Browsing by Subject "Graph visualization"

Now showing 1 - 14 of 14

Open Access
Automated layout of process description maps drawn in systems biology graphical notation = Systems biology graphical notation kullanılarak çizilen proses diyagramlarının otomatik yerleştirilmesi
(2014) Genç, Begüm
Evolving technology has increased the focus on genomics. The combination of today’s advanced studies with decades of molecular biology research yield in huge amount of pathway data. These models can be used to improve high-throughput data analysis by linking correlation to the causation, shedding light on many complex diseases. In order to prevent ambiguity and ensure regularity of the research, a need for using a standard notation has emerged. Systems Biology Graphical Notation (SBGN) is a visual language developed by a community of biochemists, modellers and computer scientists with the intention of enabling scientists to represent networks, including models of cellular processes, in a standard, unambiguous way. SBGN is formed of three languages: process, entity relationship and activity flow. This research is focused on its process diagram branch. Automated layout is commonly used to clearly visualize the information represented by graphs. Considering the fact that, biological pathways includes nested structures (e.g., nucleoplasms), we have made use of a force-directed automatic layout algorithm called Compound Spring Embedder (CoSE), which supports the compound graph structures. On top of this layout structure, we have developed a specialized layout algorithm called SBGN-PD layout. SBGN-PD layout enhancements mainly include properly tiling of complex members and disconnected molecules, placement of product and substrate edges on the opposite sides of a process node without disturbing the force-directed structure of the algorithm.
Open Access
Chisio Web : a web-based framework for customizable visualization of relational information
(2012) Sümer, Selçuk Onur
Graphs are widely used to represent complex relational information. Graph visualization is crucial for effective analysis of information. In simple graphs, nodes are generally considered as uniform-sized components and they cannot be nested. This is often not sufficient to visualize complex relationships, because relational information is often clustered or hierarchically organized into groups or nested structures. There exist many free, open source software in the field of web-based graph visualization. However, none fully supports compound or clustered graphs. Moreover, customization provided by such software is often limited to the basic visual properties of nodes and edges. It requires a lot of effort to build an advanced customization of visual properties and interactive functionality with these software. In this thesis, we introduce a free, open source, general-purpose, web-based graph visualization framework, named Chisio Web (ChiWeb). ChiWeb supports visualization, interactive editing and layout of both simple and compound graphs. ChiWeb is implemented in ActionScript language and based on Flare, which is an open source ActionScript library designed for data visualization. ChiWeb is specifically designed for easy customization with respect to visualization and functionality. ChiWeb can be used as a library to create a custom graph visualization with an advanced application behavior for particular needs of a specific domain. The elements and functionality that can be easily customized with ChiWeb are: visual styles, controls for interactive events such as node creation, key and mouse functionality, context menus, toolbars, and inspector windows. Furthermore, ChiWeb’s architecture allows easy integration of new graph layout algorithms.
Open Access
CiSE: a circular spring embedder layout algorithm
(Institute of Electrical and Electronics Engineers, 2013) Dogrusoz, U.; Belviranli, M. E.; Dilek, A.
We present a new algorithm for automatic layout of clustered graphs using a circular style. The algorithm tries to determine optimal location and orientation of individual clusters intrinsically within a modified spring embedder. Heuristics such as reversal of the order of nodes in a cluster and swap of neighboring node pairs in the same cluster are employed intermittently to further relax the spring embedder system, resulting in reduced inter-cluster edge crossings. Unlike other algorithms generating circular drawings, our algorithm does not require the quotient graph to be acyclic, nor does it sacrifice the edge crossing number of individual clusters to improve respective positioning of the clusters. Moreover, it reduces the total area required by a cluster by using the space inside the associated circle. Experimental results show that the execution time and quality of the produced drawings with respect to commonly accepted layout criteria are quite satisfactory, surpassing previous algorithms. The algorithm has also been successfully implemented and made publicly available as part of a compound and clustered graph editing and layout tool named Chisio. © 1995-2012 IEEE.
Open Access
CMGV: a unified framework for complexity management in graph visualization
(2023-08) Zafar, Osama
In today’s era of technological revolution, the sheer volume of data being produced poses a significant challenge for analyzing relational data of such scale, particularly in terms of visual analysis. Graphs provide an effective way of organizing and representing relational data, with nodes representing entities. In contrast, edges representing relationships, a comprehensive and intuitive view of complex large-scale data is created. A well-represented visualization of complex graphs allows users to understand relationships, uncover new insights, and discover hid-den patterns. To this end, we introduce a complexity management framework for effectively analyzing large-scale relational data represented as graphs. Existing methods for managing graph complexity work independently and may lead to in-consistencies and confusion consecutively applied. The Complexity Management Graph Visualization framework (CMGV) presents a novel approach integrating commonly used complexity management techniques while ensuring the preservation of the user’s mental map through a specialized layout algorithm. The frame-work introduces an intuitive Graph Complexity Management Model (CMGM) for both graph representation and complexity management. CMGV supports commonly utilized complexity management tasks, including filtering, hiding, showing, collapsing, and expanding graph elements. Importantly, CMGV is designed to be independent of the rendering method and can be seamlessly integrated with different graph rendering libraries. This is possible through an extension that synchronizes the graph models between the rendering library and CMGM. Our experiments performed on randomly generated graphs verify that CMGV flawlessly performs consecutive graph complexity management operations, leaving the user graph intact, and outperforms existing complexity management solutions in terms of both runtime and generally accepted graph layout criteria. It is fast enough to be used in interactive applications with small to medium-sized graphs.
Open Access
A compound graph layout algorithm with support for ports
(2020-10) Okka, Alihan
Information visualization is a eld of study that aims to represent abstract data in an aesthetically pleasing and easy to comprehend visual manner. Various approaches and standards have been created to reinforce the discovery of unstructured insights that are limited to human cognition via visual depictions. Complex systems and processes are often modelled as graphs since it would be di cult to describe in text. A type of visualization, graph drawing, addresses the notion of creating geometric representations of graphs. There are plentiful research directed to designing automatic layout algorithms for visualizing graphs. Nevertheless, a limited number of studies utilize ports, which are dedicated connection points on the locations where edge ends link to their incident nodes. We propose a new automatic layout algorithm named CoSEP supporting port constraints on compound nodes used for nested levels of abstractions in data. The CoSEP algorithm is based on a force-directed algorithm, Compound Spring Embedder (CoSE). Additional heuristics and force types are introduced on top of existing physical model. Using CoSE's layout structure as a baseline enables CoSEP to handle non-uniform node sizes, arbitrary levels of nesting, and intergraph edges that may span multiple levels of nesting. Our experiments show that CoSEP signi cantly improves the quality of the layouts for compound graphs with port constraints with respect to commonly accepted graph drawing criteria, while running in at most a few seconds, suitable for use in interactive applications for small to medium sized graphs. The CoSEP algorithm is implemented in JavaScript as a Cytoscape.js extension, and the sources along with a demo are available on the associated GitHub repository.
Open Access
CoSEP: a compound spring embedder layout algorithm with support for ports
(Sage Publications, 2021-07-01) Okka, Alihan; Doğrusöz, Uğur; Balcı, Hasan
This paper describes a new automatic layout algorithm named CoSEP for compound graphs with port constraints. The algorithm works by extending the physical model of a previous algorithm named CoSE by defining additional force types and heuristics for constraining edges to connect to certain user-defined locations on end nodes. Similar to its predecessor, CoSEP also accounts for non-uniform node dimensions and arbitrary levels of nesting via compound nodes. Our experiments show that CoSEP significantly improves the quality of the layouts for compound graphs with port constraints with respect to commonly accepted graph drawing criteria while running reasonably fast, suitable for use in interactive applications for small to medium-sized (up to 500 nodes) graphs. A complete JavaScript implementation of CoSEP as a Cytoscape.js extension along with a demo page is freely available at https://github.com/iVis-at-Bilkent/cytoscape.js-cosep.
Open Access
Efficient querying of SBGN maps stored in a graph database
(2019-02) Karaca, Mustafa Enes
Graph visualization is an important research area that endeavors to make graphs more understandable and easier to analyze. In various domains, graph visualization techniques and standards are developed to effectively analyze underlying graph based data. Systems Biology Graphical Notation (SBGN) is a standard language for modeling biological processes and pathways through graph visualization. Information about SBGN maps can be stored in XML based SBGNML files. libSBGN is a Java/C++ library for reading, writing SBGN-ML and manipulating SBGN maps in an object-oriented manner. Graph databases store data in terms of a graph structure consisting nodes and their relationships. Performing a computation on graph data stored in a graph database by traversals is more e cient than accessing tabled data in relational databases through costly join operations. Neo4j is a prominent graph database that provides a proprietary language named Cypher for querying stored graph data. Neo4j allows writing user defined procedures in Java as plugins to improve capabilities of Neo4j with third party Java libraries. With this thesis, we enable modeling SBGN maps in Neo4j graph database with support for compound structures. Using this SBGN data model in Neo4j, we developed graph based user defined procedures in Java using libSBGN as a plugin to Neo4j. These procedures were used to implement graph query algorithms, such as neighborhood, common stream, and paths between, along with helper functions such as populating a database from an SBGN map and loading an SBGN map from a graph database. These user defined procedures are designed to produce or consume SBGN-ML; hence, they can be used by any visualization tool which can import/export SBGN-ML text. Newt, a web based editor for viewing and diting SBGN maps, is such a tool making use of these procedures and hosting a local Neo4j instance by providing a web service to execute Cypher statements.
Open Access
An ensemble classification model for detecting voice phishing in telecommunication networks and its integration into a visual analysis tool
(2022-09) Çalık, Hüseyin Eren
Voice phishing, a method of social engineering fraud performed over phone calls, has been a major problem globally since the use of phones became widespread. Traditional and modern methods to detect these fraud schemes include visual analysis of the customers’ behaviour, rule-based systems and machine learning models such as clustering, decision trees, shallow classifiers and deep learning models. Visual analysis depends only on human expertise and requires very high labor force to be effective. Rule-based systems are useful for extreme cases but are vulnerable to concept drifts. The-state-of-the-art methods generally utilize machine learning approaches. However, they require one or more of feature engineering done by experts, high computational power and privacy infringements. Therefore, in collaboration with Turkcell Technology, we aimed to develop a system that benefits from the advantages of the traditional methods while exploiting the effectiveness and efficiency of the state-of-the-art ones to tackle this issue. In doing so, we integrated an ensemble learning model to an existing visualization tool for detecting fraud users. This tool visualizes relational data as knowledge graphs, shows the informational data as texts and statistical data with charts and texts. Our ensemble learning model has two deep neural networks and one decision tree classifier. Multiple neural networks are used to reduce the variance and make a more stable model. One of them is composed of an input layer, two hidden layers with 200 nodes using Rectified Linear Unit (ReLU) activation function, each followed by a dropout layer and an output layer of one node with sigmoid activation function. We used dropout layers in this network to prevent over-fitting. The second neural network we built has 3 hidden layers instead with node numbers 64, 64 and 32, respectively, with ReLU as their activation function. To feed these models, a total of 34 features, 20 of which are raw, have been engineered with Turkcell fraud experts. The aggregation of the outputs is done by taking their average. We measured the success of our model by calculating the F1 Score as the class imbalance is high. Our model’s F1 score is 0.82 with a precision of 0.82 and a recall of 0.83. Also, with the integration of our model into this visualization tool, a framework was formed allowing mobile network operators to examine and detect fraud cases more efficiently and act accordingly.
Open Access
Hydra: Detecting fraud in financial transactions via graph based representation and visual analysis
(IEEE, 2020) Canbaz, Yusuf Sait; Doğrusöz, Uğur; Çeliksoy, M.; Güngör, F.; Kurban, K.
In this paper, we describe a web based tool named Hydra for analyzing financial transaction data with the aim to detect or verify fraudulent activities via visual analysis and graph based querying. Hydra exclusively uses graph based query algorithms to mine useful information in the transaction database, presents the results visually, facilitating interactive graphical analysis with state-of-the-art graph visualization technologies. We present the various components of Hydra and their aims. In addition, a number of different types of scenarios using these components for a network of prepaid card transactions are provided to illustrate the use of Hydra for detecting or verifying fraudulent activities.
Open Access
HySE: a spring embedder approach for layout of hybrid graphs
(2023-09) Islam, Hamza
In recent times, the growth of data has been exponential, making the visual analysis of relational data progressively complex. Presenting such data in a visually appealing manner can help simplify the analysis process. Hybrid graphs, comprising a central directed or hierarchical part and interconnected undirected components, offer a practical structure for representing relational data with varying levels of abstraction while managing its complexity. To comprehend the relationships in data, discover insights, and get important patterns, a well-optimized graph layout for such graphs is needed. In response, we present HySE (Hybrid Spring Embedder), a novel graph layout algorithm tailored for hybrid graphs. HySE makes use of a holistic approach based on the popular spring embedder to achieve the aesthetics and quality of an optimized force-directed layout, not only on the undirected part of the graph but also on the hierarchy while maintaining the cohesion between both directed and undirected elements of the graph. The layout algorithm assumes the rank information of directed graph elements is already calculated with one of the popular approaches. Then, it finds appropriate initial positions and uses a force-directed layout technique to integrate the undirected parts into the layout, applying spring forces to model the edges, and repulsive electric forces for the nodes. Iteratively, HySE converges to an equilibrium state with minimized energy, resulting in visually pleasing and interpretable layouts for intricate hybrid graphs. Experiments performed on graphs, generated randomly through a well-designed process, validate that HySE performs as well as the state-of-the-art algorithms in terms of quality. It also matches the speed of well-established algorithms as well in small-to-medium-sized graphs.
Open Access
On labeling in graph visualization
(Elsevier Inc., 2007-06-15) Dogrusoz, U.; Kakoulis, K. G.; Madden, B.; Tollis, I. G.
When visualizing graphs, it is essential to communicate the meaning of each graph object via text or graphical labels. Automatic placement of labels in a graph is an NP-Hard problem, for which efficient heuristic solutions have been recently developed. In this paper, we describe a general framework for modeling, drawing, editing, and automatic placement of labels respecting user constraints. In addition, we present the interface and the basic engine of the Graph Editor Toolkit – a family of portable graph visualization libraries designed for integration into graphical user interface application programs. This toolkit produces a high quality automated placement of labels in a graph using our framework. A brief survey of automatic label placement algorithms is also presented. Finally we describe extensions to certain existing automatic label placement algorithms, allowing their integration into this visualization tool. (C) 2007 Elsevier Inc. All rights reserved.
Open Access
Semantic validation of biological maps in SBGN
(2019-09) Çalış, Umut Utku
Graph visualization is a research field where relational information is graphically represented in the form of graphs or networks. It is applicable in numerous areas from computer network systems, to biology, to software engineering. In such areas, graph visualization techniques provide effective visual analysis of graph based data. Systems Biology Graphical Notation (SBGN) facilitates a standard model for representing biological entities and their interactions by using graph visualization. SBGN-ML is an XML based format for keeping information about SBGN maps. libSBGN enables writing and reading SBGN-ML files in an easy manner and is meant to bring syntactic and semantic validation to SBGN maps. It is currently available in Java/C++ (libSBGN) and JavaScript (libSBGN.js) programming languages with varying support for aforementioned. libSBGN enables important syntactic and semantic correctness concepts for manipulating SBGN maps and converting SBGN-ML files into several other formats. Syntactic validation of SBGN-ML files involves using a simple XML Schema Definition (XSD) file. This validation checks whether files are in correct form or not. However, this XSD file does not enable checking against semantic rules. For semantic validation of such files, the Schematron language was developed providing higher level semantic rule controls. With this thesis, we first enabled high level semantic validation (schematron validation) of SBGN maps in libSBGN.js, which uses XSLT and transformation of process description maps in SBGN-ML files. By using Schematron rules which are written in XPath syntax and enabling human-readable messages of validation errors and source of errors, we developed an XSLT stylesheet. We obtained validation result report by transforming SBGN-ML files using this XSLT stylesheet. In the JavaScript version of libSBGN library, we used a web based XSLT processor for transformation; hence, this library is now available for providing schematron validation in any SBGN related software. Furthermore, we added schematron validation checks to Newt, a web based SBGN pathway editor, using the updated libSBGN.js library. With this addition, Newt is now able to show validation results not only in a human-readable message text for the current map but also highlights the invalid map objects graphically, and, where appropriate, suggests a way to fix the problem automatically.
Open Access
VISIBIOweb : a web-based visualization and layout service for biological pathways
(2009) Dilek, Alptuğ
A biological pathway is a representation of biological reactions between molecules in a living cell. At present, there are hundreds of Internet-accessible databases storing biological pathway data. Exchanging, handling, and storing this data are crucial in terms of both providing understandability and allowing further enhancements on the gathered data. As a result of this necessity, many biological models were developed to cluster the data in a meaningful manner under a semantically reasonable hierarchy. As the amount and complexity of the data increases, visualization of pathways becomes inevitable. Graphs are inherently suitable for modeling pathways. The task of creating a visual representation for pathways dynamically requires methods from the area of graph visualization. As a result, many software systems, which can interpret the pathway data with a graph structure and visualize the constructed graph, emerged. However, many of these software systems are insufficient due to poor complexity handling of the underlying model, lack of visual standardization or long installation steps. In this thesis, we introduce VISIBIOweb, a new open-source and web-based visualization service for biological pathway models stored in BioPAX (Biological Pathways Exchange Language) format. VISIBIOweb runs on Apache Tomcat server and is implemented in Java based on Eclipse GEF (Graphical Editing Framework). Google Maps API is used on the client side as the core component to visualize the representation constructed on the server. VISIBIOweb supports basic graph viewing functionalities such as zooming, scrolling, and selection of graph objects. The inspector window is provided to view the properties of the selected graph object. Once the view for the uploaded biological model is created, it can be stored as a static image. The biological models can also be persisted and embedded within other web sites just like Google Maps. The layout information of the constructed graph is also provided in an XML-based format. The introduction of such a format is a good starting point to develop an official layout extension for BioPAX format.
Open Access
Visuall: a quickly customizable library for jumpstarting visual graph analysis components
(2021-09) Canbaz, Yusuf Sait
Graph visualization is an area of information visualization, where relational data is depicted in the form of nodes (objects) and edges (links). Many people or organizations utilize graph visualization for insightful analysis and interpretation of relational data. In graph visualization, primary challenges include complexity management, eﬃcient database querying, and customization for speciﬁc domains. Visuall aims to solve these problems by providing a generic, highly customizable, and easily conﬁgurable software component for building web-based visual graph analysis tools. Essential functionalities needed by such visual analysis components include manually or automatically setting the layout of graph elements, support for nested or hierarchical drawings, eﬃcient querying of the database or client-side data, emphasizing or highlighting graph elements of interest, customization of visuals and styles, clustering, calculating graph-theoretical properties, and time-based ﬁltering of graph elements. Although Visuall provides all these functionalities out of the box for jumpstarting, customization of software for domain-speciﬁc needs is still unavoidable. Such software changes might result in complications due to unstructured code and code ignoring the invariants assumed by the orig-inal development team. To prevent these and to facilitate easily maintainable customization, Visuall provides a modular architecture. Furthermore, the devel-opers straightforwardly upgrade the software so long as the Visuall developers and the users developing visual analysis components based on Visuall maintain the provided architecture. We tested our database queries on a database that contains about half a million graph elements. We also examined our client-side operations up to a thousand graph elements. In both client-side and database operations, we observe that operations take at most several seconds, making Visuall convenient for interactive exploration and analysis of networks.