Bioinformatics Commons^™

Bayesian Methods For Expression-Based Integration, Elizabeth M. Jennings, Jeffrey S. Morris, Raymond J. Carroll, Ganiraju C. Manyam, Veera Baladandayuthapani

Jeffrey S. Morris

We propose methods to integrate data across several genomic platforms using a hierarchical Bayesian analysis framework that incorporates the biological relationships among the platforms to identify genes whose expression is related to clinical outcomes in cancer. This integrated approach combines information across all platforms, leading to increased statistical power in finding these predictive genes, and further provides mechanistic information about the manner in which the gene affects the outcome. We demonstrate the advantages of the shrinkage estimation used by this approach through a simulation, and finally, we apply our method to a Glioblastoma Multiforme dataset and identify several genes potentially …

Hydraphiles: A Rigorously Studied Class Of Synthetic Channel Compounds With In Vivo Activity, Saeedeh Negin, Bryan A. Smith, Alexandra Unger, W. Matthew Leevy, George W. Gokel

George Gokel

No abstract provided.

Comparative Genome Analysis Of Spiroplasma Melliferum Ipmb4a, A Honeybee-Associated Bacterium, Wen-Sui Lo, Ling-Ling Chen, Wan-Chia Chung, Gail E. Gasparich, Chih-Horng Kuo

Gail Gasparich

Ict For Poverty Alleviation In Pacific Island Nations: Study Of Icts4d In Fiji, Deogratias Harorimana, Opeti Rokotuinivono, Emali Sewale, Fane Salaiwai, Marica Naulu, Evangelin Roy

Dr Deogratias Harorimana

ICT for Poverty Alleviation in Pacific Island Nations: Study of ICTs4D in Fiji There has been a vague and little knowledge on the role or potential of Information and Communications Technologies (ICTs) in relation to addressing poverty in Fiji. This may be probably due to the newness of the technology in the South Pacific Region as a whole but also probably due to the fact that only 9.7% of the current Fiji 931,000 populations are internet users (ITC Figures 2011). This paper reports on finding how ICTs is contributing towards poverty alleviation in Fiji. On the basis of reviewed best …

Detection Of Genomic Inversion From Single End Read, Pankaj Ghimire

Master's Theses

Structural Variations (SVs) are genomic rearrangements that include both copy-number variants,such as insertion,deletions, duplications and balanced variants like inversion and translocations. These SVs are getting more attentions for research and investigation because of their role on human phenotype, genetic diseases and genomic rearrangements. Evolution of Next-generation Sequencing has provided golden opportunities to investigate these variants and make their wider and clear spectrum in human genome. This investigation includes identification of type of SVs and their breakpoints at base pair level. For their effective identification and breakpoint resolution, many techniques are devised mainly based on paired end read. With relatively low …

Error Correction In Next Generation Dna Sequencing Data, Michael Z. Molnar

Electronic Thesis and Dissertation Repository

Motivation: High throughput Next Generation Sequencing (NGS) technologies can sequence the genome of a species quickly and cheaply. Errors that are introduced by NGS technologies limit the full potential of the applications that rely on their data. Current techniques used to correct these errors are not sufficient, and a more efficient and accurate program is needed to correct errors.

Results: We have designed and implemented RACER (Rapid Accurate Correction of Errors in Reads), an error correction program that targets the Illumina genome sequencer, which is currently the dominant NGS technology. RACER combines advanced data structures with an intricate analysis of …

An Investigation Of Gene Networks Influenced By Low Dose Ionizing Radiation Using Statistical And Graph Theoretical Algorithms, Sudhir Naswa

Doctoral Dissertations

Increased application of radiation in health and security sectors has raised concerns about its deleterious effects. Ionizing radiation (IR) less than 10cGys is considered low dose ionizing radiation (LDIR) by the National Research Committee to assess health risks from exposure to low levels of IR.

It is hard to extract the effects of mild stimulus such as LDIR on gene expression profiles using simple differential expression. We hypothesized that differential correlation instead would capture the effects of LDIR on mutual relationships between genes. We tested this hypothesis on expression profiles from five inbred strains of mice treated with LDIR. Whereas …

Health Care Informatics Support Of A Simulated Study, Zeinab Salari Far

Theses and Dissertations

The objective of this project is to assess the value of REDCap (Harris, 2009) by conducting a simulated breast cancer clinical trial and demonstration. REDCap is a free, secure, web-based application designed to support data capture for research studies. To assess REDCap's value, we conducted a simulation of a clinical trial study designed to compare the use of two new technologies for breast cancer diagnosis and treatment with current best practice breast cancer diagnosis and treatment. We call the trial, "Real-Time Operating Room BC Diagnostic Treatment (RORBCDT)". The RORBCDT clinical trial is designed to assess the value of a new …

A Systematic Framework For Radio Frequency Identification (Rfid) Hazard Mitigation In The Blood Transfusion Supply Chain From Donation To Distribution, Natalie Simone Rahming

Theses and Dissertations

The RFID Consortium is developing what will be the first FDA-approved use of radio frequency identification (RFID) technology to identify, track, manage, and monitor blood throughout the entire blood transfusion supply chain. The iTraceTM is an innovative technological system designed to optimize the procedures currently employed when tracing blood from the donor to the recipient. With all novel technologies it is essential to consider not only the advantages, but also the potential harms that may come about from using the system. The deployment of the iTraceTM consists of two phases: 1) Phase One - application of the iTraceTM from the …

A Study On The Function Of 14-3-3sigma In Regulating Cancer Energy Metabolism, Liem M. Phan, Liem M. Phan

Dissertations & Theses (Open Access)

Metabolic reprogramming has been shown to be a major cancer hallmark providing tumor cells with significant advantages for survival, proliferation, growth, metastasis and resistance against anti-cancer therapies. Glycolysis, glutaminolysis and mitochondrial biogenesis are among the most essential cancer metabolic alterations because these pathways provide cancer cells with not only energy but also crucial metabolites to support large-scale biosynthesis, rapid proliferation and tumorigenesis. In this study, we find that 14-3-3σ suppresses all these three metabolic processes by promoting the degradation of their main driver, c-Myc. In fact, 14-3-3s significantly enhances c-Myc poly-ubiquitination and subsequent degradation, reduces c-Myc transcriptional activity, and down-regulates …

User Taglines: Alternative Presentations Of Expertise And Interest In Social Media, Hemant Purohit, Alex Dow, Omar Alonso, Lei Duan, Kevin Haas

Kno.e.sis Publications

Web applications are increasingly showing recommended users from social media along with some descriptions, an attempt to show relevancy - why they are being shown. For example, Twitter search for a topical keyword shows expert twitterers on the side for 'whom to follow'. Google+ and Facebook also recommend users to follow or add to friend circle. Popular Internet newspaper- The Huffington Post shows Twitter influencers/ experts on the side of an article for authoritative relevant tweets. The state of the art shows user profile bios as summary for Twitter experts, but it has issues with length constraint imposed by user …

Are Twitter Users Equal In Predicting Elections? A Study Of User Groups In Predicting 2012 U.S. Republican Primaries, Lu Chen, Wenbo Wang, Amit P. Sheth

Kno.e.sis Publications

Existing studies on predicting election results are under the assumption that all the users should be treated equally. However, recent work [14] shows that social media users from different groups (e.g., “silent majority” vs. “vocal minority”) have significant differences in the generated content and tweeting behavior. The effect of these differences on predicting election results has not been exploited yet. In this paper, we study the spectrum of Twitter users who participate in the on-line discussion of 2012 U.S. Republican Presidential Primaries, and examine the predictive power of different user groups (e.g., highly engaged users vs. lowly engaged users, right-leaning …

The Ssn Ontology Of The W3c Semantic Sensor Network Incubator Group, Michael Compton, Payam Barnaghi, Luis Bermudez, Raul Garcia-Castro, Oscar Corcho, Simon Cox, John Graybeal, Manfred Hauswirth, Cory Andrew Henson, Arthur Herzog, Vincent Huang, Krzysztof Janowicz, W. David Kelsey, Danh Le Phuoc, Laurent Lefort, Myriam Leggieri, Holger Neuhaus, Andriy Nikolov, Kevin Page, Alexandre Passant, Amit P. Sheth, Kerry Taylor

Kno.e.sis Publications

The W3C Semantic Sensor Network Incubator group (the SSN-XG) produced an OWL 2 ontology to describe sensors and observations — the SSN ontology, available at http://purl.oclc.org/NET/ssnx/ssn. The SSN ontology can describe sensors in terms of capabilities, measurement processes, observations and deployments. This article describes the SSN ontology. It further gives an example and describes the use of the ontology in recent research projects.

B-Cell Epitope Prediction Through A Graph Model, Liang Zhao, Limsoon Wong, Lanyuan Lu, Steven C. H. Hoi, Jinyan Li

Research Collection School Of Computing and Information Systems

Prediction of B-cell epitopes from antigens is useful to understand the immune basis of antibody-antigen recognition, and is helpful in vaccine design and drug development. Tremendous efforts have been devoted to this long-studied problem, however, existing methods have at least two common limitations. One is that they only favor prediction of those epitopes with protrusive conformations, but show poor performance in dealing with planar epitopes. The other limit is that they predict all of the antigenic residues of an antigen as belonging to one single epitope even when multiple non-overlapping epitopes of an antigen exist.

Transcriptional Analysis Of Cervical Epithelial Cell Responses To Hiv-1, Andrew A. Block

School of Biological Sciences: Dissertations, Theses, and Student Research

Human Immunodeficiency Virus type 1 (HIV-1) infection causes a growing pandemic throughout the world, of which women comprise 51% of people who live with HIV-1, more than 60% in sub-Saharan Africa. HIV-1 infections of women are mainly acquired through female reproductive tract where cervical and vaginal epithelial cells are the first line of defense. Although HIV-1 does not directly infect epithelial cells, HIV-1 obligatorily interacts with and crosses over epithelial layer to infect susceptible target cells, mainly CD4+ T cells, in the lamina propria to initiate an infection. However, the mechanism and ramification of the interaction of HIV-1 and epithelial …

Two Different High Throughput Sequencing Approaches Identify Thousands Of De Novo Genomic Markers For The Genetically Depleted Bornean Elephant., Reeta Sharma, Benoit Goossens, Benoit Goossens, Célia Kun-Rodrigues, Tatiana Teixeira, Nurzhafarina Othman, Nurzhafarina Othman, Jason Q. Boone, Nathaniel K. Jue, Craig Obergfell, Rachel J. O'Neill, Lounès Chikhi, Lounès Chikhi, Lounès Chikhi

Nathaniel Jue

Demonstration: Dynamic Sensor Registration And Semantic Processing For Ad-Hoc Mobile Environments (Semmob), Pramod Anantharam, Gary Alan Smith, Josh Pschorr, Krishnaprasad Thirunarayan, Amit P. Sheth

Kno.e.sis Publications

SemMOB enables dynamic registration of sensors via mobile devices, search, and near real-time inference over sensor observations in ad-hoc mobile environments (e.g., fire fighting). We demonstrate SemMOB in the context of an emergency response use case that requires automatic and dynamic registrations of sensor devices and annotation of sensor observations, decoding of latitude-longitude information in terms of human sensible names, fusion and abstraction of sensor values using background knowledge, and their visualization using mash-up.

Using Social Influence To Predict Subscriber Churn, Derek Doran, Veena Mendiratta, Chitra Phadke, Dan Kushnir, Huseyin Uzunalioglu

Kno.e.sis Publications

The saturation of mobile phone markets has resulted in rising costs for operators to obtain new customers. These operators thus focus their energies on identifying users that will churn so they can be targeted for retention campaigns. Typical churn prediction algorithms identify churners based on service usage metrics, network performance indicators, and demographic information. Social and peer-influence to churn, however, is usually not considered. In this paper, we describe a new churn prediction algorithm that incorporates the influence churners spread to their social peers. Using data from a major service provider, we show that social influence improves churn prediction and …

Understanding User Triads On Facebook, Derek Doran, Alberta De La Rosa Algarin, Swapna S. Gokhale

Kno.e.sis Publications

Contemporary approaches that analyze user behavior on online social networks only consider interactions among dyads, which are pairs of directly connected users. A large body of sociological work, however, suggests that mutual connections among users can influence their activities, leading to differences between two- and three-way interactions. This paper explores the dynamics of triads among Facebook users based on the wall posts from the New Orleans regional network. Initially, each connection is categorized as a close friendship or an acquiantance, contingent on the number of wall posts exchanged. Subsequently, the impact of different types of connections comprising triads is examined …

How I Would Like Semantic Web To Be, For My Children., Raghava Mutharaju

Kno.e.sis Publications

Semantic Web, since its inception, has gone through lot of developments in its relatively nascent existence; right from people's perception, to the standards and to its adoption by the industry and more importantly by the scientific community. This impressive growth only seems to increase. In this paper, we project this growth to the next 10 years and highlight some of the facets on which Semantic Web could have a major impact on. We also present the challenges that Semantic Web and its community has to deal with in order to get there.