25 papers · ranked by Valyu relevance
Paolo Finotelli, Carlo Piccardi, Edie Miglio, Paolo Dulio
In this paper, we propose a graphlet-based topological algorithm for the investigation of the brain network at resting state (RS). To this aim, we model the brain as a graph, where (labeled) nodes correspond to specific cerebral areas and links are weighted connections determined by the intensity of the functional…
Ine Melckenbeeck, Pieter Audenaert, Tom Michoel, Didier Colle + 2 more
'Mario Pickavet' 'Yongtang Shi'] Graphlets are small subgraphs, usually containing up to five vertices, that can be found in a larger graph. Identification of the graphlets that a vertex in an explored graph touches can provide useful information about the local structure of the graph around that vertex. Actually…
Sam F. L. Windels, Noël Malod-Dognin, Nataša Pržulj
Laplacian matrices capture the global structure of networks and are widely used to study biological networks. However, the local structure of the network around a node can also capture biological information. Local wiring patterns are typically quantified by counting how often a node touches different graphlets (small…
Pramesh Singh, Hannah Kuder, Anna Ritz
Higher-order interaction patterns among proteins have the potential to reveal mechanisms behind molecular processes and diseases. While clustering methods are used to identify functional groups within molecular interaction networks, these methods largely focus on edge density and do not explicitly take into…
David Aparício, Pedro Ribeiro, Fernando Silva
Networks are widely used to model real-world systems and uncover their topological features. Network properties such as the degree distribution and shortest path length have been computed in numerous realworld networks, and most of them have been shown to be both scale-free and small-world networks. Graphlets and…
Daniel Tello Velasco, Sam F. L. Windels, Mikhail Rotkevich, Noël Malod-Dognin + 1 more
Spatial Analysis of Functional Enrichment (SAFE) is a popular tool for biologists to investigate the functional organisation of biological networks via highly intuitive 2D functional maps. To create these maps, SAFE uses Spring embedding to project a given network into a 2D space in which nodes connected in the network…
Mingshan Jia, Maité Van Alboom, Liesbet Goubert, Piet Bracke + 3 more
'Bogdan Gabrys' 'Katarzyna Musial' 'Lun Hu'] Graph embedding approaches have been attracting increasing attention in recent years mainly due to their universal applicability. They convert network data into a vector space in which the graph structural information and properties are maximumly preserved. Most existing…
Nesreen K. Ahmed, Jennifer Neville, Ryan A. Rossi, Nick Duffield + 1 more
'Theodore L. Willke'] Abstract. From social science to biology, numerous applications often rely on graphlets for intuitive and meaningful characterization of networks at both the global macro-level as well as the local micro-level. While graphlets have witnessed a tremendous success and impact in a variety of domains…
Pinar Yanardag, S. V. N. Vishwanathan
A commonly used paradigm for representing graphs is to use a vector that contains normalized frequencies of occurrence of certain motifs or sub-graphs. This vector representation can be used in a variety of applications, such as, for computing similarity between graphs. The graphlet kernel of Shervashidze et al. [32]…
Ryan A. Rossi, Nesreen K. Ahmed, Aldo Carranza, David Arbour + 3 more
'Anup Rao' 'Sungchul Kim' 'Eunyee Koh'] In this paper, we introduce a generalization of graphlets to heterogeneous networks called typed graphlets. Informally, typed graphlets are small typed induced subgraphs. Typed graphlets generalize graphlets to rich heterogeneous networks as they explicitly capture the…
Ine Melckenbeeck, Pieter Audenaert, Thomas Van Parys, Yves Van De Peer + 2 more
Background Graphlets are useful for bioinformatics network analysis. Based on the structure of Hočevar and Demšar’s ORCA algorithm, we have created an orbit counting algorithm, named Jesse. This algorithm, like ORCA, uses equations to count the orbits, but unlike ORCA it can count graphlets of any order. To do so, it…
Altaf Barelvi, Oliver Anderson, Anna Ritz
Graphs are powerful tools for modeling and analyzing molecular interaction networks. Graphs typically represent either undirected physical interactions or directed regulatory relationships, which can obscure a particular protein’s functional context. Graphlets can describe local topologies and patterns within graphs…
G Hriday, Pranav Saikiran Sista, Apurba Das
Graphlet counting is an important problem as it has numerous applications in several fields, including social network analysis, biological network analysis, transaction network analysis, etc. Most of the practical networks are dynamic. A graphlet is a subgraph with a fixed number of vertices and can be induced or…
M. Kaan Arici, Nurcan Tuncbag
Omics technologies are powerful tools for detecting dysregulated and altered signaling components in various contexts, encompassing disease states, patients, and drug-perturbations. Network inference or reconstruction algorithms play an integral role in the successful analysis and identification of causal relationships…
Altaf Barelvi, Oliver Anderson, Anna Ritz, Mingfu Shao
Graphs are powerful tools for computationally representing complex biological networks (, , , ), and are effective in identifying differences between healthy and disease states in organisms (). Biological networks can take many forms, and researchers often study networks with isolated interaction types. Some of the…
Xiaowei Chen, Yongkun Li, Pinghui Wang, John C. S. Lui
Graphlets are induced subgraph patterns and have been frequently applied to characterize the local topology structures of graphs across various domains, e.g., online social networks (OSNs) and biological networks. Discovering and computing graphlet statistics are highly challenging. First, the massive size of…
Arzu Burcak Sonmez, Tolga Can
Background Analysis of integrated genome-scale networks is a challenging problem due to heterogeneity of high-throughput data. There are several topological measures, such as graphlet counts, for characterization of biological networks. Results In this paper, we present methods for counting small sub-graph patterns in…
Ryan A. Rossi, Nesreen K. Ahmed, Aldo Carranza, David Arbour + 3 more
'Anup Rao' 'Sungchul Kim' 'Eunyee Koh'] Many real-world applications give rise to large heterogeneous networks where nodes and edges can be of any arbitrary type (e.g., user, web page, location). Special cases of such heterogeneous graphs include homogeneous graphs, bipartite, k-partite, signed, labeled graphs, among…
Lionel Zoubritzky, François-Xavier Coudert
We present here an open-source Julia library for the topological identification of crystalline materials, with algorithmic and computational improvements over the previously available software in the field, resulting in a speed increase of one order of magnitude. This new algorithm and implementation can therefore be…
Authors not listed
Computational methods for predictive modeling have been increasingly utilized in the early stages of drug discovery to supplement high-throughput screening. The advent of highly efficient and complex machine learning architectures necessitates new methods of collating the plethora of topological, geometrical, and…
Authors not listed
Genetic Algorithms are a powerful method to solve optimization problems with complex cost functions over vast search spaces that rely in particular on recombining parts of previous solutions. Crossover operators play a crucial role in this context. Here, we describe a large class of these operators designed for…
Caitlin C. Bannan, David Mobley
Force fields are used in a variety of research fields including computer-aided drug design, biomaterials, and polymer chemistry. However, force fields also continue to limit the accuracy of predictions of physical properties. Current parameterization of these force fields involves a huge amount of human effort -- often…
Tom C. Freeman, Sebastian Horsewell, Anirudh Patir, Josh Harling-Lee + 5 more
Quantitative and qualitative data derived from the analysis of genomes, genes, proteins or metabolites from tissue or cells are currently generated in huge volumes during biomedical research. Graphia is an open-source platform created for the graph-based analysis of such complex data, e.g. transcriptomics, proteomics…
Jonas Schaub, Julian Zander, Achim Zielesny, Christoph Steinbeck
The concept of molecular scaffolds as defining core structures of organic molecules is utilised in many areas of chemistry and cheminformatics, e.g. drug design, chemical classification, or the analysis of high-throughput screening data. Here, we present Scaffold Generator, a comprehensive open library for the…
Authors not listed
We present a unified, set–theoretic framework that extends molecular graphs to hypergraphs and superhypergraphs via iterated power sets. We define Molecular Graphs, Molecular HyperGraphs, and Molecular SuperHyperGraphs, and develop four complements over them: Weighted, Rough, Neural, and Multipolar frameworks. We prove…