1 pathways have not fulfilled efficacy objectives in clinical trials, the selective targeting of the ALK2/3 pathways may be an attractive new approach.