26 papers · ranked by Valyu relevance
Nibedita Behera, Ashwina Kumar, Chougule, Atharva + 3 more
With the growth of unstructured and semistructured data, parallelization of graph algorithms is inevitable for efficiency. Unfortunately, due to the inherent irregularity of computation, memory access, and communication, graph algorithms are traditionally challenging to parallelize. To tame this challenge, several…
Belgin Ergenç Bostanoğlu, Nourhan Abuzayed, Bilal Alatas
Frequent subgraph mining (FSM) is an essential and challenging graph mining task used in several applications of the modern data science. Some of the FSM algorithms have the objective of finding all frequent subgraphs whereas some of the algorithms focus on discovering frequent subgraphs approximately. On the other…
Faraz Zaidi, Chris Muelder, Arnaud Sallaberry
| Title: | Analysis and Visualization of Dynamic Networks | | --- | --- | | Name: | Faraz Zaidi1 , Chris Muelder2 , Arnaud Sallaberry3 | | Affil./Addr. 1: | College of Computing and Information Sciences, Karachi Institute | | | of Economics and Technology (KIET), Karachi, Pakistan | | | faraz@pafkiet.edu.pk | |…
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…
Benjamin Schiller, Clemens Deusser, Jeronimo Castrillon, Thorsten Strufe
'Thorsten Strufe'] Graphs are used to model a wide range of systems from different disciplines including social network analysis, biology, and big data processing. When analyzing these constantly changing dynamic graphs at a high frequency, performance is the main concern. Depending on the graph size and structure…
Ya Ting Hu, Michael Burch, Huub van de Wetering
In this paper, an overview-based interactive visualization for temporally long dynamic data sequences is described. To reach this goal, each data object at a certain time point can be mapped to a number value based on a given property. Among others, a property is application-dependent and can be number of vertices…
SoYoung Park, HyeWon Lee, Sungsu Lim, Carlos Fernandez-Lozano
Understanding and predicting outcomes in complex real-world systems necessitates robust multivariate time series pattern analysis. Advanced techniques, such as dynamic graph neural networks, have shown significant efficacy for these tasks. However, existing approaches often overlook the inherent periodicity in data…
Megha Tyagi, Deepak Garg
Dynamically changing graphs are used in many applications of graph algorithms. The scope of these graphs are in graphics, communication networks and in VLSI designs where graphs are subjected to change, such as addition and deletion of edges and vertices. There is a rich body of the algorithms and data structures used…
Bahar Alipanahi, Alan Kuhnle, Simon J. Puglisi, Leena Salmela + 1 more
The de Bruijn graph is one of the fundamental data structures for analysis of high throughput sequencing data. In order to be applicable to population-scale studies, it is essential to build and store the graph in a space- and time-efficient manner. In addition, due to the ever-changing nature of population studies, it…
Ahmet Ay, Dihong Gong, Tamer Kahveci
Background Gene regulatory networks describe the interplay between genes and their products. These networks control almost every biological activity in the cell through interactions. The hierarchy of genes in these networks as defined by their interactions gives important insights into how these functions are governed.…
Most Tahmina Rahman, Mohammad Al Olaimat, Serdar Bozdag
Electronic Health Records (EHRs) contain vast amounts of longitudinal patient medical history data, making them highly informative for early disease prediction. Numerous computational methods have been developed to leverage EHR data; however, many process multiple patient records simultaneously, resulting in high…
Kathryn Gray, Mingwei Li, Reyan Ahmed, Stephen Kobourov
Evolving trees arise in many real-life scenarios from computer file systems and dynamic call graphs, to fake news propagation and disease spread. Most layout algorithms for static trees do not work well in an evolving setting (e.g., they are not designed to be stable between time steps). Dynamic graph layout algorithms…
Qian Chang, Li Xia, Xi-Ming Cheng
In this work, we propose Graph Retention Network (GRN) as a unified architecture for deep learning on dynamic graphs. The GRN extends the core computational manner of retention to dynamic graph data as graph retention, which empowers the model with three key computational paradigms that enable training parallelism…
Kathrin Hanauer, Monika Henzinger, Christof Schulz
In recent years, significant advances have been made in the design and analysis of fully dynamic algorithms. However, these theoretical results have received very little attention from the practical perspective. Few of the algorithms are implemented and tested on real datasets, and their practical potential is far from…
Malte Skambath, Till Tantau
While the algorithmic drawing of static trees is well-understood and well-supported by software tools, creating animations depicting how a tree changes over time is currently difficult: software support, if available at all, is not integrated into a document production workflow and algorithmic approaches only rarely…
Jarno Alanko, Bahar Alipanahi, Jonathen Settle, Christina Boucher + 1 more
The de Bruijn graph has become a ubiquitous graph model for biological data ever since its initial introduction in the later 1990s. It has been used for a variety of purposes including genome assembly (51; 8; 44), variant detection (2; 31), and storage of assembled genomes (15). For this reason, there have been over a…
Youcef Abdelsadek, Kamel Chelghoum, Francine Herrmann, Imed Kacem + 1 more
'Benoît Otjacques'] Understanding the information behind social relationships represented by a network is very challenging, especially, when the social interactions change over time inducing updates on the network topology. In this context, this paper proposes an approach for analysing dynamic social networks, more…
Jordan M. Eizenga, Adam M. Novak, Emily Kobayashi, Flavia Villani + 6 more
Pangenomics is a growing field within computational genomics. Many pangenomic analyses use bidirected sequence graphs as their core data model. However, implementing and correctly using this data model can be difficult, and the scale of pangenomic data sets can be challenging to work at. These challenges have impeded…
Alexander Smith, Spencer Runde, Alex Chew, Atharva Kelkar + 3 more
Molecular dynamics (MD) simulations are used in diverse scientific and engineering fields such as drug discovery, materials design, separations, biological systems, and reaction engineering. These simulations generate highly complex datasets that capture the 3D spatial positions, dynamics, and interactions of thousands…
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…
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…
Trevor Gokey, David L. Mobley
Molecular mechanics force fields require a chemical perception model to assign parameters to molecules. A recent advancement in force fields is the use of the SMARTS substructure query language as the perception model. Although it is straightforward to write SMARTS patterns to define new force field parameters, it is…
Authors not listed
Background: Chemical reactions form intricate, highly connected networks whose exploration is essential for discovering more efficient and sustainable synthetic routes. As reaction data from literature, patents, and high‑throughput experimentation continue to surge, so does the need for tools that can collectively…
Michael Statt, Brian Rohr, Dan Guevarra, Ja'Nya Breeden + 2 more
Materials knowledge is inherently hierarchical. While high-level descriptors such as composition and structure are valuable for contextualizing materials data, the data must ultimately be considered in the context of its low-level acquisition details. Graph databases offer an opportunity to represent hierarchical…
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
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…