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Coarse-grained topology estimation via graph sampling
2012
Proceedings of the 2012 ACM workshop on Workshop on online social networks - WOSN '12
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In this paper, we show how to efficiently estimate the category graph from a probability sample of nodes. We prove consistency of our estimators and evaluate their efficiency via simulation. ...
., countries or universities in OSNs), which naturally defines a weighted category graph i.e., a coarse-grained version of the underlying network. ...
Using these weights in conjunction with the WIS estimators above allows for consistent estimation of coarse-grained topology from random walk samples. ...
doi:10.1145/2342549.2342556
dblp:conf/wosn/KurantGWABM12
fatcat:gnosv2nlsngbfdxm2nwmnhio7e
Coarse-Grained Topology Estimation via Graph Sampling
[article]
2011
arXiv
pre-print
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In this paper, we show how to efficiently estimate the coarse-grained topology of a graph from a probability sample of nodes. ...
However, less is known about estimating the global topology of the underlying graph. ...
Using these weights in conjunction with the WIS estimators above allows for consistent estimation of coarse-grained topology from random walk samples. ...
arXiv:1105.5488v1
fatcat:vsso5a4p7bb6tlawjn65q2keyi
Sampling Rare Conformational Transitions with a Quantum Computer
[article]
2022
arXiv
pre-print
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Path sampling methods like Transition Path Sampling hold the great promise of focusing the available computational power on sampling the rare stochastic transition between metastable states. ...
We show that the quantum computing step generates uncorrelated trajectories, thus facilitating the sampling of the transition region in configuration space. ...
We leverage on this development by integrating sampling via a quantum annealer into our classical-hybrid scheme, in order to generate realistic ensembles of coarse-grained transition pathways I. ...
arXiv:2201.11781v2
fatcat:xlcprhfnh5f27p2ixcpdn5dvye
Predicting RNA 3D structure using a coarse-grain helix-centered model
2015
RNA: A publication of the RNA Society
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Our coarse-grained, helix-based, tertiary structure model operates with only a few degrees of freedom compared with all-atom models while preserving the ability to sample tertiary structures given a secondary ...
We propose that given the wide range of conformational space that needs to be explored, a coarse-grain approach can explore more conformations in less iterations than an all-atom model coupled to a finegrain ...
We first introduce a coarse-grained graph that captures the main structural elements of an RNA structure. ...
doi:10.1261/rna.047522.114
pmid:25904133
pmcid:PMC4436664
fatcat:o55gtu6utbbqpelavvcolbhe64
Learning Multi-Granular Spatio-Temporal Graph Network for Skeleton-based Action Recognition
[article]
2021
arXiv
pre-print
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To address the aforementioned problems, we propose a novel multi-granular spatio-temporal graph network for skeleton-based action classification that jointly models the coarse- and fine-grained skeleton ...
Existing approaches typically employ a single neural representation for different motion patterns, which has difficulty in capturing fine-grained action classes given limited training data. ...
However, both the RNNs and CNNs have difficulty in capturing the skeleton topology which are naturally of a graph structure. ...
arXiv:2108.04536v1
fatcat:yjzuazukyrbdrlimtlkopjz6bm
MDM-TASK-web: A web platform for protein dynamic residue networks and modal analysis
[article]
2021
bioRxiv
pre-print
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Upgrades and new functionalities to these software suites have also been introduced via the web server. ...
MODE-TASK MODE-TASK enables the calculation of protein ED, and the estimation of normal modes from coarse-grained static proteins under the assumptions of the elastic network model . ...
Figure 1 : 1 Extracts from the MDM-TASK-web interface, showing (a) a coarse-grained viral capsid pentamer, (b) the normal mode quiver plot for the coarse-grained pentamer, (c) a weighted residue contact ...
doi:10.1101/2021.01.29.428734
fatcat:tcq6d4o2w5exvatb673f7un4oq
Reconstructing functional brain networks: have we got the basics right?
2014
Frontiers in Human Neuroscience
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The spatial sampling implicitly leads to a coarse graining of the dynamics, introducing a spatial scale irrespective of the actual system organization, resulting in spatial correlations in the topology ...
A node is a drastically coarse-grained representation of an object, identifying it to a structureless point, in a way similar to the reduction of a whole mechanical system to its center of mass, allowed ...
doi:10.3389/fnhum.2014.00107
pmid:24578687
pmcid:PMC3936558
fatcat:dqrlcdallncxpc3oszoexrugmq
Computational approaches to RNA structure prediction, analysis, and design
2011
Current Opinion in Structural Biology
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Here, we review recent advances in RNA folding algorithms, RNA tertiary motif discovery, applications of graph theory approaches to RNA structure and function, and in silico generation of RNA sequence ...
Other coarse-grained models such as recently presented by Fresllsen et al. ...
The web-based program iFoldRNA by the Dokholyan group [13] predicts RNA structures using a coarse-grained model of three beads per nucleotide through molecular dynamics (MD) sampling (by the replica ...
doi:10.1016/j.sbi.2011.03.015
pmid:21514143
pmcid:PMC3112238
fatcat:rgqhbrxvkndrvdl6io7ew7rn24
Deformation-driven topology-varying 3D shape correspondence
2015
ACM Transactions on Graphics
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Our deformation model, called GeoTopo transform, allows both geometric and topological operations such as part split, duplication, and merging, leading to fine-grained and piecewise continuous correspondence ...
Driven by the combined deformation energy, an optimal shape correspondence is obtained via a pruned beam search. ...
This is achieved by encoding the fine-grained part correspondence between all pairs of shapes into a large correspondence matrix and then extracting from the matrix a sparse correspondence via graph clustering ...
doi:10.1145/2816795.2818088
fatcat:43umbdujyvbvhbf3gx6xhbmefu
Graph Representation Learning via Graphical Mutual Information Maximization
[article]
2020
arXiv
pre-print
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GMI generalizes the idea of conventional mutual information computations from vector space to the graph domain where measuring mutual information from two aspects of node features and topological structure ...
can be efficiently estimated and maximized by current mutual information estimation methods such as MINE; Finally, our theoretical analysis confirms its correctness and rationality. ...
However, DGI implements a coarse-grained maximization (i.e., maximizing MI at graph/patch-level) which makes it difficult to preserve the delicate information in the input graph. ...
arXiv:2002.01169v1
fatcat:lburokr27jbdfowwgv2opovrd4
Wavelet-accelerated Monte Carlo sampling of polymer chains
2005
Journal of Polymer Science Part B: Polymer Physics
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In this article, we highlight a new topological coarse-graining method capable of preserving structural information about polymer chains across a range of length scales and sampling con- figurations on ...
This gives the WAMC approach additional flexibility not typically found in existing topological coarse-graining techni- ques. ...
doi:10.1002/polb.20382
fatcat:e7qtbtyzh5cvdij6ek4ypqff2y
Efficient Traversal of Beta-Sheet Protein Folding Pathways Using Ensemble Models
[chapter]
2011
Lecture Notes in Computer Science
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We use tFolder to sample the β-sheet conformational landscape and build a coarse-grain model of the energy landscape. ...
This simplification enable us to sample intermediate structures and build a coarse-grained model of the energy landscape and subsequently simulate folding processes. ...
doi:10.1007/978-3-642-20036-6_38
fatcat:gq3osypjezgkpkrxjv37fdgybe
Data-driven discovery of cardiolipin-selective small molecules by computational active learning
2022
Chemical Science
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We present a data-driven approach combining deep learning-enabled active learning with coarse-grained simulations and alchemical free energy calculations to discover small molecules to selectively permeate ...
Because transferable coarse-grained models rely on a nite set of interaction types, many molecules map to the same coarsegrained representation. 25 The accuracy and transferability of our coarse-grained ...
Lastly, our trained model allows us to extrapolatively predict CL selectivity of unseen and arbitrarily large CG topologies via a decomposition into learned contributions of their constituent 1-5 bead ...
doi:10.1039/d2sc00116k
pmid:35656132
pmcid:PMC9019913
fatcat:zyquwosbujhgxaxkfgjhqs4koe
Topological Analysis of Traffic Pace via Persistent Homology
2020
Journal of Physics: Complexity
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We implement this as a preprocessing step prior to our main persistent homology analysis in order to coarse-grain small topological structures. ...
We develop a topological analysis of robust traffic pace patterns using persistent homology. ...
is to the sampling noise via a barcode [Ghr08] . ...
doi:10.1088/2632-072x/abc96a
fatcat:kzizy7hivrcr5nla45tupk2kcm
Multiscale network renormalization: scale-invariance without geometry
[article]
2021
arXiv
pre-print
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Here we introduce a graph renormalization scheme valid for any hierarchy of coarse-grainings, thereby allowing for the definition of 'block-nodes' across multiple scales. ...
Systems with lattice geometry can be renormalized exploiting their coordinates in metric space, which naturally define the coarse-grained nodes. ...
Nodes of an l-graph A (l) (left) are grouped together, via a given partition Ω l , to form the block-nodes of the coarse-grained (l+1)-graph A (l+1) (right). ...
arXiv:2009.11024v2
fatcat:ssm3yfldnrd4nbb4vpmqnsotja
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