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We present the spectrum of the (normalized) graph Laplacian as a systematic tool for the investigation of networks, and we describe basic properties of eigenvalues and eigenfunctions. Processes of graph formation like motif joining or…

Adaptation and Self-Organizing Systems · Physics 2012-10-19 Anirban Banerjee , Jürgen Jost

A GraphMaps is a system that visualizes a graph using zoom levels, which is similar to a geographic map visualization. GraphMaps reveals the structural properties of the graph and enables users to explore the graph in a natural way by using…

Computational Geometry · Computer Science 2018-08-14 Debajyoti Mondal , Lev Nachmanson

Graphs are central to the chemical sciences, providing a natural language to describe molecules, proteins, reactions, and industrial processes. They capture interactions and structures that underpin materials, biology, and medicine. This…

Graph drawings are useful tools for exploring the structure and dynamics of data that can be represented by pair-wise relationships among a set of objects. Typical real-world social, biological or technological networks exhibit high…

Social and Information Networks · Computer Science 2018-07-05 Christian Schulz

Graph representations offer powerful and intuitive ways to describe data in a multitude of application domains. Here, we consider stochastic processes generating graphs and propose a methodology for detecting changes in stationarity of such…

Machine Learning · Computer Science 2021-02-11 Daniele Zambon , Cesare Alippi , Lorenzo Livi

Graphs are ubiquitous data structures for representing interactions between entities. With an emphasis on the use of graphs to represent chemical molecules, we explore the task of learning to generate graphs that conform to a distribution…

Machine Learning · Computer Science 2019-03-08 Qi Liu , Miltiadis Allamanis , Marc Brockschmidt , Alexander L. Gaunt

Graphs are a useful abstraction of image content. Not only can graphs represent details about individual objects in a scene but they can capture the interactions between pairs of objects. We present a method for training a convolutional…

Computer Vision and Pattern Recognition · Computer Science 2018-03-28 Alejandro Newell , Jia Deng

Estimating the influence that individual nodes have on one another in a Boolean network is essential to predict and control the system's dynamical behavior, for example, detecting key therapeutic targets to control pathways in models of…

Physics and Society · Physics 2023-11-02 Thomas Parmer , Filippo Radicchi

The purpose of this paper is to give an introduction to the field of Schema Theory written by a mathematician and for mathematicians. In particular, we endeavor to to highlight areas of the field which might be of interest to a…

Neural and Evolutionary Computing · Computer Science 2021-09-01 David White

Graph association rule mining is a data mining technique used for discovering regularities in graph data. In this study, we propose a novel concept, {\it path association rule mining}, to discover the correlations of path patterns that…

Databases · Computer Science 2022-10-25 Yuya Sasaki

Bifurcation diagram is a powerful tool that visually gives information about the behavior of the equilibrium points of a dynamical system respect to the varying parameter. This paper proposes an educational algorithm by which the local…

Dynamical Systems · Mathematics 2021-05-25 Shahram Aghaei , Abolghasem Daeichian

Pathway enrichment analysis has become a key tool for biomedical researchers to gain insight into the underlying biology of differentially expressed genes, proteins and metabolites. It reduces complexity and provides a system-level view of…

Methodology · Statistics 2016-06-24 Jing Ma , Ali Shojaie , George Michailidis

Bigraphs are a versatile modelling formalism that allows easy expression of placement and connectivity relations in a graphical format. System evolution is user defined as a set of rewrite rules. This paper presents a practical, yet…

Logic in Computer Science · Computer Science 2024-06-03 Blair Archibald , Muffy Calder , Michele Sevegnani

Biological processes underlying the basic functions of a cell involve complex interactions between genes. From a technical point of view, these interactions can be represented through a graph where genes and their connections are,…

Methodology · Statistics 2020-11-24 Thi Kim Hue Nguyen , Monica Chiogna

Graph are a ubiquitous data representation, as they represent a flexible and compact representation. For instance, the 3D structure of RNA can be efficiently represented as $\textit{2.5D graphs}$, graphs whose nodes are nucleotides and…

Machine Learning · Computer Science 2021-09-21 Vincent Mallet , Carlos G. Oliver , William L. Hamilton

Understanding large molecular networks consisting of entities such as genes, proteins or RNAs that interact in complex ways to drive the cellular machinery has been an active focus of systems biology. Computational approaches have played a…

Molecular Networks · Quantitative Biology 2013-04-23 Sriganesh Srihari , Mark A. Ragan

A critical task in systems biology is the identification of genes that interact to control cellular processes by transcriptional activation of a set of target genes. Many methods have been developed to use statistical correlations in…

Quantitative Methods · Quantitative Biology 2010-11-24 Adam A. Margolin , Kai Wang , Andrea Califano , Ilya Nemenman

Complexity in biology is often described using a multi-map architecture, where the genotype, representing the encoded information, is mapped to the functional level, known as the phenotype, which is then connected to a latent phenotype we…

Other Quantitative Biology · Quantitative Biology 2024-02-06 Juan F Poyatos

Gene Regulatory Networks are networks of interactions in biological organisms responsible for determining the production levels of proteins and peptides. Proteins are workers of a cell factory, and their production defines the goal of a…

Neural and Evolutionary Computing · Computer Science 2022-09-12 Iliya Miralavy , Wolfgang Banzhaf

Graphs are fundamental data structures which concisely capture the relational structure in many important real-world domains, such as knowledge graphs, physical and social interactions, language, and chemistry. Here we introduce a powerful…

Machine Learning · Computer Science 2018-03-12 Yujia Li , Oriol Vinyals , Chris Dyer , Razvan Pascanu , Peter Battaglia