#SNAPGENE UCSF SOFTWARE#
#SNAPGENE UCSF CODE#
#SNAPGENE UCSF SIMULATOR#

We thank P Rothemund and N Case for helpful testing and feedback. We thank J Brown for assistance with the app icon and introductory video, and P Nafisi for running several gels that we used to calibrate the simulation model. We hope our work inspires others to build interactive simulations for additional aspects of scientific research so that all of these efforts can be synergistic, and so Gelbox becomes more useful and accurate with further iterations. Many of the limitations of Gelbox could be addressed with further development, including more experimental validation and integration with other simulation tools. Gelbox may help learners establish some basic skills to interpret gel data and to troubleshoot problematic experimental conditions.

#SNAPGENE UCSF SIMULATOR#

In summary, we have created a dynamic, interactive gel electrophoresis simulator that relies on multiple linked representations of the system to help young or new researchers achieve more accurate and useful results when using gel electrophoresis. However, Gelbox might be used as a visualization tool for other physically based simulations if they were adapted to output our text-based file format. We did not systematically validate all parameters with experimental data, thus the predicted band mobility and behavior may not match real-world results.įourth, our models do not have any physical basis: that is, we do not account for kinetic or thermodynamic properties of the DNA molecules. Third, the simulation could benefit from further calibration. We spent most of our effort on creating the various representations and thus didn't capture the great variation in possible parameters. Second, the simulation model is narrow in scope compared to real agarose gels. It does not yet support RNA or protein gels. First, Gelbox only models agarose gels and DNA fragments ranging in size from 100 to 14000 base pairs. Beheshti 13, but ultimately developed our own model directly from gel-image data for a 1 kb ladder.

We explored models from Van Winkle, Beheshti, and Rill 12, and the dissertation of A.

#SNAPGENE UCSF CODE#

To build the simulation model, we aimed to write code that would accurately convert the length of a DNA fragment to band mobility in the gel. To our knowledge, Gelbox is the only gel simulation tool that attempts to capture and explain how gels can produce flawed information, particularly due to user error, or fail completely. Molecules can vary in size, concentration, shape, or degree of aggregation and degradation. In contrast, Gelbox provides multiple dynamic representations of a gel under a wide range of conditions.

#SNAPGENE UCSF SOFTWARE#

These tools are typically included with computer-aided design software for gene editing or DNA cloning. While other gel simulators do exist, they provide only a single static graphical representation of predicted DNA fragment mobility under ideal experimental conditions 8–11.

Fortunately, computer simulation can reduce the time to fractions of a second between modifying a gel parameter and observing the effects, making cause-and-effect relationships more visible and explicit. Several hours can pass between making a mistake in preparing a gel and observing the effects of that mistake.

While working with real gels provides valuable hands-on experience, the learning process is constrained by a slow feedback loop. We built Gelbox to be an interactive tool that could complement the ad hoc learning methods routinely used in laboratory settings. We also drew inspiration from Parable of the Polygons by Vi Hart and Nicky Case 4, and many other works 5–7.ĭrag image (file extensions: png, jpg, gif) file onto the window. We have been greatly influenced by Bret Victor's work, especially Up and Down the Ladder of Abstraction 3. This project builds on concepts from Earth: A Primer, an interactive geology science book by Gingold 2. We wanted to explore the potential pitfalls of using gels by illustrating that, although it’s easy to make mistakes when using this method, these mistakes are also predictable and can mostly be avoided with some training and forethought. We created Gelbox, a dynamic “scientific sandbox” that can aid in visualizing various ways that gel bands, sample molecules, and the gel itself, interact. We believe interactive simulation and visualization tools can help. Challenges in preparing and using gels can frustrate budding scientists, interfere with scientific reproducibility, and impede overall research progress. Even when gels are run successfully, interpreting data can be tricky because the relationships between 'band' patterns and the molecules in a sample are abstract and often ambiguous.

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