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Description
Genes have widely different pertinences to the etiology and pathology of diseases. Thus, they can be ranked according to their disease-significance on a genomic scale, which is the subject of gene prioritization. Given a set of genes known to be related to a disease, it is reasonable to use them as a basis to determine the significance of other candidate genes, which will then be ranked based on the association they exhibit with respect to the given set of known genes. Experimental and computational data of various kinds have different reliability and relevance to a disease under study. This work presents a gene prioritization method based on integrated biological networks that incorporates and models the various levels of relevance and reliability of diverse sources. The method is shown to achieve significantly higher performance as compared to two well-known gene prioritization algorithms. Essentially, no bias in the performance was seen as it was applied to diseases of diverse ethnology, e.g., monogenic, polygenic and cancer. The method was highly stable and robust against significant levels of noise in the data. Biological networks are often sparse, which can impede the operation of associationbased gene prioritization algorithms such as the one presented here from a computational perspective. As a potential approach to overcome this limitation, we explore the value that transcription factor binding sites can have in elucidating suitable targets. Transcription factors are needed for the expression of most genes, especially in higher organisms and hence genes can be associated via their genetic regulatory properties. While each transcription factor recognizes specific DNA sequence patterns, such patterns are mostly unknown for many transcription factors. Even those that are known are inconsistently reported in the literature, implying a potentially high level of inaccuracy. We developed computational methods for prediction and improvement of transcription factor binding patterns. Tests performed on the improvement method by employing synthetic patterns under various conditions showed that the method is very robust and the patterns produced invariably converge to nearly identical series of patterns. Preliminary tests were conducted to incorporate knowledge from transcription factor binding sites into our networkbased model for prioritization, with encouraging results. Genes have widely different pertinences to the etiology and pathology of diseases. Thus, they can be ranked according to their disease-significance on a genomic scale, which is the subject of gene prioritization. Given a set of genes known to be related to a disease, it is reasonable to use them as a basis to determine the significance of other candidate genes, which will then be ranked based on the association they exhibit with respect to the given set of known genes. Experimental and computational data of various kinds have different reliability and relevance to a disease under study. This work presents a gene prioritization method based on integrated biological networks that incorporates and models the various levels of relevance and reliability of diverse sources. The method is shown to achieve significantly higher performance as compared to two well-known gene prioritization algorithms. Essentially, no bias in the performance was seen as it was applied to diseases of diverse ethnology, e.g., monogenic, polygenic and cancer. The method was highly stable and robust against significant levels of noise in the data. Biological networks are often sparse, which can impede the operation of associationbased gene prioritization algorithms such as the one presented here from a computational perspective. As a potential approach to overcome this limitation, we explore the value that transcription factor binding sites can have in elucidating suitable targets. Transcription factors are needed for the expression of most genes, especially in higher organisms and hence genes can be associated via their genetic regulatory properties. While each transcription factor recognizes specific DNA sequence patterns, such patterns are mostly unknown for many transcription factors. Even those that are known are inconsistently reported in the literature, implying a potentially high level of inaccuracy. We developed computational methods for prediction and improvement of transcription factor binding patterns. Tests performed on the improvement method by employing synthetic patterns under various conditions showed that the method is very robust and the patterns produced invariably converge to nearly identical series of patterns. Preliminary tests were conducted to incorporate knowledge from transcription factor binding sites into our networkbased model for prioritization, with encouraging results. To validate these approaches in a disease-specific context, we built a schizophreniaspecific network based on the inferred associations and performed a comprehensive prioritization of human genes with respect to the disease. These results are expected to be validated empirically, but computational validation using known targets are very positive.
ContributorsLee, Jang (Author) / Gonzalez, Graciela (Thesis advisor) / Ye, Jieping (Committee member) / Davulcu, Hasan (Committee member) / Gallitano-Mendel, Amelia (Committee member) / Arizona State University (Publisher)
Created2011
Description
Service based software (SBS) systems are software systems consisting of services based on the service oriented architecture (SOA). Each service in SBS systems provides partial functionalities and collaborates with other services as workflows to provide the functionalities required by the systems. These services may be developed and/or owned by different entities and physically distributed across the Internet. Compared with traditional software system components which are usually specifically designed for the target systems and bound tightly, the interfaces of services and their communication protocols are standardized, which allow SBS systems to support late binding, provide better interoperability, better flexibility in dynamic business logics, and higher fault tolerance. The development process of SBS systems can be divided to three major phases: 1) SBS specification, 2) service discovery and matching, and 3) service composition and workflow execution. This dissertation focuses on the second phase, and presents a privacy preserving service discovery and ranking approach for multiple user QoS requirements. This approach helps service providers to register services and service users to search services through public, but untrusted service directories with the protection of their privacy against the service directories. The service directories can match the registered services with service requests, but do not learn any information about them. Our approach also enforces access control on services during the matching process, which prevents unauthorized users from discovering services. After the service directories match a set of services that satisfy the service users' functionality requirements, the service discovery approach presented in this dissertation further considers service users' QoS requirements in two steps. First, this approach optimizes services' QoS by making tradeoff among various QoS aspects with users' QoS requirements and preferences. Second, this approach ranks services based on how well they satisfy users' QoS requirements to help service users select the most suitable service to develop their SBSs.
ContributorsYin, Yin (Author) / Yau, Stephen S. (Thesis advisor) / Candan, Kasim (Committee member) / Dasgupta, Partha (Committee member) / Santanam, Raghu (Committee member) / Arizona State University (Publisher)
Created2011
Description
Individuals' experiences, environment, and education greatly impact their entire being. Similarly, a designer is affected by these elements, which impacts how, what and why they design. In order for design education to generate designers who are more socially aware problem solvers, that education must introduce complex social matters and not just design skills. Traditionally designers learned through apprenticing a master. Most design education has moved away from this traditional model and has begun incorporating a well-rounded program of study, yet there are still more improvements to be made. This research proposes a new Integrated Transformational Experience Model, ITEM, for design education which will be rooted in sustainability, cultural integration, social embeddedness, and discipline collaboration. The designer will be introduced to new ideas and experiences from the immersion of current social issues where they will gain experience creating solutions to global problems enabling them to become catalysts of change. This research is based on interviews with industrial design students to gain insights, benefits and drawbacks of the current model of design education. This research will expand on the current model for design education, combining new ideas that will shed light on the future of design disciplines through the education and motivation of designers. The desired outcome of this study is to incorporate hands on learning through social issues in design classrooms, identify ways to educate future problem solvers, and inspire more research on this issue.
ContributorsWingate, Andrea (Author) / Takamura, John (Thesis advisor) / Stamm, Jill (Committee member) / Bender, Diane (Committee member) / Arizona State University (Publisher)
Created2011
Description
This study examines the experiences of parents in mixed marriages (Vietnamese married to non-Vietnamese) raising their children in the United States. Specifically, this study focused on what factors influence parents' development of family language policies and patterns of language use. While research has been done on language policy and planning at the macro-level and there are an increasing number of studies on family language policy at the microlevel, few studies have focused on couples in mixed marriages who are heritage language speakers of the language they are trying to teach their children. This study used both surveys and interviews to gather data about parents' beliefs and attitudes towards bilingualism and the heritage language (HL), strategies parents are using to teach their children the HL, and major challenges they face in doing so. There were three main findings. First, parents without full fluency in the HL nevertheless are able to pass the HL on to their children. Second, an important factor influencing parents' family language policies and patterns of language use were parents' attitudes towards the HL--specifically, if parents felt it was important for their children to learn the HL and if parents were willing to push their children to do so. Third, proximity to a large Vietnamese community and access to Vietnamese resources (e.g., Vietnamese language school, Vietnamese church/temple, etc.) did not assure families' involvement in the Vietnamese community or use of the available Vietnamese resources. The findings of this study reveal that though language shift is occurring in these families, parents are still trying to pass on the HL to their children despite the many challenges of raising them bilingually in the U.S.
ContributorsLam, Ha (Author) / Wiley, Terrence (Thesis advisor) / Appleton, Nicholas (Thesis advisor) / Tobin, Joseph (Committee member) / Arizona State University (Publisher)
Created2011
Description
ABSTRACT In Roosevelt v. Bishop (1994), Arizona public school districts and parents challenged Arizona's school financing system arguing that it was not "general and uniform" as required by the Arizona Constitution. The purpose of this study was to analyze Arizona's Students Fair and Immediate Resources for Students Today (Students FIRST) legislation, the remedy that resulted from the Roosevelt decision, empirically, and longitudinally. Three types of statistical analyses were conducted on a sample of 165 public school districts. Fiscal neutrality was measured for each of the eleven years of the study, to assess the association between the per-pupil Students FIRST funding level and the per-pupil property wealth. Multiple regression analysis was also conducted to assess if both property wealth and district size were associated with the distribution of Students FIRST funding. Finally, I analyzed the eleven-year average of the total Students FIRST funding distributed to school districts and assessed how the plaintiff districts ranked in the distribution. Overall, the findings revealed that Students FIRST met the fiscal neutrality standard in some, but not in all the categories and years of this study, per-pupil property wealth was only weakly related to, and district size was not associated with, Students FIRST funding. The analysis of average funding suggested that some property rich school districts benefited most from Students FIRST. These results suggest that the traditional measures used to assess the fiscal neutrality of operating funding may not be appropriate for assessing the fiscal neutrality of capital finance reforms. While the results of this study provide some suggestive evidence that Students FIRST did not fulfill the Court's mandate, additional research is needed as to whether or not Arizona's capital finance system has resulted in disparities in funding that fall short of the constitutional standard.
ContributorsBaca, Kenneth R (Author) / Powers, Jeanne M. (Thesis advisor) / Garcia, David R. (Committee member) / Essigs, Chuck (Committee member) / Arizona State University (Publisher)
Created2011
Description
Advancements in computer vision and machine learning have added a new dimension to remote sensing applications with the aid of imagery analysis techniques. Applications such as autonomous navigation and terrain classification which make use of image classification techniques are challenging problems and research is still being carried out to find better solutions. In this thesis, a novel method is proposed which uses image registration techniques to provide better image classification. This method reduces the error rate of classification by performing image registration of the images with the previously obtained images before performing classification. The motivation behind this is the fact that images that are obtained in the same region which need to be classified will not differ significantly in characteristics. Hence, registration will provide an image that matches closer to the previously obtained image, thus providing better classification. To illustrate that the proposed method works, naïve Bayes and iterative closest point (ICP) algorithms are used for the image classification and registration stages respectively. This implementation was tested extensively in simulation using synthetic images and using a real life data set called the Defense Advanced Research Project Agency (DARPA) Learning Applied to Ground Robots (LAGR) dataset. The results show that the ICP algorithm does help in better classification with Naïve Bayes by reducing the error rate by an average of about 10% in the synthetic data and by about 7% on the actual datasets used.
ContributorsMuralidhar, Ashwini (Author) / Saripalli, Srikanth (Thesis advisor) / Papandreou-Suppappola, Antonia (Committee member) / Turaga, Pavan (Committee member) / Arizona State University (Publisher)
Created2011
Description
One of the critical imperatives for the development of inclusive school systems is the capacity to nurture and develop teachers who have the skills, critical sensibilities, and the contextual awareness to provide quality educational access, participation, and outcomes for all students; however, research on teacher learning for inclusive education has not yet generated a robust body of knowledge to understand how teachers become inclusive teachers in institutions where exclusion is historical and ubiquitous. Drawing from socio-cultural theory, this study aimed to fill this gap through an examination of teacher learning for inclusive education in an urban professional learning school. In particular, I aimed to answer the following two questions: (a) What social discourses are present in a professional learning school for inclusive education?, and (b) How do teachers appropriate these social discourses in situated practice? I used analytical tools from Critical Discourse Analysis (CDA) and Grounded Theory to analyze entry and exit interviews with teacher residents, principals, site professors, and video-stimulated interviews with teacher residents, observations of classroom practices and thesis seminars, and school documents. I found two social discourses that I called discourses of professionalism, as they offered teachers a particular combination of tools, aiming to universalize certain tools for doing and thinking that signaled what it meant to be a professional teacher in the participating schools. These were the Total Quality Management like discourse (TQM-like) and the Inclusive Education-like discourse. The former was dominant in the schools, whereas the latter was dominant in the university Master's program. These discourses overlapped in teachers' classrooms practices, creating tensions. To understand how these tensions were resolved, this study introduced the concept of curating, a kind of heuristic development that pertains particularly to the work achieved in boundary practices in which individuals must claim multiple memberships by appropriating the discourses and their particular tool kits of more than one community of practice. This study provides recommendations for future research and the engineering of professional development efforts for inclusive education.
ContributorsWaitoller, Federico R. (Author) / Artiles, Alfredo J. (Thesis advisor) / Kozleski, Elizabeth B. (Committee member) / Gee, James P (Committee member) / Arizona State University (Publisher)
Created2011
Description
This thesis proposed a novel approach to establish the trust model in a social network scenario based on users' emails. Email is one of the most important social connections nowadays. By analyzing email exchange activities among users, a social network trust model can be established to judge the trust rate between each two users. The whole trust checking process is divided into two steps: local checking and remote checking. Local checking directly contacts the email server to calculate the trust rate based on user's own email communication history. Remote checking is a distributed computing process to get help from user's social network friends and built the trust rate together. The email-based trust model is built upon a cloud computing framework called MobiCloud. Inside MobiCloud, each user occupies a virtual machine which can directly communicate with others. Based on this feature, the distributed trust model is implemented as a combination of local analysis and remote analysis in the cloud. Experiment results show that the trust evaluation model can give accurate trust rate even in a small scale social network which does not have lots of social connections. With this trust model, the security in both social network services and email communication could be improved.
ContributorsZhong, Yunji (Author) / Huang, Dijiang (Thesis advisor) / Dasgupta, Partha (Committee member) / Syrotiuk, Violet (Committee member) / Arizona State University (Publisher)
Created2011
Description
In the last few decades, the rapid development of electronic music technologies has changed the way society interacts with music, which in turn impacts the profession of music therapy. Except for a few cases, music therapy has not extensively explored the integration of new technology. However, current research trends show a willingness and excitement to explore the possibilities (Nagler, 2011; Ramsey, 2011; Magee, et al., 2011; Magee & Burland, 2008; Magee 2006). The project described in this paper intends to demonstrate one of these possibilities by combining modern technologies to create an interactive musical system with practical applications in music therapy. In addition to designing a practical tool, the project aims to question the role of technology in music therapy and to initiate dialogue between technologists and music therapists. The project, entitled MIST: A Musical Interactive Space for Therapy, uses modern gestural technology (the Microsoft® Kinect®) to capture body movements and turn them into music. It is intended for use in a clinical setting with children with mild to moderate disabilities. The system is a software/hardware package that is inexpensive, user-friendly, and portable. There are two functional modes of the system: the first sonifies specific movement tasks of reaching and balancing; the second is an interactive musical play space in which an entire room becomes responsive to presence and movement, creating a sonic playground. The therapeutic goals of the system are to motivate and train physical movement, encourage exploration of space and the body, and allow for musical expression, play, auditory perception, and social interaction.
ContributorsHeadlee, Kimberlee (Author) / Ingalls, Todd M (Thesis advisor) / Crowe, Barbara J. (Thesis advisor) / Stauffer, Sandra L (Committee member) / Arizona State University (Publisher)
Created2011
Description
Michael Apple's scholarship on curriculum, educational ideology, and official knowledge continues to be influential to the study of schooling. Drawing on the sociological insights of Pierre Bourdieu and the cultural studies approaches of Raymond Williams, Apple articulates a theory of schooling that pays particular attention to how official knowledge is incorporated into the processes of schooling, including textbooks. In an effort to contribute to Apple's scholarship on textbooks, this study analyzed high school American history textbooks from the 1960s through the 2000s with specific attention to the urban riots of the late-1960s, sixties counterculture, and the women's movement utilizing Julia Kristeva's psychoanalytic concept of abjection to augment Apple's theory of knowledge incorporation. This combination reveals not only how select knowledge is incorporated as official knowledge, but also how knowledge is treated as abject, as unfit for the curricular body of official knowledge and the selective tradition of American history. To bridge the theoretical frameworks of incorporation and abjection Raymond Williams' theory of structures of feeling and Slavoj iek's theory of ideological quilting are employed to show how feelings and emotional investments maintain ideologies. The theoretical framework developed and the interpretive analyses undertaken demonstrate how textbook depictions of these historical events structure students' present educational experiences with race, class, and gender.
ContributorsKearl, Benjamin (Author) / Margolis, Eric (Thesis advisor) / Blumenfeld-Jones, Donald (Committee member) / Sandlin, Jennifer (Committee member) / Arizona State University (Publisher)
Created2011