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Three Dimensional UML using Force Directed Layout
, 2001
"... The Unified Modelling Language (UML) is a visual language for modelling software designs and is currently the most widely accepted standard for software diagrams in the software engineering field. Force Directed Layout algorithms are methods for arranging the elements of a graph in an aesthetically ..."
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Cited by 21 (1 self)
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The Unified Modelling Language (UML) is a visual language for modelling software designs and is currently the most widely accepted standard for software diagrams in the software engineering field. Force Directed Layout algorithms are methods for arranging the elements of a graph in an aesthetically pleasing and clear manner.
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 20 (5 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
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 16 (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.
Topicnets: Visual analysis of large text corpora with topic modeling
 ACM Transactions on Intelligent Systems and Technology, 2011
"... We present TopicNets, a webbased system for visual and interactive analysis of large sets of documents using statistical topic models. A range of visualization types and control mechanisms to support knowledge discovery are presented. These include corpus and document specific views, iterative topi ..."
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Cited by 13 (2 self)
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We present TopicNets, a webbased system for visual and interactive analysis of large sets of documents using statistical topic models. A range of visualization types and control mechanisms to support knowledge discovery are presented. These include corpus and document specific views, iterative topic modeling, search, and visual filtering. Drilldown functionality is provided to allow analysts to visualize individual document sections and their relations within the global topic space. Analysts can search across a data set through a set of expansion techniques on selected document and topic nodes. Furthermore, analysts can select relevant subsets of documents and perform realtime topic modeling on these subsets to interactively visualize topics at various levels of granularity, allowing for a better understanding of the documents. A discussion of the design and implementation choices for each visual analysis technique is presented. This is followed by a discussion of three diverse use cases in which TopicNets enables fast discovery of information that is otherwise hard to find. These include a corpus of 50,000 successful NSF grant proposals, 10,000 publications from a large research center, and single documents including a grant proposal and a PhD thesis.
Drawing graphs by eigenvectors: Theory and practice
 Computers and Mathematics with Applications
, 2005
"... Abstract. The spectral approach for graph visualization computes the layout of a graph using certain eigenvectors of related matrices. Some important advantages of this approach are an ability to compute optimal layouts (according to specific requirements) and a very rapid computation time. In this ..."
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Cited by 12 (1 self)
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Abstract. The spectral approach for graph visualization computes the layout of a graph using certain eigenvectors of related matrices. Some important advantages of this approach are an ability to compute optimal layouts (according to specific requirements) and a very rapid computation time. In this paper we explore spectral visualization techniques and study their properties from different points of view. We also suggest a novel algorithm for calculating spectral layouts resulting in an extremely fast computation by optimizing the layout within a small vector space.
Building Virtual Worlds with the The BigBang Model
 of Conferences in Research and Practice in Information Technology, ACS
, 2001
"... Visualisations implemented as virtual worlds can allow users to comprehend large graphs more e#ectively. Good 3D layout algorithms are an important element. Angle has been developed as a platform for experimenting with 3D forcedirected layout algorithms. The bigbang modification is proposed as ..."
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Cited by 11 (6 self)
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Visualisations implemented as virtual worlds can allow users to comprehend large graphs more e#ectively. Good 3D layout algorithms are an important element. Angle has been developed as a platform for experimenting with 3D forcedirected layout algorithms. The bigbang modification is proposed as a means of obtaining e#ciently good 3D layouts for a wide range of graphs. Results are presented and compared with those from a conventional approach. 1
Combining Hierarchy and Energy for Drawing Directed Graphs
 IEEE Trans. Visualization and Computer Graphics
, 2003
"... We present an algorithm for drawing directed graphs, which is based on rapidly solving a unique onedimensional optimization problem for each of the axes. The algorithm results in a clear description of the hierarchy structure of the graph. Nodes are not restricted to lie on fixed horizontal layers, ..."
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Cited by 9 (5 self)
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We present an algorithm for drawing directed graphs, which is based on rapidly solving a unique onedimensional optimization problem for each of the axes. The algorithm results in a clear description of the hierarchy structure of the graph. Nodes are not restricted to lie on fixed horizontal layers, resulting in layouts that convey the symmetries of the graph very naturally. The algorithm can be applied without change to cyclic or acyclic digraphs, and even to graphs containing both directed and undirected edges. We also derive a hierarchy index from the input digraph, which quantitatively measures its amount of hierarchy.
Drawing Directed Graphs Using OneDimensional Optimization
 Proc. Graph Drawing 2002, LNCS 2528
, 2001
"... We present an algorithm for drawing directed graphs, which is based on rapidly solving a unique onedimensional optimization problem for each of the axes. The algorithm results in a clear description of the hierarchy structure of the graph. Nodes are not restricted to lie on fixed horizontal laye ..."
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Cited by 9 (6 self)
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We present an algorithm for drawing directed graphs, which is based on rapidly solving a unique onedimensional optimization problem for each of the axes. The algorithm results in a clear description of the hierarchy structure of the graph. Nodes are not restricted to lie on fixed horizontal layers, resulting in layouts that convey the symmetries of the graph very naturally. The algorithm can be applied without change to cyclic or acyclic digraphs, and even to graphs containing both directed and undirected edges. We also derive a hierarchy index from the input digraph, which quantitatively measures its amount of hierarchy.
Visualizing Graphs in Three Dimensions
 ACM Transactions on Applied Perception (TAP
"... It has been known for some time that larger graphs can be interpreted if laid out in 3D and displayed with stereo and/or motion depth cues to support spatial perception. However, prior studies were carried out using displays that provided a level of detail far short of what the human visual system i ..."
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Cited by 9 (0 self)
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It has been known for some time that larger graphs can be interpreted if laid out in 3D and displayed with stereo and/or motion depth cues to support spatial perception. However, prior studies were carried out using displays that provided a level of detail far short of what the human visual system is capable of resolving. Therefore we undertook a graph comprehension study using a very high resolution stereoscopic display. In our first experiment we examined the effect of stereo, kinetic depth and using 3D tubes versus lines to display the links. The results showed a much greater benefit for 3D viewing than previous studies. For example, with both motion and depth cues, unskilled observers could see paths between nodes in 333 node graphs with less than a 10 % error rate. Skilled observers could see up to a 1000 node graph with less than a 10 % error rate. This represented an order of magnitude increase over 2D display. In our second experiment we varied both nodes and links to understand the constraints on the number of links and the size of graph that can be reliably traced. We found the difference between number of links and number of nodes to best account for error rates and suggest that this is evidence for a “perceptual phase transition”. These findings are discussed in terms of their implications for information display.
Visualizing Clustering Results
 SIAM International Conference on Data Mining
, 2002
"... Nonhierarchical clustering has a long history in numerical taxonomy [13] and machine learning [1] with many applications in fields such as data mining [2], statistical analysis [3] and information retrieval [17]. Clustering involves finding a specific number of subgroups (k) within a set of s obser ..."
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Cited by 7 (2 self)
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Nonhierarchical clustering has a long history in numerical taxonomy [13] and machine learning [1] with many applications in fields such as data mining [2], statistical analysis [3] and information retrieval [17]. Clustering involves finding a specific number of subgroups (k) within a set of s observations (data points/objects); each described by d