UNLABELLED: RIPPER is a framework for mass-spectrometry-based label-free relative quantification for proteomics and metabolomics studies. RIPPER combines a series of previously described algorithms for pre-processing, analyte quantification, retention time alignment, and analyte grouping across runs. It is also the first software framework to implement proximity-based intensity normalization. RIPPER produces lists of analyte signals with their unnormalized and normalized intensities that can serve as input to statistical and directed mass spectrometry (MS) methods for detecting quantitative differences between biological samples using MS. AVAILABILITY AND IMPLEMENTATION: http://www.z.umn.edu/ripper CONTACT: [email protected] SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

In biomechanics studies, researchers collect, via experiments or simulations, datasets with hundreds or thousands of trials, each describing the same type of motion (e.g., a neck flexion-extension exercise) but under different conditions (e.g., different patients, different disease states, pre- and post-treatment). Analyzing similarities and differences across all of the trials in these collections is a major challenge. Visualizing a single trial at a time does not work, and the typical alternative of juxtaposing multiple trials in a single visual display leads to complex, difficult-to-interpret visualizations. We address this problem via a new strategy that organizes the analysis around motion trends rather than trials. This new strategy matches the cognitive approach that scientists would like to take when analyzing motion collections. We introduce several technical innovations making trend-centric motion visualization possible. First, an algorithm detects a motion collection's trends via time-dependent clustering. Second, a 2D graphical technique visualizes how trials leave and join trends. Third, a 3D graphical technique, using a median 3D motion plus a visual variance indicator, visualizes the biomechanics of the set of trials within each trend. These innovations are combined to create an interactive exploratory visualization tool, which we designed through an iterative process in collaboration with both domain scientists and a traditionally-trained graphic designer. We report on insights generated during this design process and demonstrate the tool's effectiveness via a validation study with synthetic data and feedback from expert musculoskeletal biomechanics researchers who used the tool to analyze the effects of disc degeneration on human spinal kinematics.

The Gene Ontology Consortium built the Gene Ontology database (GO) to address the need for a common standard in naming genes and gene products. Using different names for the same concepts and different concepts with the same name makes it effectively impossible for humans and computers alike to analyze biological processes across different organisms. The consortium addresses this need by defining terms for categorizing genes and gene products. A convention in GO is that each gene or gene product is annotated to the most specific GO term in the GO database. It is, however, also useful for researchers to be able to group genesor gene products into broad biological categories that give a higher-level view of their function when analyzing results of an experiment. A GO Slim is a subset of the GO ontology that provides such a higher-level view of functions. Existing GO Slim generation tools have two important limitations: programming language dependence, and an inability to dynamically generate a GO Slim while analyzing. We have extended the relational database engine to dynamically generate a GO Slim overcoming this limitations. Using this extension, we have developed a tool (Dynamic GOSlim) that dynamically generates a GO Slim and uses the generated GO Slim to categorize genes or gene products. This tool is being used in an ongoing proteomics project aimed at identifying possible oral cancer biomarkers in saliva.

Database systems instructors face an ongoing challenge to develop meaningful assignments for their courses. We have found that instructors can successfully use large scientific datasets in teaching a database systems course to better prepare students for real-world database systems work.

To create an innovative interactive multimedia application, a multimedia designer needs to rapidly explore numerous behavioral design ideas early in the design process, as creating innovative behavior is the cornerstone of creating innovative multimedia. Current tools and techniques do not support a designer's need for early behavior exploration, limiting her ability to rapidly explore and effectively communicate behavioral design ideas. To address this need, we have developed a sketch-based, interactive multimedia storyboard tool that uses a designer's ink strokes and textual annotations as an input design vocabulary. By operationalizing this vocabulary, the tool transforms an otherwise static sketch into a working example. The behavioral sketch can be quickly edited using gestures and an expressive visual language. By enabling a designer to explore and communicate behavioral design ideas using working examples early in the design process, our tool facilitates the creation of a more effective, compelling, and entertaining multimedia application.

As users continue offloading more control and responsibility to the computer, coordinating the asynchronous interactions between the user and computer is becoming increasingly important. Without proper coordination, an application attempting to gain the user's attention risks interrupting the user in the midst of performing another task. To justify why an application should avoid interrupting the user whenever possible, we designed an experiment measuring the disruptive effect of an interruption on a user's task performance. The experiment utilized six Web-based task categories and two categories of interruption tasks. The results of the experiment demonstrate that: (i) a user performs slower on an interrupted task than a non-interrupted task, (ii) the disruptive effect of an interruption differs as a function of the task category, and (iii) different interruption tasks cause similar disruptive effects on task performance. These results empirically validate the need to better coordinate user interactions among applications that are competing for the user's attention.

Serial periodic data exhibit both serial and periodic properties. For example, time continues forward serially, but weeks, months, and years are periods that recur. While there are extensive visualization techniques for exploring serial data, and a few for exploring periodic data, no existing technique simultaneously displays serial and periodic attributes of a data set. We introduce a spiral visualization technique, which displays data along a spiral to highlight serial attributes along the spiral axis and periodic ones along the radii. We show several applications of the spiral visualization to data exploration tasks, present our implementation, discuss the capacity for data analysis, and present findings of our informal study with users in data-rich scientific domains. Keywords Information Visualization, Spiral, Data Visualization, Interactive Data Exploration, Serial Periodic Data. INTRODUCTION Information visualization is the practice of mapping data sets into visual media for...

Information visualization faces challenges presented by the need to represent abstract data and the relationships within the data. Previously, we presented a system for visualizing similarities between a single DNA sequence and a large database of other DNA sequences (E.H. Chi et al., 1995). Similarity algorithms generate similarity information in textual reports that can be hundreds or thousands of pages long. Our original system visualized the most important variables from these reports. However, the biologists we work with found this system so useful they requested visual representations of other variables. We present an enhanced system for interactive exploration of this multivariate data. We identify a larger set of useful variables in the information space. The new system involves more variables, so it focuses on exploring subsets of the data. We present an interactive system allowing mapping of different variables to different axes, incorporating animation using a time axis, and providing tools for viewing subsets of the data. Detail-on-demand is preserved by hyperlinks to the analysis reports. We present three case studies illustrating the use of these techniques. The combined technique of applying a time axis with a 3D scatter plot and query filters to visualization of biological sequence similarity data is both powerful and novel.

Biological sequence similarity analysis presents visualization challenges, primarily because of the massive amounts of discrete, multi dimensional data. Genomic data generated by molecular biologists is analyzed by algorithms that search for similarity to known sequences in large genomic databases. The output from these algorithms can be several thousand pages of text, and is difficult to analyze because of its length and complexity. We developed and implemented a novel graphical representation for sequence similarity search results, which visually reveals features that are difficult to find in textual reports. The method opens new possibilities in the interpretation of this discrete, multidimensional data by enabling interactive investigation of the graphical representation.

In laboratories around the world, neuroscientists from diverse disciplines are exploring various aspects of brain structure. Because of the size of the domain, neuroscientists must specialize, making it difficult to fit results together, causing some research efforts to be duplicated because of lack of sharing of information. The authors have begun a long-term project to build a neuroscience research database for brain structure. One aspect of the database is the ability to visualize high-quality, high-resolution micrographs montaged together into 3-D structures as they were in the living brain. As demonstrated in this paper's analysis, realistic presentation of these visualizations across computer networks will stress current and proposed gigabit networks. Image compression can reduce network loads, but wide-spread use of the visualizations will still require networks capable of sustaining terabits per second of throughput.>

The fundamental reason for database management systems is the support of applications using shared overlapping sets of data through external views of an underlying conceptual schema. The definition of such a schema for expert systems (ESs) is a topic of interest to database researchers both as a proof that ESs can be supported and as an exploration of the process of view integration. A shared conceptual schema has been constructed for four widely known medical ESs, and can be mapped to the knowledge base of each using seven operations: COMPOSE, FILTER, FOLD, UNFOLD, CONTRACT, RENAME, and CONSTRAIN. The schema and mappings show features the ESs share, such as rules and patterns, and features that distinguish them, such as a unique form of diagnosis. The schema's content shows a lack of structural, temporal, or strategic information and illustrates how the types and relationships of shell-like systems are hidden in instances and must be interpreted by program code.>

The relational algebra operator division is misnamed, hard to understand and insufficient. This paper explains division and presents HAS, a generalization of division which is useful for answering questions about an M-M relationship between entities.

As database applications have become more sophisticated, the development of support tools for database design has become more critical. Before support tools can be developed, however, the nature of database design problems and their solutions must be well defined. We apply data modelling principles to these tasks. The result is a multi level model of databases. The logical level describes database design problems and the physical level describes their solutions. This model is the basis for a computer aided database design methodology developed by the authors.