NanoBIO Workshop Abstracts
2022 Spring nanoBIO Education Recitation
The Spring 2022 recitation series is intended for students and educators to examine implementations of nanoBIO and other cloud-based applications (apps) in educational settings. Each session will include presentation of the use of one or more apps along with a discussion of supporting materials such as problem sets. Time will be reserved so that workshop attendees can either offer insights for improvements or discuss how to modify the messaging for a different context. No coding experience is required. Advance materials for preparation as well as follow-up options will be provided for each session.
Feb 3, 2022
This recitation will focus on the use of nanoBIO tools to teach topics associated with materials science and nanoscale engineering courses. The educational use of two tools will be described in detail: Ions in Nanoconfinement and Nanoparticle Shape Lab. These software tools provide an interactive GUI for students to explore and learn the links between material properties and environmental conditions. The Ions in Nanoconfinement tool also features a machine learning surrogate for instantaneous rendering of simulation outputs on the tool canvas. The use of these tools for the in-classroom instruction of topics such as self-assembly, soft material design, interfacial structure, nanoscale forces, and molecular dynamics will be discussed. Sample homework problem sets and supporting documentation will be shared to facilitate the broader use of these tools in courses associated with materials science and nanoengineering curricula.
Feb 17, 2022
Multicellular biological systems—such as competing bacteria, cell colonies, tissues, and cancer—arise from complex mechanical and chemical interactions between individual cells and their (micro)environment. Computational models can be used as “virtual laboratories” to help unravel these complex interactions, and to explore the impact of single-cell behaviors on emergent dynamics. They can also provide an interactive environment for students to rapidly perform virtual experiments to build new intuition. This talk will first introduce concepts of cell-based (agent-based) simulation of complex biological systems that can be used to build such virtual laboratories. It will then show a sample educational module that encourages students to build models of cell-cell interactions in cancer in cloud-hosted tools. We will discuss possible student evaluations, seek community feedback, and discuss possible joint ventures to test and refine simulation-based curriculum for biology and bioengineering class work.
Mar 17, 2022
Pawel Kraj and Trevor Douglas (in collaboration with Vikram Jadhao, Nicholas Brunk) Department of Chemistry, Indiana University.
NanoHUB is a repository for apps developed to simulate complex systems based on input parameters. For example, the NP Assembly lab app simulates the assembly of charged nanoparticles into ordered assemblies through interaction with an oppositely charged linker. The design of the simulation is based on the results of experiments in which negatively charged virus-like particles (VLPs) assemble upon introduction of a cationic dendrimer. In both experiment and simulation, the degree of ordering in the material is modulated by the ionic strength of the medium. The NP Assembly lab app has been used introduce undergraduate students to the principles of self-assembling materials and the methods used to characterize and study these materials. Moreover, the inclusion of the app in undergraduate coursework provides a tangible, hands-on example of the importance of multidisciplinary collaboration to solve scientific problems.
Apr 14, 2022
Cloud-based simulation tools enable easy and accessible use of complicated computational software to students, instructors, and experienced researchers alike. However, developing effective instructional content to include alongside online simulations can pose both conceptual and technological challenges, as users of cloud-based simulation software often represent a wide variety of backgrounds and experience levels. This session will introduce a selection of methods and best practices for the development and deployment of meaningful supporting resources to facilitate the adoption of online simulation tools. An overview of scalable, education-focused documentation strategies will be discussed, along with suggestions for how to use online notebook platforms (Jupyter Notebooks, Google Colab, etc.) to provide enhanced instructional flexibility to cloud-based simulation distribution. Practical examples from current nanoBIO tools on nanoHUB will be provided. Attendees are encouraged to bring thoughts and/or questions about instructional content for their own simulation tools (current or prospective) for discussion.
2021 Winter Interactive nanoBIO Workshop
The Fall '20-Spring '21 Winter Interactive nanoBIO Workshop will walk students and researchers through how to understand a variety of biological problems using simulations based on cloud-based tools on nanoHUB or other easy to use platforms. Each session will include some background material to understand the nature of a problem followed by interactive simulations using straightforward apps that have been developed using extensive, high-quality models. This series will provide an introduction to biological simulation for students wishing to learn about how various problems can be solved, and it will introduce researchers to sections of powerful and multi-scale apps that are extendable to a large number of problems. No coding experience is required. Advance materials for preparation as well as follow-up options will be provided for each session. This series is being offered free of charge but will require registration.
Let a new understanding of nanobiology and how it can be simulated fight off the winter doldrums. This will be an exciting and engaging series.
Go here to view a playlist of all recorded sessions.
Mar 04, 2021
Mechanica is an interactive mesh-free, chemistry and biology simulation environment, with an emphasis towards enabling users to model and simulate complex sub-cellular and cellular biological physics problems. Mechanica is designed first and foremost to enable users to work interactively with simulations – they can build, run and interact with simulation using standard Python in real-time. Our goal in the workshop is to demonstrate to participants how to create and explore interactive models and simulations of active matter.
Feb 25, 2021
Molecular dynamics (MD) simulations accelerated by high-performance computing (HPC) methods are powerful tools for investigating and extracting the microscopic mechanisms characterizing the properties of soft materials such as self-assembled nanoparticles, virus capsids, confined electrolytes, and polymeric fluids. However, despite the employment of optimal parallelization, scientific simulations can often take hours or days to furnish accurate information, and deep learning (DL) has the potential to address this critical need. In this talk, I will discuss ideas on integrating DL methods with HPC-accelerated MD simulations of soft materials in order to enhance their predictive power and advance their applications for research and educational activities. Parallelized MD simulations of self-assembling ions in nanoconfinement are employed to demonstrate our approach. Through this demonstration, I will introduce ``machine learning surrogates'' for MD simulations of soft-matter systems. I will also demonstrate a deployed web application on nanoHUB to realize the advantages associated with the Machine Learning surrogates.
Feb 11, 2021, 2:00 PM - 3:00 PM EST
FURY is a new visualization engine and platform for 3D+ animations involving scientific data. It provides both desktop and web-based versions using an easily accessible Pythonic API. In addition, for experienced programmers it allows to directly access the GPU and program using shading languages such as GLSL. We support integration with physics engines, machine learning libraries and also facilitate deployment by providing our own integrated user interfaces.
Jan 19, 2021, 2:30 PM - 3:30 PM EST
The in-host dynamics of SARS-CoV-2 spread and immune response play out multiple space and time scales. Most in-host to date simulate averaged dynamics that do not resolve spatial detail, heterogeneity, and stochastic cell behaviors, reflecting the scarcity of fine-scaled detail, the engineering complexity of building such a model, and key knowledge gaps in virology and immunology. In this session, we describe a community-driven effort to iteratively develop a multiscale, spatially-resolved open source model of SARS-CoV-2 dynamics and immune response in tissues. After exploring a motivating example (seehttps://nanohub.org/tools/pcisa), we will discuss the iterative progress of the modeling coalition from a simple proof-of-concept model to a fully multiscale model ranging from single-cell molecular signaling to T-cell expansion in the lymph nodes. At the end of the talk, we will briefly demonstrate an freely-available online version the model, available at https://nanohub.org/tools/pc4covid19.
Jan 12, 2021, 2:00 PM - 3:00 PM EST
Biological matter is often compartmentalized by soft membranes that dynamically change their shape in response to chemical and mechanical cues. Deformable nanoparticles that mimic this behavior can be used in nanomedicine applications as drug-delivery carriers that can adapt to evolving physiological conditions. In this talk, I will discuss the modeling and simulation of shape-changing nanoparticles. I will describe the nanoHUB tool “Nanoparticle Shape Lab” that enables simulations of the shape deformation of charged nanoparticles for a broad variety of nanoparticle material properties including nanoparticle surface charge, pattern, elasticity and solution conditions such as salinity. The tool enables users to directly interact with the research findings disseminated in several recent publications and extend the exploration to new regions of the material design space.
Jan 05, 2021, 2:00 PM - 3:00 PM EST
During solid tumor progression, cells gradually acquire the ability to reproduce in ways deleterious to their host, to acquire nutrients and oxygen, to evade the host immune system and eventually, to remodel their environment, invade surrounding tissues and recapitulate their parent tumor organization in metastases. Progression is often regarded as an inevitable sequel of tumor initiation and its genetic and biomolecular bases are widely addressed. Less studied is somatic evolution within solid tumors, which combine rapid heritable mutation and strong selection. Tumor spread is determined by the behaviors of the small fraction of stem-like cells in the tumor, with higher stem-like fractions leading to more aggressive tumors and lower survival. Considering progression from an evolutionary perspective may help explain two apparent paradoxes: 1) Selection is intrinsically undirected, but results in deterministic progression. 2) Chemotherapies, surgery and raditation often result in substantial reduction of tumor mass, but ultimately lead to greater tumor mass and more invasive phenotypes. In this interactive mini-workshop we will use a very simple model of cancer somatic evolution and resource limitation based on one originally proposed by Heiko Enderling (see, e.g. Jan Poleszczuk, Philip Hahnfeldt, Heiko Enderling “Evolution and Phenotypic Selection of Cancer Stem Cells,” PLoS Computational Biology doi.org/10.1371/journal.pcbi.1004025 (2015)). In this game-theoretic model we have a single limiting resource, space to grow; cancer cells which can have either a stem-like (immortal) or somatic (limited number of cell divisions) phenotype, and undirected mutation in the rate of cell growth, fraction of stem cell divisions which give rise to two stem cells rather than a stem cell and a somatic cell (stemness) and the number of times a somatic cell can divide before dying (senescence). In this simple model the fraction of stem-like cells increases in time. We will study how this rate of increase depends on model parameters and show that partially effective treatments can actually result in rapid increase in the fraction of stem-like cells and hence worse outcomes. If time permits, we will also model the situation where the somatic cells protect the stem cells nearby from being killed by a chemotherapeutic agent.
Dec 15, 2020
Multicellular systems—like tissues, microbial communities, and tumors—can exhibit astounding complexity in their dynamics and spatial patterning. And yet the individual cells that make up these systems perform a handful of fundamental behaviors: growth, division, death, adhesion, resistance to deformation, motility, secretion, and sampling the environment. In this talk, we use agent-based simulation models to simulate (1) individual cell behaviors, (2) cell-cell interactions, and (3) cell-environment interactions to show how simple rules can give rise to complex multicellular phenomena. We showcase and explore free, interactive online tools to explore these systems, and we close with pointers on how you can use open source tools to build your own multicellular models.
Dec 08, 2020
We show that one can study several sets of sequences or time-series in terms of an underlying evolution operator which can be learned with a deep learning network. We use the language of geospatial time series as this is a common application type but the series can be any sequence and the sequences can be in any collection (bag) - not just Euclidean space-time -- as we just need sequences labeled in some way and having properties consequent of this label (position in abstract space). This problem has been successfully tackled by deep learning in many ways and in many fields. The most advanced work is probably in Natural Language processing and transportation (ride-hailing). The second case with traffic and the number of people needing rides is a geospatial problem with significant constraints from spatial locality. As in many problems, the data here is typically space-time-stamped events but these can be converted into spatial time series by binning in space and time.
Dec 01, 2020
Host-pathogen interactions of COVID-19 involve biophysical mechanisms and complex dynamics from the subcellular to organismal scales. The outcome and timing of events in individual patients, from recovery to potentially lethal scenarios like sepsis and cytokine storm, emerge from such complex interactions and vary widely by patient and virus. Simulations of tissue-specific effects of primary acute viral infections like COVID-19 are essential for understanding differences in disease outcomes and optimizing therapeutic interventions. This workshop presents an open-source Python- and XML-scripted multiscale modeling and simulation framework of an epithelial tissue infected by a virus, a simplified cellular immune response and viral and immune-induced tissue damage and shows how to use it to model basic patterns of infection dynamics. Adding to and extending the framework by the scientific community through built-in modularity and extensibility is demonstrated with examples of modeling of tissue repair. Attendees will interactively launch and run the framework in the workshop using a web-based deployment, and investigate the effects of manipulating basic mechanisms of viral infection and immune response on emergent outcomes.