Graphics and Human Computer Interfaces Commons^™

Du Undergraduate Showcase Abstracts: Research, Scholarship, And Creative Works, Sophia Wismar, Henry Staats, Allison Metzler, Chloe Puckett, Rachel Levine, Christa Kilpatrick, Scott Wolf, Joe Walsh, Grace Doolittle, John Engebreston, Zoe Lopez, Christopher Aaby, Audrey Duff, Timothy Sisk, Katelyn Lamberton, Angela Narayan, Gilkah Argueta, Habiba Samir, Girena Tesfazghi, Genet Kenore, Sinit Tesfamariam, Effley Brooks, Abi Newell, Megan Doherty, Natalie Baer, Lexi Blood, Talya Riciputi, Jessica Jimenez, Devin Hernandez, Lynn Clark, Taj Kumar, Sunil Kumar, Allen Rutman, Mira Pronobis, Tess Carson, Anna Sher, Frankie Stroud, Tamra Pearson D'Estree, Alyssa Wilson, Emily Melnick, Jenalee Doom, Yihang Gao, Gwendolyn Geiger, Noah Gettle, Scott Nichols, Clare Ayoub, Cara Dienno, Sunny Walker, Zoe Hansen, Maya Wheeler, Addison Rice, Patrick Martin, Sanjana Acharya, Daniel Mcintosh, Amanda Mckellips, Calli Cain, Justin Blake, Peter Sokol-Hessner, Natalie Miller, Max Weisbuch, Sophia Dellota, John Macikas, Charlotte Snow, Mark Siemens, Zoe Lynch, Alex Huffman, Prachi Shah, Jason Roney, Halcyon Levi, Nicole Herzog, Andrea Koly, Daniel Linseman, Annie London, Xi Yang, Avery Zwisler, Jane Smith, Chaz Contag, Michael Kerwin, Lucy Rand, Grace Schroeder, Michelle Rozenman, Nissa Tapper, Guiming Zhang, Mateo Mazariego-Halpern, Keith Meyer, Julie Do, Dakota Park-Ozee, Travis Herink, Kara Neu, Jonathan Plomin, Eve-Odine Duchaufour, Debbie Gale Mitchell, Tennyson Anderson-Stricklin, Lily Treitz, Samantha Rosenberger, Sierra Griffith, Finley Joseph, Daniel Sampson, Emmy Davis, Skyler Kasnoff, Evon Lopez, Vivian Nguyen, Cassy Young, Franklin Sellner, Martin Tobon, Ila Graham, Zach Billings, Holden Hedit, Decatur Boland, Paul Kosempel, Cory Chandler, Jay Mahoney, Sam Dragan, Susan Dagget, Yarrow Ator, Heidi Vuletich, Owen Weber, Andrew Kloeppel, Petersen Gray, Mandi Schaeffer-Fry, Razleen Bassra, Bryanna Rodriguez, Christina Blue, Taubie Sanders, Rachel Epstein, Luke Milburn, Camryn Evans, Ezra Martinez, Mary Westwood, Gabri Notov, Robin Tinghitella, Lilou Cabrol, Eli Barbour, Juliet Mendik, Selma Myers, Zac Wise, Noah Fahlin, Michelle Knowles, Abigail Hopper, Michael Greenberger, Romi Laclair, Sarah Watamura, Sabrina Efroymson, Casey Barker, Sydney Seltzer, Bryn Yehle, Jennifer Hoffman, Sara Garcia, Ryuka Nagamine, Trevor Briggs, Remy Le Boeuf, Elena Krone, Eileen Farrell, Regan O'Rourke, Elena Roel, Greg Mortimer, Ali Ayoub, Stefani Langehennig, Caitlin Turk, Logan Scmid, Stefan Chavez-Norgaard, Karen Kim, Tatiana Peccedi, Courtney Cassidy, John Sebesta, Rhianna Lewis, Janice Bening-Lacek, Vivian Lawless, Mckenna Hanson, Jeffrey Amidon, Riya Joshi, Ram Ambre, Brady Worrell, Perrin Schneider, Ali Azadani, Brooke Agulnek, Lyndsie Salvagio, Elise Siemanowki, Yan Qin, Andre Allen, Melodie Nguyen, Megan Livengood, Abby Reams, Saffron Hartreeve, Bri Wylie, Sarah Brookman, Mariah Loiacono, Green Russo, Abhia Lodhi, Gabrielle Welsh, Nika Spehar, Shahked Levin, Evrim Baykal, Kimberly Chiew, Jocelyn Torres, Kailey Hicks, Mykaela Tanino-Springsteen, Audrey Bellows, Akam Chahal, Madeline Tepper, Shannon Murphy, Alexa Fonseca, Deborah Han, Cassandra Perez, Oluwatoyin Alaba, Julia Roncoroni, Vy Nguyen, Nana Burn, Sarah Sasse, Rubin Tuder, Anthony Gerber, Nancy Lorenzon, Christine Vohwinkel, Camryn Gunter, Tristan Weber, Sam Rommel, Brian Michel, Muskan Fatima, Alannah Oleson, Kira Frey, Edward Garrido, Beckett Morris, Kerstin Haring, Drew Middleton, Abigail Walpert, Liam Dee, Gabby Ishaw, Cole Carnes, Maddie Weiser, Claire Fox, Valeriia Vlasenko, Kateri Mcrae, Riley Smith, Abigail Templin, Kushani Rajapaksha

DU Undergraduate Research Journal Archive

Abstracts from the DU Undergraduate Research Showcase.

Cellscout: Visual Analytics For Mining Biomarkers In Cell State Discovery, Rui Sheng, Zelin Zang, Jiachen Wang, Yan Luo, Zixin Chen, Yan Zhou, Shaolun Ruan, Huamin Qu

Research Collection School Of Computing and Information Systems

Cell state discovery is crucial for understanding biological systems and enhancing medical outcomes. A key aspect of this process is identifying distinct biomarkers that define specific cell states. However, difficulties arise from the co-discovery process of cell states and biomarkers: biologists often use dimensionality reduction to visualize cells in a two-dimensional space. Then they usually interpret visually clustered cells as distinct states, from which they seek to identify unique biomarkers. However, this assumption is often this assumption often fails to hold due to internal inconsistencies in a cluster, making the process trial-and-error and highly uncertain. Therefore, biologists urgently need effective …

Trustworthy Multimodal Ai For Medical Imaging: Enhancing Diagnosis, Reasoning, And Human-Agent Interaction In Extended Reality, Jai Prakash Veerla

Computer Science and Engineering Dissertations

The transition from traditional microscopy to digital pathology has digitized diagnostic data, yet clinical workflows remain constrained by two-dimensional screens and passive, opaque analysis tools that fail to capture the spatial complexity of biological systems. While Foundation Models now promise to reason across histology and genomics, a critical disconnect persists between the richness of this data and the limited cognitive bandwidth of clinicians, who currently lack the immersive interfaces and trustworthy agents necessary to utilize it effectively. This dissertation presents a unified framework for "Embodied Agentic AI," establishing a pipeline that augments physician capabilities through immersive visualization, robust security, and …

Wearable Sensor-Based Phase Segmentation Analysis Of Front Crawl Swimming: A Scoping Review, Jonathan Simoes, Samuel Aylward, Daniel Hamze, Daniel James Goble, Daniel M. Russell, Joshua Haworth

Exercise Science Faculty Publications

Front crawl swimming stroke phase segmentation has historically relied on video analysis, but the development of wearable sensor technology has created new opportunities for automated phase segmentation. This scoping review mapped the available evidence on wearable sensor-based stroke phase segmentation methods in front crawl swimming, following PRISMA-ScR guidelines. A systematic search of SPORTDiscus, Web of Science, and IEEE Xplore conducted from January to June 2026, identified 15 eligible peer-reviewed studies published between 2000 and 2024. The review revealed an emerging field of research that has converged methodologically around inertial measurement units (IMUs) and the Chollet phase segmentation framework while remaining …

Eeg And Imu Gait Signal Processing: A Comparative Assessment Of The "Reza" Exponential Filter And Classic Filters, Reza Pousti, Daniel M. Russell, Derek C. Monroe, Christopher K. Rhea

Rehabilitation Sciences Faculty Publications

Noise degrades both EEG and gait signals, and classical IIR filters (Butterworth, Chebyshev, elliptic) involve trade-offs between passband flatness, ripple, and roll-off. This study compared a novel exponential "Reza" filter with these designs for neural and locomotor data. We analyzed an open-source mobile brain-body imaging dataset with EEG and gait data from 49 healthy adults (EEG: 256-channel, 512 Hz; IMUs: six APDM Opals, 128 Hz). EEG channels were grand-averaged and band-pass filtered at 0.5-50 Hz, while IMU axes were averaged and band-pass filtered at 0.5-5 Hz. The outcomes were signal-to-noise ratio SNR (dB) and band-integrated Welch PSD (EEG:0.5-50 Hz; IMU:0.5-5 …

Classification Of Human Trust In Ai Using Brain Activity Data, Danushka Bandara, Ruhuan Liao, Fatima Chowdhury, Leslie Abbott

Northeast Journal of Complex Systems (NEJCS)

Trust plays a crucial role in human-computer interaction, particularly in scenarios involving artificial intelligence (AI) systems. This study explores the feasibility of using functional near-infrared spectroscopy (fNIRS) data to classify trust levels in human-AI interaction scenarios. A total of 18 participants completed an image classification task with an AI team member while their hemodynamic responses were recorded using fNIRS. Preprocessing of fNIRS data involved motion artifact removal, filtering, and normalization. Exploratory analysis identified significant associations between hemodynamic responses in the prefrontal cortex and trust levels. An across-subject binary trust classification model was developed using machine learning techniques, achieving an F1 …

A System And Method For Measuring Spatially Varying Surface Appearances With A Study Of Feathers, Jessica Baron-Lis

All Dissertations

Real-world materials, particularly biological structures such as feathers exhibit complex appearances that vary spatially across their surfaces. The field of computer graphics provides a means of understanding such surfaces through material modeling which uses both analytical models and data acquired from light-surface interactions. There are many efforts within the past decade in measuring materials for graphics, but common limitations in these works include not accounting for spatially varying properties and reliance on neural networks and synthetic datasets.

Feathers from modern birds present diverse appearances due to how light interacts with their unique hierarchical microstructures. Variations in those structures lead to …

Next-Generation Crop Monitoring Technologies: Case Studies About Edge Image Processing For Crop Monitoring And Soil Water Property Modeling Via Above-Ground Sensors, Nipuna Chamara

Dissertations and Doctoral Documents, University of Nebraska-Lincoln, 2023–

Artificial Intelligence (AI) has advanced rapidly in the past two decades. Internet of Things (IoT) technology has advanced rapidly during the last decade. Merging these two technologies has immense potential in several industries, including agriculture.

We have identified several research gaps in utilizing IoT technology in agriculture. One problem was the digital divide between rural, unconnected, or limited connected areas and urban areas for utilizing images for decision-making, which has advanced with the growth of AI. Another area for improvement was the farmers' demotivation to use in-situ soil moisture sensors for irrigation decision-making due to inherited installation difficulties. As Nebraska …

Foodmask: Real-Time Food Instance Counting, Segmentation And Recognition, Huu-Thanh Nguyen, Yu Cao, Chong-Wah Ngo, Wing-Kwong Chan

Research Collection School Of Computing and Information Systems

Food computing has long been studied and deployed to several applications. Understanding a food image at the instance level, including recognition, counting and segmentation, is essential to quantifying nutrition and calorie consumption. Nevertheless, existing techniques are limited to either category-specific instance detection, which does not reflect precisely the instance size at the pixel level, or category-agnostic instance segmentation, which is insufficient for dish recognition. This paper presents a compact and fast multi-task network, namely FoodMask, for clustering-based food instance counting, segmentation and recognition. The network learns a semantic space simultaneously encoding food category distribution and instance height at pixel basis. …

Reducing Food Scarcity: The Benefits Of Urban Farming, S.A. Claudell, Emilio Mejia

Journal of Nonprofit Innovation

Urban farming can enhance the lives of communities and help reduce food scarcity. This paper presents a conceptual prototype of an efficient urban farming community that can be scaled for a single apartment building or an entire community across all global geoeconomics regions, including densely populated cities and rural, developing towns and communities. When deployed in coordination with smart crop choices, local farm support, and efficient transportation then the result isn’t just sustainability, but also increasing fresh produce accessibility, optimizing nutritional value, eliminating the use of ‘forever chemicals’, reducing transportation costs, and fostering global environmental benefits.

Imagine Doris, who is …

Deep Learning Image Analysis To Isolate And Characterize Different Stages Of S-Phase In Human Cells, Kevin A. Boyd, Rudranil Mitra, John Santerre, Christopher L. Sansam

SMU Data Science Review

Abstract. This research used deep learning for image analysis by isolating and characterizing distinct DNA replication patterns in human cells. By leveraging high-resolution microscopy images of multiple cells stained with 5-Ethynyl-2′-deoxyuridine (EdU), a replication marker, this analysis utilized Convolutional Neural Networks (CNNs) to perform image segmentation and to provide robust and reliable classification results. First multiple cells in a field of focus were identified using a pretrained CNN called Cellpose. After identifying the location of each cell in the image a python script was created to crop out each cell into individual .tif files. After careful annotation, a CNN was …

Contrastive Learning For Unsupervised Auditory Texture Models, Christina Trexler

Computer Science and Computer Engineering Undergraduate Honors Theses

Sounds with a high level of stationarity, also known as sound textures, have perceptually relevant features which can be captured by stimulus-computable models. This makes texture-like sounds, such as those made by rain, wind, and fire, an appealing test case for understanding the underlying mechanisms of auditory recognition. Previous auditory texture models typically measured statistics from auditory filter bank representations, and the statistics they used were somewhat ad-hoc, hand-engineered through a process of trial and error. Here, we investigate whether a better auditory texture representation can be obtained via contrastive learning, taking advantage of the stationarity of auditory textures to …

Sound In Color, Amber Rhodes

Honors Scholars Collaborative Projects

“Sound in Color” is an interactive audio-visual experience designed to explore the relationship between sound, color, and emotions. Taking place on the Massey Concert Hall stage, the project is inspired by synesthesia and incorporates research on color psychology. Participants are invited to select an emotion and color. As the user hums into a microphone, they hear their emotions expressed through sound in their headphones and watch as the lights on stage respond to their vocal cues.

3d Printing Of Human Microbiome Constituents To Understand Spatial Relationships And Shape Parameters In Bacteriology, Jacques Izard, Teklu Kuru Gerbaba, Shara R. P. Yumul

Department of Food Science and Technology: Faculty Publications

Effective laboratory and classroom demonstration of microbiome size and shape, diversity, and ecological relationships is hampered by a lack of high-resolution, easy-to-use, readily accessible physical or digital models for use in teaching. Three-dimensional (3D) representations are, overall, more effective in communicating visuospatial information, allowing for a better understanding of concepts not directly observable with the unaided eye. Published morphology descriptions and microscopy images were used as the basis for designing 3D digital models, scaled at 20,000×, using computer-aided design software (CAD) and generating printed models of bacteria on mass-market 3D printers. Sixteen models are presented, including rod-shaped, spiral, flask-like, vibroid, …

Soda: An Open-Source Library For Visualizing Biological Sequence Annotation, Jack W. Roddy, Travis J. Wheeler

Graduate Student Theses, Dissertations, & Professional Papers

Genome annotation is the process of identifying and labeling known genetic sequences or features within a genome. Across the various subfields within modern molecular biology, there is a common need for the visualization of such annotations. Genomic data is often visualized on web browser platforms, providing users with easy access to visualization tools without the need for installing any software or, in many cases, underlying datasets. While there exists a broad range of web-based visualization tools, there is, to my knowledge, no lightweight, modern library tailored towards the visualization of genomic data. Instead, developers charged with the task of producing …

Snow-Albedo Feedback In Northern Alaska: How Vegetation Influences Snowmelt, Lucas C. Reckhaus

Theses and Dissertations

This paper investigates how the snow-albedo feedback mechanism of the arctic is changing in response to rising climate temperatures. Specifically, the interplay of vegetation and snowmelt, and how these two variables can be correlated. This has the potential to refine climate modelling of the spring transition season. Research was conducted at the ecoregion scale in northern Alaska from 2000 to 2020. Each ecoregion is defined by distinct topographic and ecological conditions, allowing for meaningful contrast between the patterns of spring albedo transition across surface conditions and vegetation types. The five most northerly ecoregions of Alaska are chosen as they encompass …

"Flagella Base Model" And "Flagellin Monomer", Brandon Lasalle, Rebecca Roston

3-D Printed Model Structural Files

"Flagella Base Model" and "Flagellin monomer"

Description: This is a teaching model of the proteins that make a bacterial flagella. All models are depicted in space-fill. The Flagellin monomer and the Flagella base can slot together to show protein quaternary structure and filamentous protein assembly.

Printable models are already uploaded to Shapeways.com in the MacroMolecules shop under the names "Flagella Base Model" and "Flagellin monomer".

This model has been printed successfully using these parameters on Shapeways’ laser sintering printer in the following material: Processed Versatile Plastic (Strong & Flexible Plastic).

Model designer: Brandon Lasalle Authors: Brandon Lasalle and Rebecca Roston …

Amino Acid Pop-Set: Model File Name: Amino-Acid-Wgrp-Pop_Sc3.Stl, Michelle Howell, Rebecca Roston

3-D Printed Model Structural Files

This is a teaching model for protein primary structure. It consists of four amino acids (tryptophan, proline, arginine, and glycine) depicted in stick and space-fill representations, five peptide bonds depicted in space-fill, and an N-terminus and a C-terminus depicted in space-fill. It is designed so that students can make various peptides to explore the amount of space of the electron clouds of the amino acids and bonds, and explore the psi and phi angles for the peptides. The printable model is already uploaded to Shapeways.com in the MacroMolecules shop under the name “Amino acid pop-set”. This model has …

Lipoprotein Signal Peptidase Ii: Model File Name: 5dir-Lipoii-Reps_Sc1-5.Stl, Michelle Howell, Rebecca Roston

3-D Printed Model Structural Files

This is a teaching model of lipoprotein signal peptidase II (PDB: 5DIR). It is designed with different regions of the protein depicted in space-filling, ribbon, stick, and backbone-only representations to explore protein secondary structure and illustrate how much space the protein takes up. The printable model is already uploaded to Shapeways.com in the MacroMolecules shop under the name “Lipoprotein signal peptidase II” and is intended to accompany the “Crambin”, “Cytochrome c” and “3 water molecules” models. This model has been printed successfully using these parameters on Shapeways’ laser sintering printer in …

3 Water Molecules: Model File Name: 3hoh-Final.Stl, Michelle Howell, Rebecca Roston

3-D Printed Model Structural Files

This is a teaching model of 3 water molecules depicted in space-fill. It is designed to the same scale as the “Lipoprotein signal peptidase II”, “Crambin”, and “Cytochrome c” models to illustrate the amount of space taken up by proteins. The printable model is already uploaded to Shapeways.com in the MacroMolecules shop under the name “3 water molecules” and is intended to accompany the “Lipoprotein signal peptidase II”, “Crambin”, and “Cytochrome c” models. This model has been printed successfully using these parameters on Shapeways’ laser sintering …

Crambin: Model File Name: 2fd7-Crambin-Stick_Sc1-5.Stl, Michelle Howell, Rebecca Roston

3-D Printed Model Structural Files

This is a teaching model of cytochrome c (PDB: 2FD7). It is designed in a stick representation to explore protein secondary structure and how much space the protein takes up. The printable model is already uploaded to Shapeways.com in the MacroMolecules shop under the name “Crambin” and is intended to accompany the “Lipoprotein signal peptidase II”, “Cytochrome c”, and “3 water molecules” models. This model has been printed successfully using these parameters on Shapeways’ laser sintering printer in the following material: Processed Versatile Plastic (Strong & Flexible Plastic).

Cytochrome C: Model File Name: 1b7v-Cytc-Stick_Sc1-5.Stl, Michelle Howell, Rebecca Roston

3-D Printed Model Structural Files

This is a teaching model of cytochrome c (PDB: 1B7V). It is designed in a stick representation to explore protein secondary structure and how much space the protein takes up. The printable model is already uploaded to Shapeways.com in the MacroMolecules shop under the name “Cytochrome c” and is intended to accompany the “Lipoprotein signal peptidase II”, “Crambin”, and “3 water molecules” models. This model has been printed successfully using these parameters on Shapeways’ laser sintering printer in the following material: Processed Versatile Plastic (Strong & Flexible Plastic).

Human Hexokinase I - Allosteric Regulation: Model File Name: 1dgk-Editb22-Allostery_Sc06.Stl, Michelle Howell, Rebecca Roston

3-D Printed Model Structural Files

This is a teaching model of human Hexokinase I in a surface representation with small molecules ADP and G6P included (PDB: 1DGK). It is designed to be hollow with a lever to mimic allosteric regulation. The printable model is already uploaded to Shapeways.com in the MacroMolecules shop under the name “Human Hexokinase I - Allosteric regulation model”. This model has been printed successfully using these parameters on Shapeways’ laser sintering printer in the following material: Processed Versatile Plastic (Strong & Flexible Plastic).

Model File Name: 1ehz-Trna(Thick).Stl, Michelle Howell, Karin Van Dijk, Rebecca Roston

3-D Printed Model Structural Files

Model file name: 1ehz-tRNA(thick).stl

Authors: Michelle E Howell, Karin van Dijk, Rebecca L Roston

This is a teaching model of Phe-tRNA in a thick stick-representation (PDB: 1ehz), designed to go with a teaching module comparing DNA and RNA basic structures and functions. The printable model is already uploaded to Shapeways.com under the name “tRNA-Phe small”. This model has been printed successfully using these parameters on Shapeways’ laser sintering printer in the following materials: Strong & Flexible Plastic and Elasto Plastic.

Model File Name: 1lmb-Dbd-Tfmono.Stl, Michelle Howell, Karin V. Van Dijk, Rebecca Roston

3-D Printed Model Structural Files

Model file name: 1lmb-DBD-TFmono.stl

Authors: Michelle E Howell, Karin van Dijk, Rebecca L Roston

This is a teaching model of the DNA binding domain of a Lambda repressor transcription factor monomer that accompanies the full color DNA helix (PDB: 1lmb). It is in a cartoon ribbon representation with key amino acid residues in stick representation to highlight interactions with the DNA. This model is designed to accompany a teaching module illustrating transcription factor-DNA binding. The printable model is already uploaded to Shapeways.com in the MacroMolecules shop under the name “Lambda TF DBD”. This model has been printed …

Model File Name: 1ehz-Trna(Thin-Big).X3d, Michelle Howell, Karin V. Van Dijk, Rebecca Roston

3-D Printed Model Structural Files

Model file name: 1ehz-tRNA(thin-big).x3d

Authors: Michelle E Howell, Karin van Dijk, Rebecca L Roston

This is a teaching model of Phe-tRNA in a large, but thin stick-representation (PDB: 1ehz), designed to go with a teaching module comparing DNA and RNA basic structures and functions. The printable model is already uploaded to Shapeways.com in the MacroMolecules shop under the name “Full color Phe-tRNA (1ehz)”. This model has been printed successfully using these parameters on Shapeways’ laser sintering printer in the following material: Strong & Flexible Plastic.

Model File Name: 1lmb-Dnalong_Fordimer-Test6b.Stl, Michelle Howell, Karin V. Van Dijk, Rebecca Roston

3-D Printed Model Structural Files

Model file name: 1lmb-DNAlong_fordimer-test6b.stl

Authors: Michelle E Howell, Karin van Dijk, Rebecca L Roston

This is a teaching model of the 19-bp segment of DNA to which Lambda repressor transcription factor interacts (PDB: 1lmb). It is in a stick representation and has been designed with sites to add magnets to illustrate binding interactions with the transcription factor. Sphere magnets with a 1/8” diameter can be purchased separately from K&J Magnets. The model can interact with the dimer form of the transcription factor. This model is designed to accompany a teaching module illustrating transcription factor-DNA binding. The printable model …

Model File Name: 1lmb-Tfdimer-Mags-Joints-Jnd-Sc1-8-Parts-V4b.Stl, Michelle Howell, Karin V. Van Dijk, Rebecca Roston

3-D Printed Model Structural Files

Model file name: 1lmb-TFdimer-mags-joints-jnd-sc1-8-parts-v4b.stl

Additional files: 1lmb-Lys-Ser-extras-v4b.stl and 1lmb-TFdimer-Leu-v4b.stl

Authors: Michelle E Howell, Karin van Dijk, Rebecca L Roston

This is a teaching model of a ribbon and stick representation of the transcription factor lambda repressor (PDB: 1lmb). Key amino acid residues are in stick representation to illustrate the interactions between the repressor and the DNA to which it binds. Some of these residues have been designed with sites to add magnets to illustrate these interactions. Sphere magnets with a 1/8” diameter can be purchased separately from K&J Magnets. Some of the residues can be interchanged with other …

Model File Name: Dna-294bp-Magnet-Supercoil.Stl, Michelle Howell, Karin V. Van Dijk, Kalika Mahato, Rebecca Roston

3-D Printed Model Structural Files

Model file name: DNA-294bp-magnet-supercoil.stl

Authors: Michelle E Howell, Karin van Dijk, Kalika Mahato, Rebecca L Roston

This is a teaching model of a long, thin representation of double stranded DNA (294 bp). The DNA model has small sites on the ends where the user can glue magnets to mimic circular DNA, and to aid in manipulating the model. Disc magnets with a diameter of 1/8” or 1/10” and thickness of 1/16” can be purchased online from K&J Magnetics and glued into the magnet sites. The model is designed to go with a teaching module on DNA supercoiling. The model can …

Model File Name: Dna-294bp-Handle-Supercoil.Stl, Michelle Howell, Karin V. Van Dijk, Rebecca Roston

3-D Printed Model Structural Files

Model file name: DNA-294bp-handle-supercoil.stl

Authors: Michelle E Howell, Karin van Dijk, Kalika Mahato, Rebecca L Roston

This is a teaching model of a long, thin representation of double stranded DNA (294 bp). The DNA model has small handles on the ends to aid in holding and manipulating the model. The model is designed to go with a teaching module on DNA supercoiling. The model can be accompanied by Nucleosome and H1 histone models to demonstrate DNA packaging in the cell. The printable model is already uploaded to Shapeways.com in the MacroMolecules shop under the name “294bp DNA (handles)”. …