23 papers · ranked by Valyu relevance
Neli Fonseca, Amudha Kumari Duraisamy, Zhe Wang, Sriram Somasundharam + 8 more
The cryogenic sample-electron microscopy (cryoEM) field has generated significant amounts of 3D Electron Microscopy (3DEM) volumetric data and associated metadata, now comprehensively archived in the Electron Microscopy Data Bank (EMDB - www.emdatabank.org) and the Electron Microscopy Public Image Archive (EMPIAR -…
Hector Torres, Efe Ozturk, Zhou Fang, Nicholas Zhang + 4 more
Biomedical data visualization is critical for interpreting complex datasets, yet the clarity and quality of visualizations vary widely across tools and applications. This study introduces a comprehensive framework for evaluating biomedical figures and benchmarking visualization platforms. We developed Metrics for…
Muhammad Zain Butt, Rana Sheraz Ahmad, Eman Fatima, Muhammad Tahir ul Qamar
The application of Large Language Models (LLMs) for generating data visualizations through natural language interaction represents a promising advance in AI-assisted scientific analysis. However, existing LLM-based tools largely emphasize graph generation, while research workflows require not only visualization but…
Naomi Cahill, Jiaying Lai, Izuchukwu Okpalanwaka, Dominik Boehm + 11 more
Background Complex and expanding datasets in clinical oncology applications require flexible and interactive visualization of patient data to provide physicians and other medical professionals with maximum amount of information. In particular, interdisciplinary tumor conferences profit from customized tools to…
Yunxing Liu, Zhangfan Shen
In scenarios where driving decisions must be made rapidly, an optimally designed dashboard is crucial for maintaining driver concentration and facilitating precise decision-making. This study examines the influence of four principal aspects of dashboard design-graphical form, scale precision, indicator type, and…
Ouxun Jiang, Camillia Matuk, Madhumitha Gopalakrishnan, Wen Xu + 5 more
Data visualizations are used widely to help people see patterns in data across research, policy, education, and business. Computer screens allow these visualizations to become animated, which can effectively show processes of change. While animations can be engaging, ineffective design can also make them confusing or…
Julien Barnier, Cassandra Bompard, Aurélie Siberchicot, Vincent Navratil + 2 more
The need to visualize data associated with NCBI Taxonomy Identifiers (taxids) is growing in various biological fields ranging from comparative genomics to metagenomics and metabarcoding, and even for outreach. No tool today allows to visualize such data while still keeping the full vision of the whole taxonomy…
Yunhai Wang, Kecheng Lu, Junhao Chen, Alper Sarikaya + 1 more
We present Flint, an intermediate language that enables authors to create high-quality visualizations from concise, semantics-driven specifications without explicitly configuring low-level parameters such as scales, axes, and formatting. Unlike prior systems that infer default configurations from surface-level data…
Xiaolin Wen, Changlin Li, Manusha Karunathilaka, Can Liu + 2 more
Many expressive visualizations are shared online only as bitmap images, making them difficult to redesign or adapt to new data. Reusing such image-based visualizations requires substantial expertise and is often time-consuming, even for experienced visualization practitioners. Existing work on reproducing…
Laura Lotteraner, Anna Kurtenkova, Torsten Möller, Daniel Pahr
A range of charts with different strengths and weaknesses exists to support the visual analysis of univariate distributions, with a limited understanding of which charts best support which tasks and users, and how practitioners use charts. We categorize the available charts for univariate distributions into four groups…
Arran Zeyu Wang, David S. Borland, Estella Calcaterra, Gotz + 1 more
—Understanding how individuals interpret charts is a crucial concern for visual data communication. This imperative has motivated a number of studies, including past work demonstrating that causal priors—a priori beliefs about causal relationships between concepts—can have significant influences on the perceived…
Sverre Branders, Manfred G. Grabherr, Rafi Ahmad
Integrating different types of biological data is often challenging due to the presence of both numerical and categorical data. This complexity makes it harder to evaluate causal biological effects, especially when confounders like population structure, sampling methods, or multi-omics integration can lead to incorrect…
Emma Gairin, Vincent Laudet, Marcela Herrera
Interpreting high-dimensional omics datasets requires visualisation tools that reveal coordinated responses across multiple biological processes. Existing approaches such as heatmaps or enrichment plots typically present processes independently and struggle to convey system-level patterns as experimental complexity…
Panos Kalnis. Shuo Shang, Christian S. Jensen
Spatio-temporal data captures complex dynamics across both space and time, yet traditional visualizations are complex, require domain expertise and often fail to resonate with broader audiences. Here, we propose MapMuse, a storytelling-based framework for interpreting spatio-temporal datasets, transforming them into…
Leni Yang, Aymeric Ferron, Yvonne Jansen, Pierre Dragicevic
The display dimension captures the type of devices or medium that is used to present the information objects. 2D screens include mobile phones, desktop monitors, and wallsized screens that display information objects on a two-dimensional surface. This display type allows visualization designs to be shared very broadly…
Liza Hadley, Nick Holliman, Kai Xu, Edyta Bogucka + 5 more
Communicating scientific ideas to policy actors is a longstanding challenge, especially in epidemiological modeling where evidence is inherently uncertain. Central to this communication is visualization-the graphic representation of complex epidemiological modeling concepts through figures, plots, and charts. Effective…
Authors not listed
Large Language Models have demonstrated impressive capabilities in natural language understanding and processing. However, as AI and LLMs continue to evolve, their ability to accurately and efficiently interpret data from scientific figures and plots remains obscure. In this study, we test and evaluate the ability of…
Chloe Hudson Prock, Enrico Bertini, Michael Correll
What do we value in our visualizations, and in the people who design them? Despite a growing body of work on critical data visualization, the conception of what it is to do ethical data visualization work can often be narrow (for instance, holding that our ethical duties are discharged merely by avoiding overtly lying…
Authors not listed
Here, we present MolPic, an open-source Python-based software that can be used to generate high-resolution, publication-quality molecular figures directly from compound names or SMILES strings. MolPic supports single-molecule rendering, batch processing, and automated multi-panel 2D figure generation, which are…
Authors not listed
Nuclear magnetic resonance (NMR) spectroscopy is a powerful analytical tool that can be used to determine the structures of both small organic molecules and large biomacromolecules. Many undergraduate students are exposed to NMR spectral analysis during organic chemistry courses, but few students have the opportunity…
Authors not listed
Untargeted metabolomics is a powerful approach for exploring the chemical diversity and dynamics of biological systems. However, the types of questions that can be addressed depend not only on experimental design but also on the data processing and analysis workflows employed, many of which require advanced…
Authors not listed
Next Generation Risk Assessment (NGRA) promotes animal-free, exposure-informed, and hypothesis-driven approaches to chemical safety assessment. In silico tools, such as quantitative structure-activity relationship (QSAR) models, are valuable new approach methodologies (NAMs) for use in NGRA. However, the practical…
Authors not listed
Mass spectrometry (MS) generates large datasets that are stored in increasingly optimized and complex file types, demanding technical expertise to extract information rapidly and easily. We wondered whether a simple structured query language (SQL) database could hold raw MS data and allow for easily readable queries…