Evaluation of methods for detecting conversion events in gene clusters

Background: Gene clusters are genetically important, but their analysis poses significant computational challenges. One of the major reasons for these difficulties is gene conversion among the duplicated regions of the cluster, which can obscure their true relationships. Many computational methods for detecting gene conversion events have been released, but their performance has not been assessed for wide deployment in evolutionary history studies due to a lack of accurate evaluation methods. Results: We designed a new method that simulates gene cluster evolution, including large-scale events of duplication, deletion, and conversion as well as small mutations. We used this simulation data to evaluate several different programs for detecting gene conversion events. Conclusions: Our evaluation identifies strengths and weaknesses of several methods for detecting gene conversion, which can contribute to more accurate analysis of gene cluster evolution

ILR Faculty Publications 2007-08

The production of scholarly research continues to be one of the primary missions of the ILR School. During a typical academic year, ILR faculty members published or had accepted for publication over 25 books, edited volumes, and monographs, 170 articles and chapters in edited volumes, numerous book reviews. In addition, a large number of manuscripts were submitted for publication, presented at professional association meetings, or circulated in working paper form. Our faculty's research continues to find its way into the very best industrial relations, social science and statistics journals.Faculty_Publications_2007_08.pdf: 39 downloads, before Oct. 1, 2020

Cloud Services Brokerage for Mobile Ubiquitous Computing

Recently, companies are adopting Mobile Cloud Computing (MCC) to efficiently deliver enterprise services to users (or consumers) on their personalized devices. MCC is the facilitation of mobile devices (e.g., smartphones, tablets, notebooks, and smart watches) to access virtualized services such as software applications, servers, storage, and network services over the Internet. With the advancement and diversity of the mobile landscape, there has been a growing trend in consumer attitude where a single user owns multiple mobile devices. This paradigm of supporting a single user or consumer to access multiple services from n-devices is referred to as the Ubiquitous Cloud Computing (UCC) or the Personal Cloud Computing. In the UCC era, consumers expect to have application and data consistency across their multiple devices and in real time. However, this expectation can be hindered by the intermittent loss of connectivity in wireless networks, user mobility, and peak load demands. Hence, this dissertation presents an architectural framework called, Cloud Services Brokerage for Mobile Ubiquitous Cloud Computing (CSB-UCC), which ensures soft real-time and reliable services consumption on multiple devices of users. The CSB-UCC acts as an application middleware broker that connects the n-devices of users to the multi-cloud services. The designed system determines the multi-cloud services based on the user's subscriptions and the n-devices are determined through device registration on the broker. The preliminary evaluations of the designed system shows that the following are achieved: 1) high scalability through the adoption of a distributed architecture of the brokerage service, 2) providing soft real-time application synchronization for consistent user experience through an enhanced mobile-to-cloud proximity-based access technique, 3) reliable error recovery from system failure through transactional services re-assignment to active nodes, and 4) transparent audit trail through access-level and context-centric provenance

Integration of multiple data sources to prioritize candidate genes using discounted rating system

Background: Identifying disease gene from a list of candidate genes is an important task in bioinformatics. The main strategy is to prioritize candidate genes based on their similarity to known disease genes. Most of existing gene prioritization methods access only one genomic data source, which is noisy and incomplete. Thus, there is a need for the integration of multiple data sources containing different information. Results: In this paper, we proposed a combination strategy, called discounted rating system (DRS). We performed leave one out cross validation to compare it with N-dimensional order statistics (NDOS) used in Endeavour. Results showed that the AUC (Area Under the Curve) values achieved by DRS were comparable with NDOS on most of the disease families. But DRS worked much faster than NDOS, especially when the number of data sources increases. When there are 100 candidate genes and 20 data sources, DRS works more than 180 times faster than NDOS. In the framework of DRS, we give different weights for different data sources. The weighted DRS achieved significantly higher AUC values than NDOS. Conclusion: The proposed DRS algorithm is a powerful and effective framework for candidate gene prioritization. If weights of different data sources are proper given, the DRS algorithm will perform better

Biomedical relation extraction:from binary to complex

Biomedical relation extraction aims to uncover high-quality relations from life science literature with high accuracy and efficiency. Early biomedical relation extraction tasks focused on capturing binary relations, such as protein-protein interactions, which are crucial for virtually every process in a living cell. Information about these interactions provides the foundations for new therapeutic approaches. In recent years, more interests have been shifted to the extraction of complex relations such as biomolecular events. While complex relations go beyond binary relations and involve more than two arguments, they might also take another relation as an argument. In the paper, we conduct a thorough survey on the research in biomedical relation extraction. We first present a general framework for biomedical relation extraction and then discuss the approaches proposed for binary and complex relation extraction with focus on the latter since it is a much more difficult task compared to binary relation extraction. Finally, we discuss challenges that we are facing with complex relation extraction and outline possible solutions and future directions

Annual Research Report, 2009-2010

Annual report of collaborative research projects of Old Dominion University faculty and students in partnership with business, industry and governmenthttps://digitalcommons.odu.edu/or_researchreports/1001/thumbnail.jp

Educational applications of augmented reality: A bibliometric study

[EN] Augmented Reality (AR) has been used successfully in several industries; one of these is education. A systematic understanding of how AR contributes to education still lacks studies about the content type and its effects on learning outcomes. This article systematically analyzes the AR state-of-the-art in education, determines productivity and publication indicators in this field, and identifies research works that have studied how content type affects the learning outcomes. The methodology was performed through a bibliometric analysis using the Scopus database, focusing on AR's educational uses. Engineering education is the primary research trend, followed by simulation, tracking, and virtual reality. Education and e-learning also have leading roles within this analysis, along with gamification and human-computer interaction, whose impacts are further explored. There is no preferred design methodology for creating AR content. In its absence, most of the works suggest a design based on the developers' and researchers' experience.The authors thank the editors and two anonymous reviewers for their highly constructive feedback. The authors also would like to acknowledge the technical support of Writing Lab, Institute for the Future of Education, Tecnologico de Monterrey, Mexico, in the production of this workHincapié, M.; Díaz, C.; Valencia, A.; Contero, M.; Güemes-Castorena, D. (2021). Educational applications of augmented reality: A bibliometric study. Computers & Electrical Engineering. 93:1-11. https://doi.org/10.1016/j.compeleceng.2021.1072891119

GenoLink: a graph-based querying and browsing system for investigating the function of genes and proteins

BACKGROUND: A large variety of biological data can be represented by graphs. These graphs can be constructed from heterogeneous data coming from genomic and post-genomic technologies, but there is still need for tools aiming at exploring and analysing such graphs. This paper describes GenoLink, a software platform for the graphical querying and exploration of graphs. RESULTS: GenoLink provides a generic framework for representing and querying data graphs. This framework provides a graph data structure, a graph query engine, allowing to retrieve sub-graphs from the entire data graph, and several graphical interfaces to express such queries and to further explore their results. A query consists in a graph pattern with constraints attached to the vertices and edges. A query result is the set of all sub-graphs of the entire data graph that are isomorphic to the pattern and satisfy the constraints. The graph data structure does not rely upon any particular data model but can dynamically accommodate for any user-supplied data model. However, for genomic and post-genomic applications, we provide a default data model and several parsers for the most popular data sources. GenoLink does not require any programming skill since all operations on graphs and the analysis of the results can be carried out graphically through several dedicated graphical interfaces. CONCLUSION: GenoLink is a generic and interactive tool allowing biologists to graphically explore various sources of information. GenoLink is distributed either as a standalone application or as a component of the Genostar/Iogma platform. Both distributions are free for academic research and teaching purposes and can be requested at [email protected]. A commercial licence form can be obtained for profit company at [email protected]. See also

A mapping study on documentation in Continuous Software Development

Context: With an increase in Agile, Lean, and DevOps software methodologies over the last years (collectively referred to as Continuous Software Development (CSD)), we have observed that documentation is often poor. Objective: This work aims at collecting studies on documentation challenges, documentation practices, and tools that can support documentation in CSD. Method: A systematic mapping study was conducted to identify and analyze research on documentation in CSD, covering publications between 2001 and 2019. Results: A total of 63 studies were selected. We found 40 studies related to documentation practices and challenges, and 23 studies related to tools used in CSD. The challenges include: informal documentation is hard to understand, documentation is considered as waste, productivity is measured by working software only, documentation is out-of-sync with the software and there is a short-term focus. The practices include: non-written and informal communication, the usage of development artifacts for documentation, and the use of architecture frameworks. We also made an inventory of numerous tools that can be used for documentation purposes in CSD. Overall, we recommend the usage of executable documentation, modern tools and technologies to retrieve information and transform it into documentation, and the practice of minimal documentation upfront combined with detailed design for knowledge transfer afterwards. Conclusion: It is of paramount importance to increase the quantity and quality of documentation in CSD. While this remains challenging, practitioners will benefit from applying the identified practices and tools in order to mitigate the stated challenges

The relationship between e-government system and government operation excellence in the Sultanate of Oman

Every government is seeking to provide the best services to demonstrate efficiency and excellence of performance. This goal could be achieved by improving the service performance of entire sectors in society. The government of Sultanate of Oman has realized the importance of moving towards information technology. Therefore, e-Government initiatives were launched in Oman as a part of overall country information technology in 1998. It was first established under the name “Digital Oman”. Every government sector has since upgraded the performance by having its own websites and e-services application. However, there are gaps and loose connections exist among the sectors, which has consequently tarnished the image of Omani E-government. This has led to important questions about the requirement of modification and improvement of such service. Hence, the purpose of this research is to investigate and explore the factors that drive the e-government implementation and affect the government performance as well as the government-citizen relationship in Sultanate of Oman. A survey was conducted among Omani citizens in order to have their feedback and overview of the current e-government in the Sultanate, their technological and behavioral intention in using the e-government system and the governmental operation excellence (GOE) of the system. The outcomes of the study indicate that the e-government system has a direct effect towards GOE. The ‘technology intention to use’ is found to have a mediating effect, while the ‘behavioral intention to use’ has a partially mediating effect on the e-government project approach from citizen's point of view. The study outcomes should offer guidance to conduct e-government projects, especially for the policy makers in the Sultanate of Oman for future researchers. It also can provide a foundation for future researches related to the issues of the government-citizen relationship