PathBank: Web-Based Querying and Visualziation of an Integrated Biological Pathway Database
PathBank is a Web-based query and visualization system for biological pathways using an integrated pathway database. To address the needs for biologists to visualize and analyze biological pathways, PathBank is designed to be user-friendly, flexible and extensible. It is, to the best of our knowledge, the first Web-based system that allows biological pathways to be visualized in three dimensions. PathBank demonstrates the ability to automatically generate and layout biological pathways in response to Web-based database query about proteins, genes, gene ontology and small molecules. Using a novel OWL-to-relational database schema generation approach, it can automatically integrate biological data from different sources that support the BioPAX exchange format (e.g. KEGG, Bio- Cyc). The systems Web interface allows both simple keyword and complex query-based searches in the database. The pathway visualization component provides fast and interactive data access by using asynchronous data retrieval. Due to its modular implementation, it can be easily extended with new visualization algorithms

title: A Multiresolution Terrain Model for Efficient Visualization Query Processing
abstract: Multiresolution triangular mesh (MTM) models are widely used to improve the performance of large terrain visualization by replacing the original model with a simplified one. MTM models, which consist of both original and simplified data, are commonly stored in spatial database systems due to their size. The relatively slow access speed of disks makes data retrieval the bottleneck of such terrain visualization systems. Existing spatial access methods proposed to address this problem rely on main-memory MTM models, which leads to significant overhead during query processing. In this paper, we approach the problem from a new perspective and propose a novel MTM called direct mesh that is designed specifically for secondary storage. It supports available indexing methods natively and requires no modification to MTM structure. Experiment results, which are based on two real-world data sets, show an average performance improvement of 5-10 times over the existing methods

title: A multi-resolution surface distance model for k-NN query processing
abstract: A spatial k-NN query returns k nearest points in a point dataset to a given query point. To measure the distance between two points, most of the literature focuses on the Euclidean distance or the network distance. For many applications, such as wildlife movement, it is necessary to consider the surface distance, which is computed from the shortest path along a terrain surface. In this paper, we investigate the problem of efficient surface k-NN (sk-NN) query processing. This is an important yet highly challenging problem because the underlying environment data can be very large and the computational cost of finding the shortest path on a surface can be very high. To minimize the amount of surface data to be used and the cost of surface distance computation, a multi-resolution surface distance model is proposed in this paper to take advantage of monotonic distance changes when the distances are computed at different resolution levels. Based on this innovative model, sk-NN queries can be processed efficiently by accessing and processing surface data at a just-enough resolution level within a just-enough search region. Our extensive performance evaluations using real world datasets confirm the efficiency of our proposed model.

title: Gene Specific Co-regulation Discovery: An Improved Approach
abstract: Discovering gene co-regulatory relationships is a new but important research problem in DNA microarray data analysis. The problem of gene specific co-regulation discovery is to, for a particular gene of interest, called the target gene , identify its strongly co-regulated genes and the condition subsets where such strong gene co-regulations are observed. The study on this problem can contribute to a better understanding and characterization of the target gene. The existing method, using the genetic algorithm (GA), is slow due to its expensive fitness evaluation and long individual representation. In this paper, we propose an improved method for finding gene specific co-regulations. Compared with the current method, our method features a notably improved efficiency. We employ k NN Search Table to substantially speed up fitness evaluation in the GA. We also propose a more compact representation scheme for encoding individuals in the GA, which contributes to faster crossover and mutation operations. Experimental results with a real-life gene microarray data set demonstrate the improved efficiency of our technique compared with the current method.

title: Workshop Organizers' Message
abstract: International Workshop on Privacy-Preserving Data Analysis (PPDA) 2009 took place at Brisbane, Australia on 21st April, 2009. There were two sessions for this workshop with 2 paper presentations in the first session and 3 presentations in the second session. 
 
With the advancement of information technology and declining hardware price, organizations and companies are able to collect large amount of personal data. Moreover, advanced data analysis and mining techniques have been proposed to derived patterns hidden in data. However, the increasing power in data processing and analysis also raises concerns over the proper usage of personal information. Without proper treatment of the threat of sensitive information leakage, organizations would be reluctant to disclose their data even when there may be great potential gains from the data exploration. Therefore research in the area of privacy preservation is deemed important for both theoretical and practical reasons. PPDA 2009 was held in conjunction with DASFAA 2009 conference, and aims to bring together researchers in different fields related to privacy preserving data analysis and to provide a forum where researchers and practitioners can share and exchange their knowledge and experiences.

title: Seeing more than the graph: evaluation of multivariate graph visualization methods
abstract: Many real-world networks are multivariate, i.e., they have attributes associated with nodes and/or edges. Examples include social networks whose nodes represent people and edges represent relationships. There is usually information about each person (such as name, age, and gender) and the relationship (such type, duration, and strength). Besides common graph analysis tasks (such as identifying the most influential or structurally important nodes), there are more complex analyses for multivariate networks. One of these is the multivariate graph clustering, i.e., identifying clusters formed by nodes that have similar attributes and are close to each other in terms of graph distance. For instance, in social network analysis, it is interesting to sociologists whether or not people with similar characteristics (node attributes) are also connected to each other. Currently there are very few visualization methods available for such analysis.
 Graph and multivariate visualization have been well studied separately in the literature. Herman et al. summarized the recent work on graph visualization , and Wong and Bergeron covered the development in multivariate visualization . However, there is relatively less work available on multivariate network visualization. Two types of approaches are commonly used. The first one is the mapping approach, which maps attributes to visual elements of a node or edge. A simple example is to map one attribute to node size and another to node color . A more advanced mapping approach uses glyphs to represent node or edge attributes. One such example is to use the length and width of a rectangle node glyph to represent two node attributes . The second one is the 2.5D approach: it uses the third dimension to present the multivariate information, while the graph is shown on a 2D plane. Examples include the recently proposed "GraphScape" , which adopts a landscape metaphor: each attribute is represented by a two-and-a-half- dimensional surface, whose height indicates its value.
 Each approach has its strength and weakness. The mapping approach is effective of showing numerical value using visual element such as size, but it can be difficult to compare the value of attributes represented by different elements such as size and color. The problem is alleviated by a carefully designed glyph, but visual complexity increases quickly as the number of attributes that a glyph needs to represent grows. The 2.5D approach is good at showing the distribution of attribute values over the network, but the attribute surface could introduce occlusion and affect the visibility of underlying network.
 In this paper, we present a study evaluating the effectiveness of these two approaches for different analysis tasks. We compare the performance of mapping and 2.5D approach in a controlled lab environment. We included both simple tasks (such as identifying nodes with the largest attribute value) and complex tasks (such as multivariate graph clustering). The performance is measured both in terms of accuracy and completion time. The results indicate that statistically mapping approach performs better for the simple tasks, while the 2.5D approach is favored in the complex task. The outcomes from this study provide some guidelines for the design of effective multivariate graph visualization for different analysis tasks.

title: Test-Driven Component Integration with UML 2.0 Testing and Monitoring Profile
abstract: Test-driven development (TDD) is a software development methodology for achieving high reliability. However, the practice of TDD at the integration level is rare. In this paper, we propose a test-driven component integration approach with the support of UML 2.0 Testing and Monitoring Profile (U2TMP) that is also proposed in this paper. In our approach, automated integration-level test cases are specified using U2TMP before writing the glue-code that integrates components. U2TMP enhances UML 2.0 diagrams for specifying how test scenarios should be set up and how the integrated components are expected to interact under these scenarios. Test cases written in U2TMP can be automatically transformed into test artifacts that setup the test environment, generate test stimuli, and monitor the component interactions at runtime. These test cases serve as a guideline for writing the glue-code and a regression test- bed. With this approach, the software developers may produce glue-code of high reliability.

title: Intrinsic Wrench Estimation and Its Performance Index for Multisegment Continuum Robots
abstract: This paper presents the intrinsic capability of full-wrench estimation of multisegment continuum robots with multiple flexible backbones. Intrinsic-full-wrench estimation refers to the ability of continuum robots to also serve as force and moment sensors by using measurements of axial loads on their backbones. This end-effector-as-sensor approach fulfills the rapidly increasing needs for miniature-robotic-surgical tools with haptic sensing ability subject to various limitations, such as size, magnetic resonance imaging (MRI) compatibility, sterilizability, etc. A performance index for the intrinsic wrench-sensing capability is introduced and evaluated to show how this index can serve as a design guide for continuum robots that provide force sensing.

title: Formally defining a graphical language for monitoring and checking object interactions
abstract: Monitoring and checking object interactions is an important activity for testing/debugging scenario implementation in an object-oriented system. In our previous work, we proposed behavior view diagrams (BVD) as a graphical language for writing programs that automate such monitoring and checking process. In this paper, we illustrate the formal definition of the syntax and the semantics of an extended version of BVD that can also be used to describe multi-threaded scenarios. This formal definition provides a critical foundation both for understanding the language and for building its tool support.

title: System design of an Insertable Robotic Effector Platform for Single Port Access (SPA) Surgery
abstract: This paper presents a novel design and preliminary kinematic analysis of an Insertable Robotic Effector Platform (IREP) for Single Port Access (SPA) Surgery. The IREP robot can be deployed into body cavity through a Ø15mm skin incision to perform SPA procedures. It consists of two snake-like continuum robots as slave surgical assistants for tissue manipulation, two parallelogram mechanisms for the continuum robots' placement, and one controllable stereo vision module with integrated light source for depth perception and tool tracking. Design considerations and alternatives, calculations and preliminary simulations of this 17-DoF surgical robotic system are presented in this paper. The overall control system hierarchy for tele-manipulation using the IREP robot is also presented.

title: Testing Scenario Implementation with Behavior Contracts
abstract: This paper presents behavior contracts as a new assertion mechanism and a tool that uses such contracts to support the testing of object-oriented (OO) systems. A behavior contract models how the scenarios for performing a designated task are expected to be implemented. Based on this contract, our tool can automatically monitor the program execution for checking important properties related to these scenarios. This capability can help testers to determine whether the scenarios have been implemented correctly. Our tool can also collect test coverage information w.r.t. the scenarios modeled by a behavior contract. Such information can be used to direct the testing efforts towards the less-covered scenarios, and to determine whether the implementation of these scenarios has been adequately tested. Therefore, using this tool should improve both the efficiency and effectiveness of testing OO systems