The goal of What-if Hypothetical Implementations in Minecraft (WHIMC) is to develop computer simulations that engage, excite, and generate interest in science. WHIMC leverages Minecraft as a learning environment for learners to interactively explore the scientific consequences of alternative versions of Earth via “what if?” questions, such as “What if the earth had no moon?” or “What if the earth were twice its current size?” Learners using our mods are invited to make observations and propose scientific explanations for what they see as different. Given ongoing discoveries of potentially habitable worlds throughout the Galaxy, such questions have high relevance to public discourse around space exploration, conditions necessary for life, and the long-term future of the human race. Studies in our project are occurring across three informal learning settings: museum exhibits, after school programs, and summer camps. Our research is driven by the following research questions: 1. What technology-based triggers of interest have the strongest influence on interest? 2. Which contextual factors are most important for supporting long-term interest development? 3. And, what kinds of technology-based triggers are most effective for learners from audiences who are underrepresented in STEM?
more »
« less
This content will become publicly available on February 3, 2026
Visualizing Cell Structures with Minecraft
ABSTRACT Many microscopic images and simulations of cells give results in different kinds of formats, making it difficult for people lacking computational skills to visualize and interact with them. Minecraft—known for its three-dimensional, open-world, voxel-based environment—offers a unique solution by allowing the direct insertion of voxel-based cellular structures from light microscopy and simulations into its worlds without modification. This integration enables Minecraft players to explore the ultrastructure of cells in a highly immersive and interactive environment. Here, we demonstrate several workflows that can convert images and simulation results into Minecraft worlds. Using the workflows, students can easily import and interact with a variety of cellular content, including bacteria, yeast, and cancer cells. This approach not only opens new avenues for science education but also demonstrates the potential of combining scientific visualization with interactive gaming platforms for facilitating research and improving appreciation of cellular structure for a broad audience.
more »
« less
- PAR ID:
- 10594580
- Publisher / Repository:
- The Biophysicist
- Date Published:
- Journal Name:
- The Biophysicist
- ISSN:
- 2578-6970
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
Abstract Interactive visual analysis has many advantages, but an important disadvantage is that analysis processes and workflows cannot be easily stored and reused. This is in contrast to code‐based analysis workflows, which can simply be run on updated datasets, and adapted when necessary. In this paper, we introduce methods to capture workflows in interactive visualization systems for different interactions such as selections, filters, categorizing/grouping, labeling, and aggregation. These workflows can then be applied to updated datasets, making interactive visualization sessions reusable. We demonstrate this specification using an interactive visualization system that tracks interaction provenance, and allows generating workflows from the recorded actions. The system can then be used to compare different versions of datasets and apply workflows to them. Finally, we introduce a Python library that can load workflows and apply it to updated datasets directly in a computational notebook, providing a seamless bridge between computational workflows and interactive visualization tools.more » « less
-
Abstract Robotic systems often struggle to adapt to dynamic, unstructured environments due to top-down design constraints based on human assumptions. Inspired by biological morphogenesis, this study introduces a cellular plasticity model based on Turing patterns, enabling multi-cellular robots to self-organize their cell phenotypes in response to environmental stimuli. The model leverages reaction-diffusion dynamics to capture key cellular plasticity phenomena observed in muscle cells, neurons, and stem cells. Analytical analysis explores equilibrium points, stability, and conditions for emergent Turing patterns, while simulations examine parametric influences on system behavior. Physical experiments with the Loopy platform demonstrate that its cells dynamically self-organize mechanical properties in response to behavioral and environmental demands. This response enables Loopy to achieve similar performance to empirically optimized static parameters in obstacle-free environments and outperform the static configuration in an environment with limited space. This work advances morphogenetic robotics, presenting a scalable framework for decentralized, dynamic adaptation in unmodeled environments.more » « less
-
The organization of cells within tissues plays a vital role in various biological processes, including development and morphogenesis. As a result, understanding how cells self-organize in tissues has been an active area of research. In our study, we explore a mechanistic model of cellular organization that represents cells as force dipoles that interact with each other via the tissue, which we model as an elastic medium. By conducting numerical simulations using this model, we are able to observe organizational features that are consistent with those obtained from vertex model simulations. This approach provides valuable insights into the underlying mechanisms that govern cellular organization within tissues, which can help us better understand the processes involved in development and disease.more » « less
-
null (Ed.)Nuclear mechanics is emerging as a key component of stem cell function and differentiation. While changes in nuclear structure can be visually imaged with confocal microscopy, mechanical characterization of the nucleus and its sub-cellular components require specialized testing equipment. A computational model permitting cell-specific mechanical information directly from confocal and atomic force microscopy of cell nuclei would be of great value. Here, we developed a computational framework for generating finite element models of isolated cell nuclei from multiple confocal microscopy scans and simple atomic force microscopy (AFM) tests. Confocal imaging stacks of isolated mesenchymal stem cells were converted into finite element models and siRNA-mediated Lamin A/C depletion isolated chromatin and Lamin A/C structures. Using AFM-measured experimental stiffness values, a set of conversion factors were determined for both chromatin and Lamin A/C to map the voxel intensity of the original images to the element stiffness, allowing the prediction of nuclear stiffness in an additional set of other nuclei. The developed computational framework will identify the contribution of a multitude of sub-nuclear structures and predict global nuclear stiffness of multiple nuclei based on simple nuclear isolation protocols, confocal images and AFM tests.more » « less
An official website of the United States government
