CancerLinker: Explorations of Cancer Study Network

Interactive visualization tools are highly desirable to biologist and cancer researchers to explore the complex structures, detect patterns and find out the relationships among bio-molecules responsible for a cancer type. A pathway contains various bio-molecules in different layers of the cell which is responsible for specific cancer type. Researchers are highly interested in understanding the relationships among the proteins of different pathways and furthermore want to know how those proteins are interacting in different pathways for various cancer types. Biologists find it useful to merge the data of different cancer studies in a single network and see the relationships among the different proteins which can help them detect the common proteins in cancer studies and hence reveal the pattern of interactions of those proteins. We introduce the CancerLinker, a visual analytic tool that helps researchers explore cancer study interaction network. Twenty-six cancer studies are merged to explore pathway data and bio-molecules relationships that can provide the answers to some significant questions which are helpful in cancer research. The CancerLinker also helps biologists explore the critical mutated proteins in multiple cancer studies. A bubble graph is constructed to visualize common protein based on its frequency and biological assemblies. Parallel coordinates highlight patterns of patient profiles (obtained from cBioportal by WebAPI services) on different attributes for a specified cancer studyComment: 7 pages, 9 figure

Outliagnostics: Visualizing Temporal Discrepancy in Outlying Signatures of Data Entries

This paper presents an approach to analyzing two-dimensional temporal datasets focusing on identifying observations that are significant in calculating the outliers of a scatterplot. We also propose a prototype, called Outliagnostics, to guide users when interactively exploring abnormalities in large time series. Instead of focusing on detecting outliers at each time point, we monitor and display the discrepant temporal signatures of each data entry concerning the overall distributions. Our prototype is designed to handle these tasks in parallel to improve performance. To highlight the benefits and performance of our approach, we illustrate and validate the use of Outliagnostics on real-world datasets of various sizes in different parallelism configurations. This work also discusses how to extend these ideas to handle time series with a higher number of dimensions and provides a prototype for this type of datasets.Comment: in IEEE Visualization in Data Science (IEEE VDS) (2019

JavaScript Implementation of Scagnostics and Its Applications

Scagnostics is a set of features that characterizes the 2D distributions in the underlying data. Various real-world applications have been using Scagnostics visual features to detect unusual bivariate data correlations. Concomitantly, many applications are required to be implemented on web platforms due to their accessibility and convenience. Therefore, this chapter discusses a recent JavaScript implementation of Scagnostics, an extension to higher dimensional data, and its applications in detecting abnormalities in bivariate and multivariate time series data. Its implementation in JavaScript supports the tremendous demand for visual features in the web environment. Likewise, its higher dimensional implementations allow generating Scagnostics features for the rapidly growing multivariate data. Finally, conventional ScagnosticsJS computations involve time-consuming algorithms, and they are sensitive to slight changes in the underlying data. Therefore, this chapter also discusses a recent attempt to tackle these issues using machine learning to estimate the Scagnostics scores

TGF-β inhibitor Smad7 regulates dendritic cell-induced autoimmunity

TGF-β is an anti-inflammatory cytokine whose signaling is negatively controlled by Smad7. Previously, we established a role for Smad7 in the generation of autoreactive T cells; however, the function of Smad7 in dendritic cells (DCs) remains elusive. Here, we demonstrate that DC-specific Smad7 deficiency resulted in elevated expression of the transcription factors Batf3 and IRF8, leading to increased frequencies of CD8(+)CD103(+) DCs in the spleen. Furthermore, Smad7-deficient DCs expressed higher levels of indoleamine 2,3-dioxygenase (IDO), an enzyme associated with tolerance induction. Mice devoid of Smad7 specifically in DCs are resistant to the development of experimental autoimmune encephalomyelitis (EAE) as a result of an increase of protective regulatory T cells (Tregs) and reduction of encephalitogenic effector T cells in the central nervous system. In agreement, inhibition of IDO activity or depletion of Tregs restored disease susceptibility. Intriguingly, when Smad7-deficient DCs also lacked the IFN-γ receptor, the mice regained susceptibility to EAE, demonstrating that IFN-γ signaling in DCs mediates their tolerogenic function. Our data indicate that Smad7 expression governs splenic DC subset differentiation and is critical for the promotion of their efficient function in immunity

BlocklyAR: A Visual Programming Interface for Creating Augmented Reality Experiences

State-of-the-art tools for creating augmented reality (AR) applications often depend on a specific programming language and the deployed target devices. The typing syntax of a program is error-prone, and device dependency makes it difficult to share newly created AR applications. This paper presents BlocklyAR, a novel web-based visual programming interface for creating and generating an AR application. This tool is intended for non-programmers (young learners and enthusiasts) who are interested in making an AR application. The goals of this tool are: (1) to help young learners and enthusiasts express their programming ideas without memorizing syntax, (2) to enable users to perceive their expressions, (3) to enable learners to generate an AR application with minimal effort, and (4) to support users by allowing them to share newly created AR applications with others. BlocklyAR uses Blockly for creating a palette of commands and AR.js for transcribing commands into AR experience. The applicability of BlocklyAR was demonstrated through a use case where an existing AR application was recreated by using our tool. The result showed that our tool could yield an equivalent product. We evaluated the visual tool with the help of 66 users to gather perspectives on the specific benefits of employing BlocklyAR in producing an AR application. The technology acceptance model was adapted to assess an individual’s acceptance of information technology