24 papers · ranked by Valyu relevance
Kang Rong Roy Ang
I, the candidate for Part II of the Computer Science Tripos with Blind Grading Number 2320D, hereby declare that this report and the work described in it are my own work, unaided except as may be specified below, and that the report does not contain material that has already been used to any substantial extent for a…
Timo Kehrer, Christos Tsigkanos, Carlo Ghezzi
Bigraphs are an emerging modeling formalism for structures in ubiquitous computing. Besides an algebraic notation, which can be adopted to provide an algebraic syntax for bigraphs, the bigraphical theory introduces a visual concrete syntax which is intuitive and unambiguous at the same time; the standard visual…
Luca Cappelletti, Tommaso Fontana, Elena Casiraghi, Vida Ravanmehr + 7 more
'Tiffany J. Callahan' 'Carlos Cano' 'Marcin P. Joachimiak' 'Christopher J. Mungall' 'Peter N. Robinson' 'Justin Reese' 'Giorgio Valentini'] Graph representation learning methods opened new avenues for addressing complex, real-world problems represented by graphs. However, many graphs used in these applications comprise…
Tom C. Freeman, Sebastian Horsewell, Anirudh Patir, Josh Harling-Lee + 6 more
'Tim Regan' 'Barbara B. Shih' 'James Prendergast' 'David A. Hume' 'Tim Angus' 'Eli Zunder'] Graphia is an open-source platform created for the graph-based analysis of the huge amounts of quantitative and qualitative data currently being generated from the study of genomes, genes, proteins metabolites and cells. Core to…
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…
Nikos Bikakis, John Liagouris, Maria Krommyda, George Papastefanatos + 1 more
'Timos Sellis'] Abstract. In this paper, we outline our work on developing a disk-based infrastructure for efficient visualization and graph exploration operations over very large graphs. The proposed platform, called graphVizdb, is based on a novel technique for indexing and storing the graph. Particularly, the graph…
Bob Blakley, G. R. Blakley, Sean M. Blakley
A graph is a mathematical object consisting of a set of vertices and a set of edges connecting vertices. Graphs can be drawn on paper in various ways, but until recently all published methods of drawing graphs have had undesirable properties: (i) for graphs which are not plane embeddable, intersections between the…
Omar Batarfi, Radwa Elshawi, Ayman Fayoumi, Ahmed Barnawi + 1 more
'Sherif Sakr'] A graph is a popular data model that has become pervasively used for modeling structural relationships between objects. In practice, in many real-world graphs, the graph vertices and edges need to be associated with descriptive attributes. Such type of graphs are referred to as attributed graphs.…
Sabuzima Nayak, Ripon Patgiri
Big Graph is a graph having thousands of vertices and hundreds of thousands of edges. The study of graphs is crucial because the interlinkage among the vertices provides various insights and uncovers the hidden truth developed due to their relationship. The graph processing has non-linear time complexity. The…
A. K. M. Mubashwir Alam, Keke Chen
Introduction Big graphs like social network user interactions and customer rating matrices require significant computing resources to maintain. Data owners are now using public cloud resources for storage and computing elasticity. However, existing solutions do not fully address the privacy and ownership protection…
Velitchko Filipov, Alessio Arleo, Silvia Miksch
Networks are abstract and ubiquitous data structures, defined as a set of data points and relationships between them. Network visualization provides meaningful representations of these data, supporting researchers in understanding the connections, gathering insights, and detecting and identifying unexpected patterns.…
Apostolos Syropoulos
In a way, the work of the ACM Turing Award laureate Robin Milner[11, 12] defined the evolution of concurrency theory. Initially, his CCS calculus and later on his π-calculus were milestones in the development of concurrency theory. His work was an algebraic approach to concurrency and communication. Later on, Milner…
Adam Struck, Brian Walsh, Alexander Buchanan, Jordan A. Lee + 3 more
The analysis of cancer biology data involves extremely heterogeneous datasets including information from RNA sequencing, genome-wide copy number, DNA methylation data reporting on epigenomic regulation, somatic mutations from whole-exome or whole-genome analyses, pathology estimates from imaging sections or subtyping…
Marino Miculan, Marco Peressotti
A crucial problem for many results and tools about bigraphs and bigraphical reactive systems is bigraph embedding. An embedding is more informative than a bigraph matching, since it keeps track of the correspondence between the various components of the redex (guest) within the agent (host). In this paper, we present…
David Earl Hostallero, Yihui Li, Amin Emad
The increasing number of publicly available databases containing drugs’ chemical structures, their response in cell lines, and molecular profiles of the cell lines has garnered attention to the problem of drug response prediction. However, many existing methods do not fully leverage the information that is shared among…
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…
Vasileios Karyotis, Konstantinos Tsitseklis, Konstantinos Sotiropoulos, Symeon Papavassiliou
'Konstantinos Sotiropoulos' 'Symeon Papavassiliou'] In this paper, we present a novel data clustering framework for big sensory data produced by IoT applications. Based on a network representation of the relations among multi-dimensional data, data clustering is mapped to node clustering over the produced data graphs.…
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…
Authors not listed
Curried functions provide a systematic way of transforming multi-argument functions into nested singleargument functions. This transformation allows partial application and supports many central principles of functional programming. Their extension, called curried 𝑘-ary functions, naturally generalizes the familiar…
Gunther Eysenbach, Luca Toldo, Junfeng Gao, Weiqi Wang + 1 more
Background In the past few decades, medically related data collection saw a huge increase, referred to as big data. These huge datasets bring challenges in storage, processing, and analysis. In clinical medicine, big data is expected to play an important role in identifying causality of patient symptoms, in predicting…
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…
Rosemary Wyber, Samuel Vaillancourt, William Perry, Priya Mannava + 2 more
'Temitope Folaranmi' 'Leo Anthony Celi'] Title: Abstract Over the last decade, a massive increase in data collection and analysis has occurred in many fields. In the health sector, however, there has been relatively little progress in data analysis and application despite a rapid rise in data production. Given adequate…
Authors not listed
In the real world, many reversal phenomena occur—for example, cases in which a statement once regarded as false is later recognized as true. Upside-Down Logic is a framework designed to formalize such reversal phenomena as a logical system. It inverts the truth and falsity of propositions through contextual…
Alex M. Ascension, Marcos J. Araúzo-Bravo
Big Data analysis is a discipline with a growing number of areas where huge amounts of data is extracted and analyzed. Parallelization in Python integrates Message Passing Interface via mpi4py module. Since mpi4py does not support parallelization of objects greater than 2^31^ bytes, we developed BigMPI4py, a Python…