26 papers · ranked by Valyu relevance
Young-Joon Park, Dong-Kyu Lee, Tien-Cuong Bui
Analyzing large graph data is an essential part of many modern applications, such as social networks. Due to its large computational complexity, distributed processing is frequently employed. This requires graph data to be divided across nodes, and the choice of partitioning strategy has a great impact on the execution…
Jie Cao, Haoxiang Wang, Jingru Jiao, Kekun Hu + 1 more
With the rapid expansion of social networks, efficiently mining and analyzing massive graph data has become a fundamental challenge in social network research. Graph partitioning plays a pivotal role in enhancing the performance of such analyses. However, conventional graph partitioning methods predominantly rely on…
Milad Rezaei Hajidehi, Sraavan Sridhar, Margo Seltzer
Ubiquity and massive growth of real-world networks sparked the applications of distributed graph processing. A graph is a common data model that can represent complex relationships between real-world entities in myriad domains such as social networks, the World Wide Web, finance, fraud detection, transportation, and…
B. Kaan Karamete, Louaï Adhami, Eli Glaser
A distributed graph database architecture that co-exists with the distributed relational DB for I/O and atscale OLAP expression support with hundreds of PostGIS compatible geometry functions will be discussed in this article. The uniqueness of this implementation stems mainly from its double link topology structure for…
Amin Sahebi, Marco Barbone, Marco Procaccini, Wayne Luk + 2 more
'Georgi Gaydadjiev' 'Roberto Giorgi'] Processing large-scale graphs is challenging due to the nature of the computation that causes irregular memory access patterns. Managing such irregular accesses may cause significant performance degradation on both CPUs and GPUs. Thus, recent research trends propose graph…
Qiushi Liang, Shengjie Zhao, Lingxi Chen, Shuai Cheng Li
Entropy quantifies the limits of information compression and provides a theoretical foundation for exploring complex structures in large-scale graphs. However, effective metrics are needed to capture the intricate structural details in biological graphs. In this paper, we introduce the topology entropy encoding tree to…
Fawaz Dabbaghie
The representation of genomes and genomic sequences through graph structures has undergone a period of rapid development in recent years, particularly to accommodate the growing size of genome sequences that are being produced. Genome graphs have been employed extensively for a variety of purposes, including assembly…
Christine Farrugia, Paola Galdi, Irati Arenzana Irazu, Kenneth Scerri + 1 more
In this work, we take a closer look at the Vogt-Bailey (VB) index, proposed in Ref. [1] as a tool for studying local functional homogeneity in the human cortex. We interpret the VB index in terms of the minimum ratio cut, a weighted graph cut that indicates whether a network can easily be disconnected into two parts…
Oleg Kruglov, Anna Mastikhina, Oleg Senkevich, Dmitry Sirotkin + 1 more
'Stanislav Moiseev'] Recently, the use of large graphs has become increasingly popular in various real-world applications, including web and social network services, as well as machine learning and data mining algorithms. In order to perform distributed graph computing on clusters with multiple machines or servers, the…
Zezhong Ding, Yongan Xiang, Shangyou Wang, Xike Xie + 1 more
Partitioning Authors: ['Zezhong Ding' 'Yongan Xiang' 'Shangyou Wang' 'Xike Xie' 'S. Kevin Zhou'] In the realm of distributed systems tasked with managing and processing large-scale graph-structured data, optimizing graph partitioning stands as a pivotal challenge. The primary goal is to minimize communication overhead…
Nikolai Merkel, Ruben Mayer, Tawkir Ahmed Fakir, Hans‐Arno Jacobsen
—For distributed graph processing on massive graphs, a graph is partitioned into multiple equally-sized parts which are distributed among machines in a compute cluster. In the last decade, many partitioning algorithms have been developed which differ from each other with respect to the partitioning quality, the…
Felix Teufel, Magnús Halldór Gíslason, José Juan Almagro Armenteros, Alexander Rosenberg Johansen + 2 more
'José Juan Almagro\xa0Armenteros' 'Alexander\xa0Rosenberg Johansen' 'Ole Winther' 'Henrik Nielsen'] Title: Abstract When splitting biological sequence data for the development and testing of predictive models, it is necessary to avoid too-closely related pairs of sequences ending up in different partitions. If this is…
Anna Mastikhina, Oleg Senkevich, Dmitry Sirotkin, Danila Demin + 1 more
using a novel metric Authors: ['Anna Mastikhina' 'Oleg Senkevich' 'Dmitry Sirotkin' 'Danila Demin' 'Stanislav Moiseev'] This paper examines the graph partition problem and introduces a new metric, MSIDS (maximal sum of inner degrees squared). We establish its connection to the replication factor (RF) optimization…
Deepak Maurya, Balaraman Ravindran, Ilya Safro
Hypergraphs have gained increasing attention in the machine learning community lately due to their superiority over graphs in capturing super-dyadic interactions among entities. In this work, we propose a novel approach for the partitioning of k-uniform hypergraphs. Most of the existing methods work by reducing the…
Zhenqin Wu, Ayano Kondo, Monee McGrady, Ethan A. G. Baker + 10 more
Spatial transcriptomic and proteomic measurements enable high-dimensional characterization of tissues. However, understanding organizations of cells at different spatial scales and extracting tissue structures of interest remain challenging tasks that require extensive human annotations. To address this need for…
Seyed Ardalan Ghoreishi, Aleksandra Weronika Szmigiel, James Nagai, Ivan G. Costa + 2 more
Single-cell RNA sequencing (scRNA-seq) is widely used to resolve cellular heterogeneity across thousands to millions of cells. A major challenge is to identify biologically meaningful cell populations while preserving their hierarchical organization, because broad cell types frequently split into more specialized…
Samuel Barton, Zoe Broad, Daniel Ortiz-Barrientos, Diane Donovan + 1 more
Multidisciplinary approaches can significantly advance our understanding of complex systems. For instance, gene co-expression networks align prior knowledge of biological systems with studies in graph theory, emphasising pairwise gene to gene interactions. In this paper, we extend these ideas, promoting hypergraphs as…
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…
Authors not listed
The Polytope Formalism provides a rigorous and unifying mathematical framework for representing all possible molecular configurations and their interrelationships. Extending its application from stereoisomerism to molecular constitution reveals that both arise from a common structural foundation linking discrete and…
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…
Michael Hutcheon, Andrew Teale
Algorithms are presented for performing a topological analysis of an arbitrary function, evaluated on an arbitrary grid of points. These algorithms work strictly by post-processing the data and require no additional function evaluations. This is achieved by connecting the grid points with a neighbourhood graph…
Wilfried Agbeto, Camille Coti, Vladimir Reinharz
Subgraph isomorphism is a fundamental combinatorial problem that involves finding one or more occurrences of a pattern graph within a target graph. It arises in a wide range of application domains, including biology, chemistry, social network analysis, and pattern recognition. Although subgraph isomorphism is…
Authors not listed
Digital twins are virtual companions for the design, scale-up, and control of chemical processes. Equipping digital twins with mechanistic models of their mirrored unit operation expands their range of applicability compared to pure data-driven models. As constructing mechanistic models requires time, effort, and…
Wilfried Agbeto, Camille Coti, Vladimir Reinharz
Advances in graph algorithmics have allowed in-depth study of many natural objects from molecular biology or chemistry to social networks. Particularly in molecular biology and cheminformatics, understanding complex structures by identifying conserved sub-structures is a key milestone towards the artificial design of…
Michael Hutcheon, Andrew Teale
Algorithms are presented for performing a topological analysis of an arbitrary function, evaluated on an arbitrary grid of points. These algorithms work strictly by post-processing the data and require no additional function evaluations. This is achieved by connecting the grid points with a neighbourhood graph…
Authors not listed
A directed graph (or digraph) consists of a finite vertex set 𝑉 and a set of ordered edges 𝐸 ⊆ 𝑉 × 𝑉, each edge (𝑢, 𝑣) indicating a one-way connection from 𝑢 (source) to 𝑣 (target). A bidirected graph is a generalization of an undirected graph where each edge is assigned a direction at each of its endpoints…