Matching Items (70)
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
With the acknowledgement of Type 2 Diabetes as a disease that disproportionately affects the Latinx communities, this study is designed to look at the relationship between health literacy and diabetes awareness. This research was conducted using data from Dr. Felipe Castro's previous study on Latino Lifestyles for Diabetes Prevention. Multiple linear regressions were ran to find the correlation between certain measures and diabetes awareness. Major findings included seeing the positive relationship between education and diabetes awareness and the negative correlation between Behavior Intentions Self Monitoring and diabetes awareness. Further studies are required to see how different social factors impact an individual's ability to gain health literacy regarding Type 2 Diabetes.
ContributorsHuerta, Isabel (Author) / Castro, Felipe (Thesis director) / Lopez, Gilberto (Committee member) / Barrett, The Honors College (Contributor) / School of Human Evolution & Social Change (Contributor) / School of Public Affairs (Contributor) / School of Life Sciences (Contributor)
Created2024-05
Description
Type 2 diabetes mellitus is the most common form that exists and has many variables that play into its development and diagnosis. This study looks at some of the factors that may have played an impact on people who are pre-diabetic or at risk of being pre-diabetic. Pre-diabetes can often serve as a warning sign for people and presents them with an opportunity for intervention before their condition worsens. However, it often goes unnoticed due to the lack of education regarding healthy living and making better quality-of-life decisions in Hispanic communities. The purpose of this study was to help identify patterns in how people from these communities manage their conditions and find techniques that can be replicated by others in order to improve health outcomes.
This study followed a mixed methods approach in order to gain a full understanding of the quantitative (QUAN) and qualitative (QUAL) aspects that may have an impact on diabetes. Data was collected using a questionnaire to analyze different aspects and lifestyles of the participants and an interview with probing questions regarding life decisions, beliefs, and expectations. The overarching research question was “How did varying levels of health motivation and healthful eating habits affect glycosylated hemoglobin levels (HbA1c) in Hispanic/Latinx populations who are at risk of or are pre-diabetic?”. With this, we can obtain a better understanding of certain key aspects that play a role in the development of diabetes.
A correlations matrix analysis was run to test how certain variables related and caused changes with one another. To analyze how these variables related specifically to HbA1c, our dependent variable, a multiple regression model analysis was used. It was found that the main contributors to elevated HbA1c levels were health motivation and age. A joint display analysis combined different levels of health motivation, QUAN data, and the responses to a focus question regarding efforts taken to improve one's condition, QUAL. This displayed a pattern of participants with higher health motivation showing efforts to reduce their diabetes risk and by contrast, low health motivation participants showing minimal to no efforts in changing behavior.
This study found that elevated HbA1c levels also come with higher health motivation which normally wouldn’t make sense. However, the participants from this study knew about their HbA1c levels before this survey was conducted which means that these people already knew about the dangers of their condition and may have been taking steps to mitigate further risk. This demonstrates the importance of developing education systems to help inform people about risk factors and symptoms to alert them of their condition.
It is common in Hispanic areas for people to cook high-fat foods, lard, or oil which often lead to an increased risk of diabetes. There is also a great difference in the amount of resources that Hispanic communities have for practicing healthy lifestyle habits and less effective self-monitoring that makes it difficult to recognize early signs of diabetes. Promoting interventions that help educate about the risks of diabetes could encourage great change in eating habits, activity levels, and overall health outcomes for people from Hispanic communities.
ContributorsZafar, Rehan (Author) / Castro, Felipe (Thesis director) / Kavouras, Stavros (Committee member) / Barrett, The Honors College (Contributor) / School of Humanities, Arts, and Cultural Studies (Contributor) / College of Health Solutions (Contributor)
Created2024-05
Description
This study utilized a Convergent Mixed Methods design to identify different expressions of resilience in response to a health/familial problem. The research aimed to determine which specific expressions of resilience were significantly associated with higher levels of resilience. The findings revealed two significant effects related to social support and persistence as expressions of resilience. The High Resilience group exhibited a higher proportion of individuals mentioning persistence and social support in their coping strategies. The study concluded that social support seeking is a major coping strategy among individuals with high resilience and suggested that healthcare providers, particularly nurses, should recommend and provide resources for clients to seek social support. Furthermore, the role of persistence highlights the importance of encouraging clients to set achievable goals, develop a plan, and monitor their progress to remain motivated in resolving their difficult health-related problem.
ContributorsJohn, Avery (Author) / Castro, Felipe (Thesis director) / Lober, Angela (Committee member) / Juarigue, Lisa (Committee member) / Barrett, The Honors College (Contributor) / Edson College of Nursing and Health Innovation (Contributor)
Created2023-05
Description
A leading chronic disease within the United States, type 2 diabetes mellitus (T2D) disproportionately affects the Latinx-American population. Given that prediabetes is closely correlated to the eventual development of T2D, this paper examines the effects of five sociopsychological variables - socioeconomic status, acculturation, education, exercise behavior, and high caloric intake - as associated with levels of glycosylated hemoglobin (A1c), among prediabetic Latinx adults to identify which of these five factors exhibits the strongest association, and is thereby the strongest risk factor for the development of T2D. Accordingly, the overarching research question for the study is the following: “Which of these five identified variables has the strongest correlation with levels of A1c among prediabetic Latinx adults, both men and women?” 35 cases of adult Latinx American individuals with a known history of prediabetes were analyzed to form the database for the study. Initial correlations matrices served as an exploratory analysis, and affirmed expected findings of a strongly negative correlation between each of the following three variables – household income, acculturation, and high caloric intake – and A1c levels. The revised final multiple regression model confirmed a negative correlation between acculturation and A1c levels, while also demonstrating a positive correlation between both health motivation and low-density lipoprotein (LDL) in regards to A1c levels. These observations demonstrate the need for further research to better understand these correlations, and thereby improve health disparities for the Latinx-American community as a whole.
ContributorsMagiyawala, Rashi (Author) / Castro, Felipe (Thesis director) / Lopez, Gilberto (Committee member) / Barrett, The Honors College (Contributor) / Dean, W.P. Carey School of Business (Contributor) / School of Transborder Studies (Contributor) / School of Life Sciences (Contributor) / School of Art (Contributor)
Created2024-05
Description
The present study, Examination of Parent-Child Relationships in Latino Families
investigated the relationship between early adolescent experiences on coping behaviors, as
determinants of present day depressive symptoms and resilience. Three multiple regression
models were conducted (Model 1) Predictors of Problem Solving Coping, (Model 2) Predictors
of Depressive Symptoms, (Model 3) Predictors of Resilience. Following this a cross tabulation
analysis was conducted to look at (Yes = Mention) and (No = No Mention) of Active Problem
Solving across 3 levels of Quality of Relationship with Father. This study found that (a) Quality
of Relationship with Father was a significant predictor of Problem Solving Coping Behavior.
Also, (a) Father Expectations and Problem Solving Coping Behavior in adolescence were
significant positive predictors of Resilience. This evidence suggests that Quality of Relationship
with Father in adolescence aids in the development of specific skills and capabilities for (a)
effective Problem Solving Coping Behaviors and (b) effective Expression of Resilience.
ContributorsCarbajal, Robert (Author) / Castro, Felipe (Thesis director) / Carlos Chavez, Fiorella (Committee member) / Barrett, The Honors College (Contributor) / Department of Psychology (Contributor)
Created2024-05
Description
The Walter Cronkite School of Journalism and Mass Communications stands as a "gold standard" of journalism education throughout the country. In my time at the school though, I found that some aspects in the whole of the curriculum were missing. I as well as several other friends became interested in production and the technical side of things. This seemed to be the direction we wanted to go and soon realized this played a crucial part in journalism. Although there is a studio production class and a studio production track through the immersive Cronkite News program, there is not much in between. This inspired me to take a look deeper into production skills and their place within a journalism education. The project is split into three main sections that dive into the ideas of teaching production skills and technical skills to journalism students and whether or not it is valuable. The first part is the background of the project and why this project came to be. The background section explores the inspiration for the project. The project continues with a look at job statistics and where the industry currently sits. This continues into the final section that contains personal stories and interviews with professionals in the field. This is a critical section to back up claims made through research and evaluation. There is a lot of personal experience and non-traditional research done through this project, but the assertions and conclusions made are clear. Through job statistics, personal stories, and interviews with professionals, this project examines how production could be taught in a traditional journalism program. These stories show that a journalism curriculum may not be the best place to teach production in depth, but that it still is an incredibly important part of the journalism world as a whole.
ContributorsHardy, Joseph Michael (Author) / Jacoby, Jim (Thesis director) / McJannet, Rob (Committee member) / College of Public Service and Community Solutions (Contributor) / Walter Cronkite School of Journalism and Mass Communication (Contributor) / Barrett, The Honors College (Contributor)
Created2016-12
Description
The Chinese tourism market has become the largest tourism market in the world and continues to show promise in its future development. Global destinations such as Southeast Asia, France and now Australia have begun to see a major boom in Chinese tourists within the past decade due to less restrictive travel policies, a growing economy and higher disposable income rates within urban centers in China. Australia has become the top destination among Chinese citizens that wish to travel due to its coastal and beach attractions, unique wildlife, and general welcoming attitude toward Chinese citizens. As the market continues to grow, the characteristics and demographics change as well. The Chinese government did not allow for international travel until the early 1990s. During this time, package tours offered by government-regulated travel agencies were the prominent method of travel planning with travelers over the age of 35 making up the majority of travelers. However, in the past decade there has been a shift from group travel toward independent travel due to higher income and more independence among young adults. There remains a stigma against Chinese tourists due to behavioral and cultural challenges Chinese tourists face when traveling abroad, but as Chinese travelers begin to travel in smaller groups and have greater exposure to international cultures, these negative stereotypes will start to disappear. This paper focuses on the impact the Chinese tourism market has on Cairns, Australia. Cairns is characterized by its backpacking culture, easy access to environmental attractions and a high number of annual travelers from Asia and China specifically. The paper uses qualitative research and compiles information from news sources, government documents and statistical data regarding Chinese outbound tourism and its impacts on Australian tourism. There is also a case study composed of personal observations of a nature park in North Queensland which uses specific marketing and attraction coordination to appeal to Chinese tourists. This case study analyzes the tactics used by local destinations that cater to group travel over independent travel and points out the benefits of this type of specialized tourism. The research concludes by arguing the trend toward independent travel is beneficial to the Cairns tourism industry rather than harmful as long as the industry recognizes the new trends in Chinese tourism and does not focus on the previous trends of group travel when appealing to Chinese tourists. Instead, the industry should continue to focus on the backpacking culture and work toward catering to the demands of millennial travelers.
ContributorsRochon, Jacob Henri (Author) / Goodman, Rebekka (Thesis director) / McWilliams, Claire (Committee member) / College of Public Service and Community Solutions (Contributor) / School of Politics and Global Studies (Contributor) / School of International Letters and Cultures (Contributor) / Barrett, The Honors College (Contributor)
Created2016-12