The Widths of Strict Outerconfluent Graphs

Strict outerconfluent drawing is a style of graph drawing in which vertices are drawn on the boundary of a disk, adjacencies are indicated by the existence of smooth curves through a system of tracks within the disk, and no two adjacent vertices are connected by more than one of these smooth tracks. We investigate graph width parameters on the graphs that have drawings in this style. We prove that the clique-width of these graphs is unbounded, but their twin-width is bounded.Comment: 15 pages, 2 figure

Algorithms and Bounds for Drawing Directed Graphs

In this paper we present a new approach to visualize directed graphs and their hierarchies that completely departs from the classical four-phase framework of Sugiyama and computes readable hierarchical visualizations that contain the complete reachability information of a graph. Additionally, our approach has the advantage that only the necessary edges are drawn in the drawing, thus reducing the visual complexity of the resulting drawing. Furthermore, most problems involved in our framework require only polynomial time. Our framework offers a suite of solutions depending upon the requirements, and it consists of only two steps: (a) the cycle removal step (if the graph contains cycles) and (b) the channel decomposition and hierarchical drawing step. Our framework does not introduce any dummy vertices and it keeps the vertices of a channel vertically aligned. The time complexity of the main drawing algorithms of our framework is $O(kn)$, where $k$ is the number of channels, typically much smaller than $n$ (the number of vertices).Comment: Appears in the Proceedings of the 26th International Symposium on Graph Drawing and Network Visualization (GD 2018

DiscoverPath: A Knowledge Refinement and Retrieval System for Interdisciplinarity on Biomedical Research

The exponential growth in scholarly publications necessitates advanced tools for efficient article retrieval, especially in interdisciplinary fields where diverse terminologies are used to describe similar research. Traditional keyword-based search engines often fall short in assisting users who may not be familiar with specific terminologies. To address this, we present a knowledge graph-based paper search engine for biomedical research to enhance the user experience in discovering relevant queries and articles. The system, dubbed DiscoverPath, employs Named Entity Recognition (NER) and part-of-speech (POS) tagging to extract terminologies and relationships from article abstracts to create a KG. To reduce information overload, DiscoverPath presents users with a focused subgraph containing the queried entity and its neighboring nodes and incorporates a query recommendation system, enabling users to iteratively refine their queries. The system is equipped with an accessible Graphical User Interface that provides an intuitive visualization of the KG, query recommendations, and detailed article information, enabling efficient article retrieval, thus fostering interdisciplinary knowledge exploration. DiscoverPath is open-sourced at https://github.com/ynchuang/DiscoverPath

Graph Algorithms and Applications

The mixture of data in real-life exhibits structure or connection property in nature. Typical data include biological data, communication network data, image data, etc. Graphs provide a natural way to represent and analyze these types of data and their relationships. Unfortunately, the related algorithms usually suffer from high computational complexity, since some of these problems are NP-hard. Therefore, in recent years, many graph models and optimization algorithms have been proposed to achieve a better balance between efficacy and efficiency. This book contains some papers reporting recent achievements regarding graph models, algorithms, and applications to problems in the real world, with some focus on optimization and computational complexity

Helmholtz Portfolio Theme Large-Scale Data Management and Analysis (LSDMA)

The Helmholtz Association funded the "Large-Scale Data Management and Analysis" portfolio theme from 2012-2016. Four Helmholtz centres, six universities and another research institution in Germany joined to enable data-intensive science by optimising data life cycles in selected scientific communities. In our Data Life cycle Labs, data experts performed joint R&D together with scientific communities. The Data Services Integration Team focused on generic solutions applied by several communities

Identifying Changes of Functional Brain Networks using Graph Theory

This thesis gives an overview on how to estimate changes in functional brain networks using graph theoretical measures. It explains the assessment and definition of functional brain networks derived from fMRI data. More explicitly, this thesis provides examples and newly developed methods on the measurement and visualization of changes due to pathology, external electrical stimulation or ongoing internal thought processes. These changes can occur on long as well as on short time scales and might be a key to understanding brain pathologies and their development. Furthermore, this thesis describes new methods to investigate and visualize these changes on both time scales and provides a more complete picture of the brain as a dynamic and constantly changing network.:1 Introduction 1.1 General Introduction 1.2 Functional Magnetic Resonance Imaging 1.3 Resting-state fMRI 1.4 Brain Networks and Graph Theory 1.5 White-Matter Lesions and Small Vessel Disease 1.6 Transcranial Direct Current Stimulation 1.7 Dynamic Functional Connectivity 2 Publications 2.1 Resting developments: a review of fMRI post-processing methodologies for spontaneous brain activity 2.2 Early small vessel disease affects fronto-parietal and cerebellar hubs in close correlation with clinical symptoms - A resting-state fMRI study 2.3 Dynamic modulation of intrinsic functional connectivity by transcranial direct current stimulation 2.4 Three-dimensional mean-shift edge bundling for the visualization of functional connectivity in the brain 2.5 Dynamic network participation of functional connectivity hubs assessed by resting-state fMRI 3 Summary 4 Bibliography 5. Appendix 5.1 Erklärung über die eigenständige Abfassung der Arbeit 5.2 Curriculum vitae 5.3 Publications 5.4 Acknowledgement