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.
The past two and a half semesters have been extremely difficult for college students. Due to the COVID-19 pandemic, student motivation has been slipping. I felt my own productivity slowly diminishing shortly after March 2020, and a number of students that I have spoken with share a similar mentality. In addition, the social lives of students have taken a toll. Social distancing, event cancellations and online classes have led to a serious lack of social interaction with their peers. I felt as though the theatre community, in particular, was suffering, because of how much of our lives are centered around social interaction. Not only is social interaction recreational for us theatre students, but it’s integral for our careers as well. We are very conditioned to getting together multiple times a week just to experience emotion with each other, and this was all taken away very abruptly in March 2020. The remaining theatrical events last season were cancelled, and the events this season were mostly moved to an online setting. I began to think that the theatre community at ASU needed some way to stay connected despite these unfortunate circumstances, and that is when I found out about Alpha Psi Omega. Alpha Psi Omega is a National Theatre Honors Society which used to have a chapter here at ASU, so I took it upon myself to reactivate the chapter.
Research has shown that being a female athlete in a male-dominated sports world is an oppressive burden, yet the experiences of being a black female athlete have been largely ignored. To combat this lack of attention, this paper invokes communication and feminist theorist Bell Hook's concept of moving black women from margin to center to reveal the intersectional oppression of gender and racial narratives that they face in sports. By outlining the difference between white and black femininity and studying media portrayals of popular black female athletes such as Venus and Serena Williams and others, it becomes obvious how black women are typecast into certain social and athletic roles. This research also includes an auto-ethnographic component of my own experience as a black female lacrosse player at the NCAA Division I level. This component functions as a point of comparison and contrast of the ideas and concepts I discuss. Lastly, I offer recommendations and suggestions as to how to empower young black female athletes and retain them in a variety of sports. The goal of my thesis is to place special attention onto black women in an area which there is an extreme lack of representation. My own empirical research has led me to the conclusion that not only is such a discussion important, but it is absolutely necessary. If we are to fight back against hegemonic social structures such as racism and gender roles in the sports world, we must first understand what we are up against. My thesis gives us a glimpse into our imposing opponents, and I hope that future research continues this trend so that black female athletes like myself may one day be considered an athlete in the same sense that our white peers are.
This work explores the dynamic of gender and sport through the lens of Title IX, with the intention of highlighting the importance of gender equality within athletics.
Building on research on family communication and forgiveness, this study seeks to understand how families communicate the value and practice of forgiveness. Through semi-structured interviews, the study asks participants to recall their formative conversations and experiences about forgiveness with their family members and to discuss how those conversations influenced their current perspectives on forgiveness. Interviews from five female undergraduate students yielded seven main themes from where individuals learn how to forgive: 1) Sibling conflicts, 2) Family conversations about friendship conflicts, 3) Conversations with Mom, 4) Living by example, 5) Take the high road, 6) “Life’s too short”, and 7) Messages rooted in faith and morality.
The media often portrays and the public often percieves white women and women of color politicians experience feminist obstacles, such as the masculine-feminine double bind and being dehumanized in the same way. Many of these representations of women of color politicians in society do not incorporate the impact of intersectionality and confining gender schemas; therefore, women of color politician’s experiences are often lumped together with that of their white women counterparts. This phenomenon ultimately contributes to the persistence of color-blind racism in the United States, which negatively effects the life outcomes of women of color politicians and women of color in general. In effort to help lessen the effects of color-blind racism locally and in government, some tools on how to reflect on one’s own biases are provided and avenues for change are proposed.
The current study investigated emotional language use in middle aged and older adults in interviews in which they were asked questions relating to Alzheimer's disease and related dementias. Participants were split into two groups, one that attended Memory Clinic to have their cognition assessed, representing information seekers, and those who did not attend. These interviews were then transcribed and run through LIWC2015 software to determine linguistic differences between the two groups. Results did not indicate statistically significant differences between language use in those who attended Memory Clinic compared with those who did not. Further study with a sample that has higher levels of anxiety related to Alzheimer's disease and related dementias may produce statistically significant results.