Multicellular organisms consist of cells of many different types that are established during development. Each type of cell is characterized by the unique combination of expressed gene products as a result of spatiotemporal gene regulation. Currently, a fundamental challenge in regulatory biology is to elucidate the gene expression controls that generate the complex body plans during development. Recent advances in high-throughput biotechnologies have generated spatiotemporal expression patterns for thousands of genes in the model organism fruit fly Drosophila melanogaster. Existing qualitative methods enhanced by a quantitative analysis based on computational tools we present in this paper would provide promising ways for addressing key scientific questions.
Results
We develop a set of computational methods and open source tools for identifying co-expressed embryonic domains and the associated genes simultaneously. To map the expression patterns of many genes into the same coordinate space and account for the embryonic shape variations, we develop a mesh generation method to deform a meshed generic ellipse to each individual embryo. We then develop a co-clustering formulation to cluster the genes and the mesh elements, thereby identifying co-expressed embryonic domains and the associated genes simultaneously. Experimental results indicate that the gene and mesh co-clusters can be correlated to key developmental events during the stages of embryogenesis we study. The open source software tool has been made available at http://compbio.cs.odu.edu/fly/.
Conclusions
Our mesh generation and machine learning methods and tools improve upon the flexibility, ease-of-use and accuracy of existing methods.
Learning Sparse Representations for Fruit-Fly Gene Expression Pattern Image Annotation and Retrieval
Fruit fly embryogenesis is one of the best understood animal development systems, and the spatiotemporal gene expression dynamics in this process are captured by digital images. Analysis of these high-throughput images will provide novel insights into the functions, interactions, and networks of animal genes governing development. To facilitate comparative analysis, web-based interfaces have been developed to conduct image retrieval based on body part keywords and images. Currently, the keyword annotation of spatiotemporal gene expression patterns is conducted manually. However, this manual practice does not scale with the continuously expanding collection of images. In addition, existing image retrieval systems based on the expression patterns may be made more accurate using keywords.
Results
In this article, we adapt advanced data mining and computer vision techniques to address the key challenges in annotating and retrieving fruit fly gene expression pattern images. To boost the performance of image annotation and retrieval, we propose representations integrating spatial information and sparse features, overcoming the limitations of prior schemes.
Conclusions
We perform systematic experimental studies to evaluate the proposed schemes in comparison with current methods. Experimental results indicate that the integration of spatial information and sparse features lead to consistent performance improvement in image annotation, while for the task of retrieval, sparse features alone yields better results.
Drosophila melanogaster has been established as a model organism for investigating the developmental gene interactions. The spatio-temporal gene expression patterns of Drosophila melanogaster can be visualized by in situ hybridization and documented as digital images. Automated and efficient tools for analyzing these expression images will provide biological insights into the gene functions, interactions, and networks. To facilitate pattern recognition and comparison, many web-based resources have been created to conduct comparative analysis based on the body part keywords and the associated images. With the fast accumulation of images from high-throughput techniques, manual inspection of images will impose a serious impediment on the pace of biological discovery. It is thus imperative to design an automated system for efficient image annotation and comparison.
Results
We present a computational framework to perform anatomical keywords annotation for Drosophila gene expression images. The spatial sparse coding approach is used to represent local patches of images in comparison with the well-known bag-of-words (BoW) method. Three pooling functions including max pooling, average pooling and Sqrt (square root of mean squared statistics) pooling are employed to transform the sparse codes to image features. Based on the constructed features, we develop both an image-level scheme and a group-level scheme to tackle the key challenges in annotating Drosophila gene expression pattern images automatically. To deal with the imbalanced data distribution inherent in image annotation tasks, the undersampling method is applied together with majority vote. Results on Drosophila embryonic expression pattern images verify the efficacy of our approach.
Conclusion
In our experiment, the three pooling functions perform comparably well in feature dimension reduction. The undersampling with majority vote is shown to be effective in tackling the problem of imbalanced data. Moreover, combining sparse coding and image-level scheme leads to consistent performance improvement in keywords annotation.
In a COVID-19 world, student engagement has suffered drastically as organizations and universities shifted to an online format. Yet, there is still an opportunity and a space for digital content creation to bridge the gap in a virtual and hybrid university lifestyle. This project looks at how student groups can still engage students at ASU Tempe through digital content creation and which tools to use to enter the space.
During the global COVID-19 pandemic in 2020, many universities shifted their focus to hosting classes and events online for their student population in order to keep them engaged. The present study investigated whether an association exists between student engagement (an individual’s engagement with class and campus) and resilience. A single-shot survey was administered to 200 participants currently enrolled as undergraduate students at Arizona State University. A multiple regression analysis and Pearson correlations were calculated. A moderate, significant correlation was found between student engagement (total score) and resilience. A significant correlation was found between cognitive engagement (student’s approach and understanding of his learning) and resilience and between valuing and resilience. Contrary to expectations, participation was not associated with resilience. Potential explanations for these results were explored and practical applications for the university were discussed.
The mental health of ASU students has been negatively affected by the pandemic. Our research looks to prove that COVID-19 has caused an increase in stress levels while uncovering other relationships to stress. We obtained our data by conducting a survey through Google Forms that was exclusively accessible to ASU students. Stress levels were measured with the use of the Perceived Stress Scale (PSS). We find that the stress of ASU students from before the pandemic to during rises from 15 to 22 points, a 50% increase (n = 228). We discovered that women are more stressed than men before and during the pandemic. We also discovered that there is no difference between stresses among different races. We notice that there is a parabolic relationship between enrollment time and stress levels with the peak occurring during semesters 2-6. We also conclude that students who attended more than 5 events during the pandemic had lower stress scores, and those who had their videos on for at least 3 events had lower stress scores. Furthermore, students who utilized campus resources to manage their stress had higher stress levels than those who did not.
The purpose of this creative project was to create a stereo sound system in a unique medium. As a team, we decided to integrate a Tesla Coil with a bluetooth audio source. These high frequency, high voltage systems can be configured to emit their electrical discharge in a manner that resembles playing tunes. Originally the idea was to split the audio into left and right, then to further segregate the signals to have a treble, mid, and base emitter for each side. Due to time, budget, and scope constraints, we decided to complete the project with only two coils.<br/><br/>For this project, the team decided to use a solid-state coil kit. This kit was purchased from OneTelsa and would help ensure everyone’s safety and the project’s success. The team developed our own interrupting or driving circuit through reverse-engineering the interrupter provided by oneTesla and discussing with other engineers. The custom interpreter was controlled by the PSoC5 LP and communicated with an audio source through the DFRobot Bluetooth module. Utilizing the left and right audio signals it can drive the two Tesla Coils in stereo to play the music.
An X class solar flare has the potential to remove our satellites from orbit, permanently deactivate our main forms of communication and bring humanity into a technology-free age. By using Geant4, it is possible to simulate several layers of the Earth's atmosphere and send a simulated solar flare and coronal mass ejection. This thesis will show the interaction of photons and protons of various energies with several kilometers of atmosphere.
This thesis looks at how Latinx communities in Wyoming, despite recognizing the impossibility of overcoming the traditional conservative autocracy, still utilize their identity as a political response to unify Latinx communities throughout the state. The project draws from oral histories conducted with Latinx/Chicanx community members in Wyoming, including professors, legislators, and everyday citizens.
This thesis worked towards the development of a parameterized 3D model off a cover that could go over any specific prosthesis depending on the parameters that had been entered. It also focused on gathering user inputs, which was done with the aid of the Amputee Coalition, that could be used to create an aesthetic design on this cover. The Amputee Coalition helped to recruit participants through its website and social media platforms. Finally, multiple methods of creating a design were developed to increase the amount of customization that a user could have for their cover.