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Characterizing the structural properties of neural networks is crucial yet poorly understood, and there are no well-established similarity measures between networks. In this work, we observe that neural networks can be represented as…

Machine Learning · Computer Science 2021-06-01 David Pérez-Fernández , Asier Gutiérrez-Fandiño , Jordi Armengol-Estapé , Marta Villegas

Complex systems are difficult to study not only because they are nonlinear, multiscale, and often nonstationary, but because their scientifically relevant organization is often invisible at the level of individual components, pairwise…

Physics and Society · Physics 2026-03-30 Mark M. Bailey

Persistent homology barcodes and diagrams are a cornerstone of topological data analysis that capture the "shape" of a wide range of complex data structures, such as point clouds, networks, and functions. However, their use in statistical…

Algebraic Topology · Mathematics 2024-09-24 Qiquan Wang , Inés García-Redondo , Pierre Faugère , Gregory Henselman-Petrusek , Anthea Monod

Unravelling the block structure of a network is critical for studying macroscopic features and community-level dynamics. The weighted stochastic block model (WSBM), a variation of the traditional stochastic block model, is designed for…

Dynamical Systems · Mathematics 2021-08-04 Wooseok Jung

Complex network theory aims to model and analyze complex systems that consist of multiple and interdependent components. Among all studies on complex networks, topological structure analysis is of the most fundamental importance, as it…

Social and Information Networks · Computer Science 2010-09-15 Bo Yang , Jiming Liu

The promise of discovering a functional blueprint of a cellular system from large-scale and high-throughput sequence and experimental data is predicated on the belief that the same top-down investigative approach that proved successful in…

Molecular Networks · Quantitative Biology 2007-05-23 Riccardo Boscolo , Behnam A. Rezaei , P. Oscar Boykin , Vwani P. Roychowdhury

Topological data analysis uses tools from topology -- the mathematical area that studies shapes -- to create representations of data. In particular, in persistent homology, one studies one-parameter families of spaces associated with data,…

Machine Learning · Computer Science 2020-12-01 Guido Montúfar , Nina Otter , Yuguang Wang

Geometric and structural constraints greatly restrict the selection of folds adapted by protein backbones, and yet, folded proteins show an astounding diversity in functionality. For structure to have any bearing on function, it is thus…

Biological Physics · Physics 2010-04-20 Brinda K. V. , Saraswathi Vishveshwara , Smitha Vishveshwara

Molecular networks guide the biochemistry of a living cell on multiple levels: its metabolic and signalling pathways are shaped by the network of interacting proteins, whose production, in turn, is controlled by the genetic regulatory…

Soft Condensed Matter · Physics 2009-11-07 Sergei Maslov , Kim Sneppen

The relationship between the regulatory design and the functionality of molecular networks is a key issue in biology. Modules and motifs have been associated to various cellular processes, thereby providing anecdotal evidence for…

Molecular Networks · Quantitative Biology 2008-03-04 Jacob Bock Axelsen , Sebastian Bernhardsson , Kim Sneppen

A common feature of biological networks is the geometric property of self-similarity. Molecular regulatory networks through to circulatory systems, nervous systems, social systems and ecological trophic networks, show self-similar…

Molecular Networks · Quantitative Biology 2012-03-09 Simon DeDeo , David C. Krakauer

Persistent topological properties of an image serve as an additional descriptor providing an insight that might not be discovered by traditional neural networks. The existing research in this area focuses primarily on efficiently…

Computer Vision and Pattern Recognition · Computer Science 2023-03-07 Ekaterina Khramtsova , Guido Zuccon , Xi Wang , Mahsa Baktashmotlagh

Networks offer a powerful approach to modeling complex systems by representing the underlying set of pairwise interactions. Link prediction is the task that predicts links of a network that are not directly visible, with profound…

Physics and Society · Physics 2024-04-22 Yijun Ran , Xiao-Ke Xu , Tao Jia

Proteins are essential macromolecules of life and thus understanding their function is of great importance. The number of functionally unclassified proteins is large even for simple and well studied organisms such as baker's yeast. Methods…

Molecular Networks · Quantitative Biology 2008-02-06 Tijana Milenkovic , Natasa Przulj

Persistent homology analysis provides means to capture the connectivity structure of data sets in various dimensions. On the mathematical level, by defining a metric between the objects that persistence attaches to data sets, we can…

Machine Learning · Computer Science 2019-06-12 Henri Riihimäki , José Licón-Saláiz

Most real-world networks are embedded in latent geometries. If a node in a network is found in the vicinity of another node in the latent geometry, the two nodes have a disproportionately high probability of being connected by a link. The…

Physics and Society · Physics 2024-06-19 Bukyoung Jhun

Recently, persistent homology has had tremendous success in biomolecular data analysis. It works by examining the topological relationship or connectivity of a group of atoms in a molecule at a variety of scales, then rendering a family of…

Biomolecules · Quantitative Biology 2019-03-27 David Bramer , Guo-Wei Wei

Allosteric regulation in proteins is often accompanied by conformational changes that facilitate transmission of mechanical signals between distant ligand binding sites. Typically, these deformations are classified in terms of specific…

Soft Condensed Matter · Physics 2024-01-26 Jason W. Rocks , Eleni Katifori , Andrea J. Liu

Interactions between units in phyical, biological, technological, and social systems usually give rise to intrincate networks with non-trivial structure, which critically affects the dynamics and properties of the system. The focus of most…

Data Analysis, Statistics and Probability · Physics 2007-05-23 R. Guimera , M. Sales-Pardo , L. A. N. Amaral

Hyperuniformity refers to the suppression of density fluctuations at large scales. Typical for ordered systems, this property also emerges in several disordered physical and biological systems, where it is particularly relevant to…

Statistical Mechanics · Physics 2025-02-24 Abel H. G. Milor , Marco Salvalaglio