23 papers · ranked by Valyu relevance
Zuguang Gu
Heatmap is a widely used statistical visualization method on matrix-like data to reveal similar patterns shared by subsets of rows and columns. In the R programming language, there are many packages that make heatmaps. Among them, the ComplexHeatmap package provides the richest toolset for constructing highly…
João Palmeiro, Beatriz Malveiro, Rita Costa, David Polido + 2 more
The overview visualization shows how the features diverged from their reference over time (R1, R2). The main element of the application is the heatmap (Figure 2.A), where each cell color represents the p-value for a given feature at a time instance. - Tripartite color scale: The legend on top of the heatmap describes…
Tian-Xin Zhao, Ze-Lin Wang
Here, we present GraphBio, a shiny web app to easily perform visualization analysis for omics data. GraphBio provides 15 popular visualization analysis methods, including heatmap, volcano plots, MA plots, network plots, dot plots, chord plots, pie plots, four quadrant diagrams, venn diagrams, cumulative distribution…
Wubin Ding, David Goldberg, Wanding Zhou
PyComplexHeatmap was designed to visualize matrix data and associated metadata through sophisticated, richly annotated heatmap layouts. We have integrated the R grammar-of-graphics semantics with the Python-native matplotlib/Pandas-based data science ecosystem, allowing users to utilize built-in matplotlib colormaps…
Sarah Sohana, William Pourmajidi, John Steinbacher, Andriy Miranskyy
—Cloud computing is essential for modern enterprises, requiring robust tools to monitor and manage Large-Scale Cloud Systems (LCS). Traditional monitoring tools often miss critical insights due to the complexity and volume of LCS telemetry data. This paper presents CLOUDHEATMAP, a novel heatmap-based visualization tool…
Eugénie Lohmann, Laurent Gorvel, Samuel Granjeaud
High-content cytometry is an important technique in clinical research, producing data that is rich and complex to analyze. The resulting clusters of cells must be profiled to determine their role and function, and analyzed to identify changes in cell frequency or marker intensity. The heat map is the most suitable tool…
Yan Liu, Melissa Allen‐Dumas
Heatmap is a common geovisualization method that interpolates and visualizes a set of point observations on a map surface. Most of online web mapping libraries implement a one-pass heatmap algorithm using HTML5 canvas or WebGL for efficient heatmap generation. However, such implementation applies additive operations…
Eckehard Hermann, Harald Lampesberger
—Traditional two-dimensional risk matrices (heatmaps) are widely used to model and visualize likelihood and impact relationships, but they face fundamental methodological limitations when applied to complex infrastructures. In particular, regulatory frameworks such as NIS2 and DORA call for more context-sensitive and…
Rujia Chen, Akbar Ghobakhlou, Ajit Narayanan
Introduction Musical instrument recognition is a critical component of music information retrieval (MIR), aimed at identifying and classifying instruments from audio recordings. This task poses significant challenges due to the complexity and variability of musical signals. Methods In this study, we employed…
Yejin Lee, Kwangtae Jung, Marino Menozzi
In safety-critical systems like nuclear power plants, the rapid and accurate perception of visual interface information is vital. This study investigates the relationship between visual attention dispersion measured via heatmap entropy (as a specific measure of gaze entropy) and response time during information search…
Himaghna Bhattacharjee, Jackson Burns, Dionisios Vlachos
The recent advances in deep learning, generative modeling, and statistical learning have ushered in a renewed interest in traditional cheminformatics tools and methods. Quantifying molecular similarity is essential in molecular generative modeling, exploratory molecular synthesis campaigns, and drug-discovery…
Yi-Heng Du, Jing-Hua Mu
Genome sequencing has revolutionized the study of biological systems, enabling exploration of species origins, evolution, and identification. However, traditional methods for constructing phylogenetic trees based on raw sequence data require substantial computational resources and may be challenging for biologists with…
Hefei Zhao, Selina C. Wang, Tao Huang
With innovations and advancements in analytical instruments and computer technology, omics studies based on statistical analysis, such as phytochemical omics, oilomics/lipidomics, proteomics, metabolomics, and glycomics, are increasingly popular in the areas of food chemistry and nutrition science. However, a remaining…
Juntong Chen, Huayuan Ye, Zhu He, Siwei Fu + 2 more
Fig. 1: We propose a novel spatiotemporal visualization pipeline leveraging imputation reference data produced by GNNs to generate more reliable and accurate heatmaps (A). Various sources of uncertainties in the data-to-mapping process are visualized(B). Additionally, our model can also increase the temporal resolution…
Alexander P. Sweeten, Michael C. Schatz, Adam M. Phillippy
A common method for analyzing genomic repeats is to produce a sequence similarity matrix visualized via a dot plot. Innovative approaches such as StainedGlass have improved upon this classic visualization by rendering dot plots as a heatmap of sequence identity, enabling researchers to better visualize multi-megabase…
Thomas C Smits, Nikolay Akhmetov, Tiffany S Liaw, Mark S Keller + 3 more
scellop is available as a Python package on PyPI ([https://pypi.org/project/scellop/]()) and a JavaScript package on npm ([https://www.npmjs.com/package/scellop]()). The Python package provides a Jupyter widget implemented with anywidget (). scellop is implemented in React, using visx ([https://airbnb.io/visx/]()) to…
Angelo L. De Castro, Jin Wang, Jessica G. Bonney-King, Gota Morota + 2 more
Monitoring the movement patterns of dairy cattle can provide important insight into space utilization or space occupancy in a barn. Although several precision livestock technologies have been developed to record dairy cattle movements, there is a lack of open source tools to track and visualize cattle movement…
Christina Humer, Rachel Nicholls, Henry Heberle, Moritz Heckmann + 7 more
Chemical reaction optimization (RO) is an iterative process that results in large and high-dimensional datasets. Current tools only allow for limited analysis and understanding of parameter spaces, making it hard for scientists to review or follow changes throughout the process. With the recent emergence of using…
Kevin Mildau, Christoph Büschl, Jürgen Zanghellini, Justin J.J. van der Hooft
Computational metabolomics workflows have revolutionized the untargeted metabolomics field. However, the organization and prioritization of metabolite features remains a laborious process. Organizing metabolomics data is often done through mass fragmentation-based spectral similarity grouping, resulting in feature sets…
Ye Tao, Anand D. Sarwate, Sandeep Panta, Jessica Turner + 2 more
Data visualizations are an integral part of neuroimging research, supporting activities ranging from exploratory data analysis to the interpretation and communication of findings. While essential, visualizations can also reveal private information about individual participants. In this paper, we discuss how…
Himaghna Bhattacharjee, Jackson Burns, Dionisios Vlachos
The recent advances in deep learning, generative modeling, and statistical learning have ushered in a renewed interest in traditional cheminformatics tools and methods. Quantifying molecular similarity is essential in molecular generative modeling, exploratory molecular synthesis campaigns, and drug-discovery…
Himaghna Bhattacharjee, Jackson Burns, Dionisios Vlachos
The recent advances in deep learning, generative modeling, and statistical learning have ushered in a renewed interest in traditional cheminformatics tools and methods. Quantifying molecular similarity is essential in molecular generative modeling, exploratory molecular synthesis campaigns, and drug-discovery…
Murat Cihan Sorkun, Dajt Mullaj, J. M. Vianney A. Koelman, Süleyman Er
Visualizing chemical spaces streamlines the analysis of molecular datasets by reducing the information to human perception level, hence it forms an integral piece of molecular engineering, including chemical library design, high-throughput screening, diversity analysis, and outlier detection. We present here ChemPlot…