Matching Items (686)
Description
Background: Breast cancer is the most frequently diagnosed cancer and the leading cause of cancer deaths in females worldwide, accounting for 23% of all new cancer cases and 14% of all total cancer deaths in 2008. Five tumor-normal pairs of primary breast epithelial cells were treated for infinite proliferation by using a ROCK inhibitor and mouse feeder cells. Methods: Raw paired-end, 100x coverage RNA-Seq data was aligned to the Human Reference Genome Version 19 using BWA and Tophat. Gene differential expression analysis was completed using Cufflinks and Cuffdiff. Interactive Genome Viewer was used for data visualization. Results: 15 genes were found to be down-regulated by at least one log-fold change in 4/5 of tumor samples. 75 genes were found to be down-regulated in 3/5 of our tumor samples by at least one log-fold change. 11 genes were found to be up-regulated in 4/5 of our tumor samples, and 68 genes were identified to be up-regulated in 3/5 of the tumor samples by at least one-fold change. Conclusion: Expression changes in genes such as AZGP1, AGER, ALG11, and S1007 suggest a disruption in the glycosylation pathway. No correlation was found between Cufflink's Her2 gene-expression and DAKO score classification.
ContributorsHernandez, Fernando (Author) / Anderson, Karen (Thesis director) / Mangone, Marco (Committee member) / Park, Jin (Committee member) / Barrett, The Honors College (Contributor) / Department of Information Systems (Contributor)
Created2013-05
Description
Background
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.
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.
ContributorsZhang, Wenlu (Author) / Feng, Daming (Author) / Li, Rongjian (Author) / Chernikov, Andrey (Author) / Chrisochoides, Nikos (Author) / Osgood, Christopher (Author) / Konikoff, Charlotte (Author) / Newfeld, Stuart (Author) / Kumar, Sudhir (Author) / Ji, Shuiwang (Author) / Biodesign Institute (Contributor) / Center for Evolution and Medicine (Contributor) / College of Liberal Arts and Sciences (Contributor) / School of Life Sciences (Contributor)
Created2013-12-28
Learning Sparse Representations for Fruit-Fly Gene Expression Pattern Image Annotation and Retrieval
Description
Background
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.
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.
ContributorsYuan, Lei (Author) / Woodard, Alexander (Author) / Ji, Shuiwang (Author) / Jiang, Yuan (Author) / Zhou, Zhi-Hua (Author) / Kumar, Sudhir (Author) / Ye, Jieping (Author) / Biodesign Institute (Contributor) / Center for Evolution and Medicine (Contributor) / Ira A. Fulton School of Engineering (Contributor) / College of Liberal Arts and Sciences (Contributor) / School of Life Sciences (Contributor)
Created2012-05-23
Description
Background
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.
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.
ContributorsSun, Qian (Author) / Muckatira, Sherin (Author) / Yuan, Lei (Author) / Ji, Shuiwang (Author) / Newfeld, Stuart (Author) / Kumar, Sudhir (Author) / Ye, Jieping (Author) / Biodesign Institute (Contributor) / Center for Evolution and Medicine (Contributor) / College of Liberal Arts and Sciences (Contributor) / School of Life Sciences (Contributor) / Ira A. Fulton School of Engineering (Contributor)
Created2013-12-03
Description
This report analyzes the intersection that is present between law and technology. It covers the basics of patents and intellectual property law, and then touches briefly about the software side of patent law. The future of patent and technology law are explored as well. The main focus of this report is the patent that was created for a beacon that provides for a full enterprise resource planning solution at both supply chain and full business levels.
ContributorsShah, Dhara Vimesh (Author) / Michelle, Gross (Thesis director) / Stevens, Yvonne (Committee member) / Department of Information Systems (Contributor) / W. P. Carey School of Business (Contributor) / Barrett, The Honors College (Contributor)
Created2016-12
Description
Over the course of 2015-2017, the ASU-SCMA/UASGC Outreach program was developed at Arizona State University (ASU) to support both high school students and college students interested in supply chain management careers. In particular, the program targets the high school students of the Urban Assembly School for Global Commerce (UASGC) and the college students of the ASU Supply Chain Management Association (ASU-SCMA). High school students are partnered with college students in a year-long mentoring program that allows both parties to develop professional supply chain skills. The work of the ASU-SCMA/UASGC Outreach Program is particularly important because it provides UASGC with much needed resources to address urban poverty issues in New York using career and technical education. The Urban Assembly describes its student group as "at-risk, under-resourced youth," and of those youth: - 85% are low-income - 83% enter high school below grade level in at least one subject - 20% require Individualized Education Plans (Special Needs) (urbanassembly.org). The Outreach Program addresses the above issues by providing the high school students with collegiate mentors that develop supply chain and college readiness resources in the form of a case study, site tour, supply chain simulation and presentations. In order to be considered successful, the program must first, equip the high school mentees with tools and skills for a professional career, specifically supply chain management, that they would not otherwise be exposed to; and second, motivate the collegiate participants who are about to enter the workforce to continue to participate in mentoring throughout their careers. This program documents the efforts and results of the pilot year for the Outreach Program that took place from September 2016 through March 2017. Through this pilot program, it was determined that the ASU-SCMA/UASGC Outreach Program is effective and valuable. In fact, the program found that: - 75% of the high school students agreed or strongly agreed that the program helped them learn new business skills. - 75% of the high school students agreed that the program taught them new, interesting things about supply chain. - 75% of the high school students became more interested in college. 100% of the college mentors agreed or strongly agreed that they gained new and important supply chain and professional skills. The success of the pilot year has led to plans for the Outreach Program to become an annual project for ASU-SCMA. This is a program that will continue for the foreseeable future.
ContributorsLam, Tiffany Ai (Author) / Davila, Eduardo (Thesis director) / Manfredo, Mark (Committee member) / Department of Economics (Contributor) / Department of Information Systems (Contributor) / Department of Supply Chain Management (Contributor) / Barrett, The Honors College (Contributor)
Created2016-12
Description
This ethnography outlines the live storytelling culture in Phoenix, Arizona, and what each of its sub-cultures contributes to the city's community. Phoenix's live storytelling events incorporate elements of an ancient art form into contemporary entertainment and sophisticated platforms for community building. These events are described and delineated by stylistic, structural, and content-based differences into the following categories: open-mic, curated, scripted, non-scripted, micro-culture, and marginalized groups. Research presented in this report was collected by reviewing scholarly materials about the social power of storytelling, attending live storytelling events across all categories, and interviewing event organizers and storytellers. My research developed toward an auto-ethnographic direction when I joined the community of storytellers in Phoenix, shifting the thesis to assume a voice of solidarity with the community. This resulted in a research project framed primarily as an ethnography that also includes my initial, personal experiences as a storyteller. The thesis concludes with the art form's macro-influences on Phoenix's rapidly-expanding community.
ContributorsNorton, Maeve (Author) / Dombrowski, Rosemarie (Thesis director) / McAdams, Charity (Committee member) / School of International Letters and Cultures (Contributor) / Department of Information Systems (Contributor) / Barrett, The Honors College (Contributor)
Created2017-12
Description
This thesis examines the value creation potential of renovating an existing commercial real estate asset to a medical office. It begins by examining commercial real estate and the medical sector at a high level. It then discusses the various criteria used to select a subject property for renovation. This renovation is then depicted through a modified pitch book that contains a financial model and pro forma.
ContributorsPeters, Matthew Scott (Co-author) / Larrea, Justin (Co-author) / Berger, Nicholas (Co-author) / Simonson, Mark (Thesis director) / Gray, William (Committee member) / Department of Finance (Contributor, Contributor) / Department of Information Systems (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
Description
This thesis will bring together students to engage in entrepreneurship by finding, measuring and sharing strategic market opportunities. From a student’s perspective, it will take a deep dive into the world of startup ecosystems, markets and trends utilizing both qualitative and quantitative market research techniques. The information gathered has been curated into a productive, meaningful manner, through a report titled “The State of Startups: A Student Perspective.” <br/> The first key theme of this thesis is that market intelligence can be a powerful tool. The second key theme is the power of knowledge implementation towards competitive strategies. The first section of the thesis will focus on identifying and understanding the current “startup” landscape as a basis on which to build strategic and impactful business decisions. This will be accomplished as the team conducts a landscape analysis focused on the student perspective of the student-based North American “entrepreneurial” ecosystem. The second section of the thesis will focus specifically on the personal experiences of student startup founders. This will be accomplished through the analysis of interviews with founders of the startups researched from the first section of the thesis. This will provide us with a direct insight into the student perspective of the student-based North American “entrepreneurial” ecosystem.
ContributorsMinic, Jacob Michael (Co-author) / Callahan, Ryan (Co-author) / Rudick, Justin (Co-author) / Forshey, Cecilia (Co-author) / Hybert, Jacob (Co-author) / Byrne, Jared (Thesis director) / Olsen, Douglas (Committee member) / Curtiss, Ian (Committee member) / Department of Information Systems (Contributor) / Department of Economics (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
Description
With as rapid a growth that Esports has had and its current introduction to the public mainstream, there is yet to be sufficient studies and research compiled to fully develop the profile of an Esport consumer. While companies such as Neilson and others have begun scratching the surface of the Esport community, there is much that is relatively unknown. Consumer behavior patterns of traditional sports has been defined for years, however as the billion dollar a year industry that Esports is, Esport consumer behavior is still taking shape. This thesis will attempt to build upon previous studies conducted by former Arizona State University students to continue to define the Esport consumer. Through quantitative research conducted via an online survey consisting of demographic, behavioral, and psychographic questions, the stereotype of an Esport consumer will be dissolved to reveal their true nature. This study will prove to be an iteration among the previous research by -<br/>• Developing a functional segmentation of Esport consumers, which will allow for marketers within the industry to better understand their audience in their attempts to persuade/incentivize<br/>• Understanding and dissecting the scale of influence that content creators (those who play Esports for the purpose of entertaining through various platforms) and competitive Esport athletes have on certain segmentations of consumers<br/>• Discovering the impact the COVID-19 pandemic has had on certain segmentations in regards to their time spent playing themselves<br/><br/> After compiling results from this questionnaire, marketers that are both endemic and non-endemic brands seeking to partner within the Esports space will have a better understanding of their audience and how to connect with them.
ContributorsPearson, Samuel Tyler (Author) / McIntosh, Daniel (Thesis director) / Eaton, John (Committee member) / Department of Information Systems (Contributor) / Department of Marketing (Contributor) / Department of Management and Entrepreneurship (Contributor) / Sandra Day O'Connor College of Law (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05