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37
An open graph visualization system and its applications to software engineering
 SOFTWARE  PRACTICE AND EXPERIENCE
, 2000
"... We describe a package of practical tools and libraries for manipulating graphs and their drawings. Our design, which aimed at facilitating the combination of the package components with other tools, includes stream and event interfaces for graph operations, highquality static and dynamic layout alg ..."
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Cited by 412 (9 self)
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We describe a package of practical tools and libraries for manipulating graphs and their drawings. Our design, which aimed at facilitating the combination of the package components with other tools, includes stream and event interfaces for graph operations, highquality static and dynamic layout algorithms, and the ability to handle sizable graphs. We conclude with a description of the applications of this package to a variety of software engineering tools.
Graph drawing by stress majorization
 GRAPH DRAWING
, 2004
"... One of the most popular graph drawing methods is based of achieving graphtheoretic target ditsances. This method was used by Kamada and Kawai [15], who formulated it as an energy optimization problem. Their energy is known in the multidimensional scaling (MDS) community as the stress function. In th ..."
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Cited by 93 (12 self)
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One of the most popular graph drawing methods is based of achieving graphtheoretic target ditsances. This method was used by Kamada and Kawai [15], who formulated it as an energy optimization problem. Their energy is known in the multidimensional scaling (MDS) community as the stress function. In this work, we show how to draw graphs by stress majorization, adapting a technique known in the MDS community for more than two decades. It appears that majorization has advantages over the technique of Kamada and Kawai in running time and stability. We also present a few extensions to the basic energy model which can improve layout quality and computation speed in practice. Majorizationbased optimization is essential to these extensions.
XGvis: Interactive Data Visualization with Multidimensional Scaling
, 2001
"... this article. Section 2 gives an overview of how a user operates the XGvis system. Section 3 deals with algorithm animation, direct manipulation and perturbation of the con guration. Section 4 gives details about the cost functions and their interactively controlled parameters for transformation, s ..."
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Cited by 57 (1 self)
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this article. Section 2 gives an overview of how a user operates the XGvis system. Section 3 deals with algorithm animation, direct manipulation and perturbation of the con guration. Section 4 gives details about the cost functions and their interactively controlled parameters for transformation, subsetting and weighting of dissimilarities. Section 5 describes diagnostics for MDS. Section 6 is about computational and systems aspects, including coordination of windows, algorithms, and large data problems. Finally, Section 7 gives a tour of applications with examples of proximity analysis, dimension reduction, and graph layout in two and more dimensions
Eigensolver Methods for Progressive Multidimensional Scaling of Large Data
, 2007
"... We present a novel samplingbased approximation technique for classical multidimensional scaling that yields an extremely fast layout algorithm suitable even for very large graphs. It produces layouts that compare favorably with other methods for drawing large graphs, and it is among the fastest me ..."
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Cited by 49 (8 self)
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We present a novel samplingbased approximation technique for classical multidimensional scaling that yields an extremely fast layout algorithm suitable even for very large graphs. It produces layouts that compare favorably with other methods for drawing large graphs, and it is among the fastest methods available. In addition, our approach allows for progressive computation, i.e. a rough approximation of the layout can be produced even faster, and then be refined until satisfaction.
Graphviz and dynagraph – static and dynamic graph drawing tools
 GRAPH DRAWING SOFTWARE
, 2003
"... Graphviz is a collection of software for viewing and manipulating abstract graphs. It provides graph visualization for tools and web sites in domains such as software engineering, networking, databases, knowledge representation, and bioinformatics. Hundreds of thousands of copies have been distribu ..."
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Cited by 43 (0 self)
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Graphviz is a collection of software for viewing and manipulating abstract graphs. It provides graph visualization for tools and web sites in domains such as software engineering, networking, databases, knowledge representation, and bioinformatics. Hundreds of thousands of copies have been distributed under an open source license. The core of Graphviz consists of implementations of various common types of graph layout. These layouts can be used via a C library interface, streambased command line tools, graphical user interfaces and web browsers. Aspects which distinguish the software include a retention of streambased interfaces in conjunction with a variety of tools for graph manipulation, and support for a wide assortment of graphical features and output formats. The former makes it possible to write highlevel programs for querying, modifying and displaying graphs. The latter allows Graphviz to be useful in a wide range of areas, with applications far removed from academic exercises. The algorithms of Graphviz concentrate on static layouts. Dynagraph is a sibling of Graphviz, with algorithms and interactive programs for incremental layout. At the library level, it provides an objectoriented interface for graphs and graph algorithms.
Statistical strategies for avoiding false discoveries in metabolomics and related experiments
, 2006
"... Many metabolomics, and other highcontent or highthroughput, experiments are set up such that the primary aim is the discovery of biomarker metabolites that can discriminate, with a certain level of certainty, between nominally matched ‘case ’ and ‘control ’ samples. However, it is unfortunately ve ..."
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Cited by 39 (10 self)
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Many metabolomics, and other highcontent or highthroughput, experiments are set up such that the primary aim is the discovery of biomarker metabolites that can discriminate, with a certain level of certainty, between nominally matched ‘case ’ and ‘control ’ samples. However, it is unfortunately very easy to find markers that are apparently persuasive but that are in fact entirely spurious, and there are wellknown examples in the proteomics literature. The main types of danger are not entirely independent of each other, but include bias, inadequate sample size (especially relative to the number of metabolite variables and to the required statistical power to prove that a biomarker is discriminant), excessive false discovery rate due to multiple hypothesis testing, inappropriate choice of particular numerical methods, and overfitting (generally caused by the failure to perform adequate validation and crossvalidation). Many studies fail to take these into account, and thereby fail to discover anything of true significance (despite their claims). We summarise these problems, and provide pointers to a substantial existing literature that should assist in the improved design and evaluation of metabolomics experiments, thereby allowing robust scientific conclusions to be drawn from the available data. We provide a list of some of the simpler checks that might improve one’s confidence that a candidate biomarker is not simply a statistical artefact, and suggest a series of preferred tests and visualisation tools that can assist readers and authors in assessing papers. These tools can be applied to individual metabolites by using multiple univariate tests performed in parallel across all metabolite peaks. They may also be applied to the validation of multivariate models. We stress in
A Practical Approach to Drawing Undirected Graphs
, 1994
"... Although there is extensive research on drawing graphs, none of the published methods are satisfactory for drawing general undirected graphs. Generating drawings which are optimal with respect to several aesthetic criteria is known to be NPhard, so all published approaches to the problem have used ..."
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Cited by 24 (2 self)
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Although there is extensive research on drawing graphs, none of the published methods are satisfactory for drawing general undirected graphs. Generating drawings which are optimal with respect to several aesthetic criteria is known to be NPhard, so all published approaches to the problem have used heuristics. These heuristics are too slow to be practical for graphs of moderate size, and they do not produce consistently good drawings for general graphs. Moreover, they rely on general optimization methods, because problemspecific methods require a deeper theoretical understanding of the graph drawing problem. This paper presents an algorithm to generate twodimensional drawings of undirected graphs. The algorithm uses a combination of heuristics to obtain drawings which are nearoptimal with respect to an aesthetic cost function. The algorithm is incremental in nature, but preprocesses the graph to determine an order for node placement. The algorithm uses a local optimization strategy...
Local Multidimensional Scaling for Nonlinear Dimension Reduction, Graph Layout and Proximity Analysis
, 2006
"... In recent years there has been a resurgence of interest in nonlinear dimension reduction methods. Among new proposals are socalled “Local Linear Embedding ” (LLE) and “Isomap”. Both use local neighborhood information to construct a global lowdimensional embedding of a hypothetical manifold near w ..."
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Cited by 24 (3 self)
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In recent years there has been a resurgence of interest in nonlinear dimension reduction methods. Among new proposals are socalled “Local Linear Embedding ” (LLE) and “Isomap”. Both use local neighborhood information to construct a global lowdimensional embedding of a hypothetical manifold near which the data fall. In this paper we introduce a family of new nonlinear dimension reduction methods called “Local Multidimensional Scaling ” or LMDS. Like LLE and Isomap, LMDS only uses local information from userchosen neighborhoods, but it differs from them in that it uses ideas from the area of “graph layout”. A common paradigm in graph layout is to achieve desirable drawings of graphs by minimizing energy functions that balance attractive forces between near points and repulsive forces between nonnear points against each other. We approach the force paradigm by proposing a parametrized family of stress or energy functions inspired by BoxCox power transformations. This family provides users with considerable flexibility for achieving desirable embeddings, and it comprises most energy functions proposed in the past.
An Experimental Study on DistanceBased Graph Drawing (Extended Abstract)
, 2009
"... In numerous application areas, general undirected graphs need to be drawn, and forcedirected layout appears to be the most frequent choice. We present an extensive experimental study showing that, if the goal is to represent the distances in a graph well, a combination of two simple algorithms base ..."
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Cited by 22 (6 self)
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In numerous application areas, general undirected graphs need to be drawn, and forcedirected layout appears to be the most frequent choice. We present an extensive experimental study showing that, if the goal is to represent the distances in a graph well, a combination of two simple algorithms based on variants of multidimensional scaling is to be preferred because of their efficiency, reliability, and even simplicity. We also hope that details in the design of our study help advance experimental methodology in algorithm engineering and graph drawing, independent of the case at hand.
Constraints in graph drawing algorithms
 Constraints
, 1998
"... Abstract. Graphs are widely used for information visualization purposes, since they provide a natural and intuitive representation of complex abstract structures. The automatic generation of drawings of graphs has applications a variety of fields such as software engineering, database systems, and g ..."
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Cited by 16 (0 self)
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Abstract. Graphs are widely used for information visualization purposes, since they provide a natural and intuitive representation of complex abstract structures. The automatic generation of drawings of graphs has applications a variety of fields such as software engineering, database systems, and graphical user interfaces. In this paper, we survey algorithmic techniques for graph drawing that support the expression and satisfaction of userdefined constraints. 1.