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Abstract Analyses of large ensemble data on future climate are significantly useful for the probabilistic future projection of climate change in various interdisciplinary fields. However, the data volume of the Database for Policy Decision making for Future climate change or d4PDF, which is a mega-ensemble dataset, exceeds ∼ 3 PB, which is too large to download to local computers. To allow users for retrieve and downloading necessary data, we developed a user-friendly system called “System for Efficient content-based retrieval to Analyze Large volume climate data” (SEAL) under the Social Implementation Program on Climate Change Adaptation Technology (SI-CAT). Conventional web-based retrieval systems allow retrievals using metadata associated with a data file itself. In contrast, SEAL allows the users to retrieve the necessary data by using metadata associated with contents, such as physical values, of a data file. We confirmed that SEAL can reduce data sizes and total time required for obtaining necessary data to less than 0.5% and 1%, respectively, compared to conventional web-based retrieval systems.

To improve visualization, it is necessary to optimize the design by analyzing the behavior of users as well as improving the evaluation index of the computational experiment and the task performance (e.g., the correct answer rate and completion time) in the user experiment. Although various studies have investigated the influence of user behavior on the evaluation of visualization, majority of these studies focused on simple visualization tasks. A simple task does not indicate a simple visualization comprising a few visualization elements but a task in which the information obtained from visualization is the only clue for completing the task. However, a few studies have targeted complicated tasks in which multiple information obtained from visualization is considered to be a clue for completing the task regardless of the number of elements that are contained in the visualization. Therefore, in this study, we investigated the behavior of the participants who have performed complicated tasks. We selected two types of group-in-a-box (GIB) layouts, which can be considered to be a complicated visualization method, as the target of the user experiment. In the user experiment, participants were asked to perform an exploration task specific to GIB layouts; which group has the maximum number of intra-edges? We also collected the eye-tracking data in addition to task performance. The results showed that the correct answer rate is considerably affected by the visualization factor; whether the correct answer, the box with maximum number of intra-edges, is the box with the largest area. Furthermore, an analysis of the collected eye-tracking data revealed that this visualization factor affected the exploration behavior of the participants; however, it did not affect the location at which the participants were focused on. The obtained results indicated that the visualization elements that were not considered by the visualization designer can influence the task of extracting information from the data. Therefore, designers have to configure the visualization by considering the visual cognitive behavior of the users. Keywords: Visual search, Eye-tracking, Group-in-a-box layout

In most species, calcium waves in the oocyte are considered common phenomena in the activation of eggs. However, the mechanism of calcium waves has not yet been clarified. By collaborating with biologists studying Caenorhabditis elegans (C. elegans), which is widely used as a model organism, we observed that the following requirements must be satisfied to form a useful hypothesis based on calcium waves captured using high-speed in vivo imaging: (1) the ability to obtain an overview of how the calcium waves are propagated and (2) the ability to understand the propagation of waves in a narrow region. However, conventional visualization methods cannot satisfy these requirements simultaneously. Therefore, we propose a visual analytics system that allows users to understand and explore calcium wave images using cross-correlation analysis of the time-series data of the Ca2+ fluorescence intensity at each point. The interface of this system comprises an overview visualization, a detail visualization, and user interactions to satisfy these requirements and realize exploratory visualization. Some views present an overview visualization that displays the clustering results of a directed graph calculated using cross-correlation analysis. These views enable the users to understand the overview of wave propagation, thereby helping users find a region of interest. The detail visualization shows the relationship between the region of interest and other areas. Furthermore, users can use the proposed system with overview-detail and brush-link exploration to assign meaning to the region of interest and construct a hypothesis for its role. In this paper, we demonstrate how the proposed visual analytics approach works and how new hypotheses can be formed using the analysis of C. elegans calcium waves. Keywords: Visual Knowledge Discovery, Time Series Data, Bioinformatics Visualization

We propose a novel interactive parameter optimization technique which asks users to determine whether further exploration is required by using a hierarchical visualization technique. Our technique generates a k-d tree and uses the coefficient of multiple determinations (R2) for tree-branching; however, this requires a huge amount of computation since it processes the response surface at every leaf node of the k-d tree, including those that may not have minimum parameters. To solve the problem, we introduce human evaluation of the display on the computer screen, in which every tree-node is evenly displayed regardless of its hierarchical level. We confirmed the effectiveness of the proposed technique by searching for pre-determined parameters in some test functions and biological cell simulation results.

BACKGROUND: Activation of caspases is crucial for the execution of apoptosis. Although the caspase cascade associated with activation of the initiator caspase-8 (CASP8) has been investigated in molecular and biochemical detail, the dynamics of CASP8 activation are not fully understood. METHODOLOGY/PRINCIPAL FINDINGS: We have established a biosensor based on fluorescence resonance energy transfer (FRET) for visualizing apoptotic signals associated with CASP8 activation at the single-cell level. Our dual FRET (dual-FRET) system, comprising a triple fusion fluorescent protein, enabled us to simultaneously monitor the activation of CASP8 and its downstream effector, caspase-3 (CASP3) in single live cells. With the dual-FRET-based biosensor, we detected distinct activation patterns of CASP8 and CASP3 in response to various apoptotic stimuli in mammalian cells, resulting in the positive feedback amplification of CASP8 activation. We reproduced these observations by in vitro reconstitution of the cascade, with a recombinant protein mixture that included procaspases. Furthermore, using a plasma membrane-bound FRET-based biosensor, we captured the spatiotemporal dynamics of CASP8 activation by the diffusion process, suggesting the focal activation of CASP8 is sufficient to propagate apoptotic signals through death receptors. CONCLUSIONS: Our new FRET-based system visualized the activation process of both initiator and effector caspases in a single apoptotic cell and also elucidated the necessity of an amplification loop for full activation of CASP8.