Digital Commons Network^™

The 4 X 4 Semantic Model: Exploiting Data, Functional, Non-Functional And Execution Semantics Across Business Process, Workflow, Partner Services And Middleware Services Tiers, Amit P. Sheth, Karthik Gomadam

Kno.e.sis Publications

Business processes in the global environment increasingly encompass multiple partners and complex, rapidly changing requirements. In this context it is critical that strategic business objectives align with and map accurately to systems that support flexible and dynamic business processes. To support the demanding requirements of global business processes, we propose a comprehensive, unifying 4 X 4 Semantic Model that uses Semantic Templates to link four tiers of implementation with four types of semantics. The four tiers are the Business Process Tier, the Workflow Enactment Tier, the Partner Services Tier, and the Middleware Services Tier. The four types of semantics are …

Semantic Sensor Web, Amit P. Sheth, Cory Henson, Krishnaprasad Thirunarayan

Kno.e.sis Publications

No abstract provided.

Capturing Workflow Event Data For Monitoring, Performance Analysis, And Management Of Scientific Workflows, Matthew Valerio, Satya S. Sahoo, Roger Barga, Jared Jackson

Kno.e.sis Publications

To effectively support real-time monitoring and performance analysis of scientific workflow execution, varying levels of event data must be captured and made available to interested parties. This paper discusses the creation of an ontology-aware workflow monitoring system for use in the Trident system which utilizes a distributed publish/subscribe event model. The implementation of the publish/subscribe system is discussed and performance results are presented.

Growing Fields Of Interest: Using An Expand And Reduce Strategy For Domain Model Extraction, Christopher Thomas, Pankaj Mehra, Roger Brooks, Amit P. Sheth

Kno.e.sis Publications

Domain hierarchies are widely used as models underlying information retrieval tasks. Formal ontologies and taxonomies enrich such hierarchies further with properties and relationships associated with concepts and categories but require manual effort; therefore they are costly to maintain, and often stale. Folksonomies and vocabularies lack rich category structure and are almost entirely devoid of properties and relationships. Classification and extraction require the coverage of vocabularies and the alterability of folksonomies and can largely benefit from category relationships and other properties. With Doozer, a program for building conceptual models of information domains, we want to bridge the gap between the vocabularies …

Detection Of Recurrent Copy Number Alterations In The Genome: A Probabilistic Approach, Oscar M. Rueda, Ramon Diaz-Uriarte

COBRA Preprint Series

Copy number variation (CNV) in genomic DNA is linked to a variety of human diseases (including cancer, HIV acquisition, autoimmune and neurodegenerative diseases), and array-based CGH (aCGH) is currently the main technology to locate CNVs. Several methods can analyze aCGH data at the single sample level, but disease-critical genes are more likely to be found in regions that are common or recurrent among samples. Unfortunately, defining recurrent CNV regions remains a challenge. Moreover, the heterogeneous nature of many diseases requires that we search for CNVs that affect only some subsets of the samples (without prior knowledge of which regions and …

Finding Recurrent Regions Of Copy Number Variation: A Review, Oscar M. Rueda, Ramon Diaz-Uriarte

COBRA Preprint Series

Copy number variation (CNV) in genomic DNA is linked to a variety of human diseases, and array-based CGH (aCGH) is currently the main technology to locate CNVs. Although many methods have been developed to analyze aCGH from a single array/subject, disease-critical genes are more likely to be found in regions that are common or recurrent among subjects. Unfortunately, finding recurrent CNV regions remains a challenge. We review existing methods for the identification of recurrent CNV regions. The working definition of ``common'' or ``recurrent'' region differs between methods, leading to approaches that use different types of input (discretized output from a …

Molecular Characterisation Of A Bovine-Like Rotavirus Detected From A Giraffe, Emily Mulherin, Jill Bryan, Marijke Beltman, Luke O'Grady, Eugene Pidgeon, Lucie Garon, Andrew Lloyd, John Bainbridge, Helen O'Shea, Paul Whyte, Séamus Fanning

Department of Biological Sciences Publications

Background

Rotavirus (RV), is a member of the Reoviridae family and an important etiological agent of acute viral gastroenteritis in the young. Rotaviruses have a wide host range infecting a broad range of animal species, however little is known about rotavirus infection in exotic animals. In this paper we report the first characterisation of a RV strain from a giraffe calf.

Results

This report describes the identification and detailed molecular characterisation of a rotavirus strain detected from a 14-day-old Giraffe (Giraffa camelopardalis), presenting with acute diarrhea. The RV strain detected from the giraffe was characterized molecularly as G10P[11]. …

The Strength Of Statistical Evidence For Composite Hypotheses With An Application To Multiple Comparisons, David R. Bickel

COBRA Preprint Series

The strength of the statistical evidence in a sample of data that favors one composite hypothesis over another may be quantified by the likelihood ratio using the parameter value consistent with each hypothesis that maximizes the likelihood function. Unlike the p-value and the Bayes factor, this measure of evidence is coherent in the sense that it cannot support a hypothesis over any hypothesis that it entails. Further, when comparing the hypothesis that the parameter lies outside a non-trivial interval to the hypotheses that it lies within the interval, the proposed measure of evidence almost always asymptotically favors the correct hypothesis …

Leading Firms As Knowledge Gatekeepers In A Networked Environment, Deogratias Harorimana Mr

Dr Deogratias Harorimana

This chapter introduces the role of the knowledge gatekeeper as a mechanism by which knowledge is created and transferred in a networked environment. Knowledge creation and transfer are essential for building a knowledge based economy. The chapter considers obstacles that inhibit this process and argues that leading firms create a shared socio-cultural context that enables the condivision of tacit meanings and codification of knowledge. Leading firms act as gatekeepers of knowledge through the creation of shared virtual platforms. There will be a leading firm that connects several networks of clients and suppliers may not interact directly with one another, but …

A Network-Constrained Empirical Bayes Method For Analysis Of Genomic Data, Caiyan Li, Zhi Wei, Hongzhe Li

UPenn Biostatistics Working Papers

Empirical Bayes methods are widely used in the analysis of microarray gene expression data in order to identify the differentially expressed genes or genes that are associated with other general phenotypes. Available methods often assume that genes are independent. However, genes are expected to function interactively and to form molecular modules to affect the phenotypes. In order to account for regulatory dependency among genes, we propose in this paper a network-constrained empirical Bayes method for analyzing genomic data in the framework of general linear models, where the dependency of genes is modeled by a discrete Markov random field model defined …

Relationship Web: Trailblazing, Analytics And Computing For Human Experience, Amit P. Sheth

Kno.e.sis Publications

This panel presentation was give at the 27th International Conference on Conceptual Modeling (ER 2008), Barcelona, Spain, October 20-23, 2008.

Integrated Mining Of Feature Spaces For Bioinformatics Domain Discovery, Pradeep Chowriappa

Doctoral Dissertations

One of the major challenges in the field of bioinformatics is the elucidation of protein folding for the functional annotation of proteins. The factors that govern protein folding include the chemical, physical, and environmental conditions of the protein's surroundings, which can be measured and exploited for computational discovery purposes. These conditions enable the protein to transform from a sequence of amino acids to a globular three-dimensional structure. Information concerning the folded state of a protein has significant potential to explain biochemical pathways and their involvement in disorders and diseases. This information impacts the ways in which genetic diseases are characterized …

Adapting Ranking Functions To User Preference, Keke Chen, Ya Zhang, Zhaohui Zheng, Hongyuan Zha, Gordon Sun

Kno.e.sis Publications

Learning to rank has become a popular method for web search ranking. Traditionally, expert-judged examples are the major training resource for machine learned web ranking, which is expensive to get for training a satisfactory ranking function. The demands for generating specific web search ranking functions tailored for different domains, such as ranking functions for different regions, have aggravated this problem. Recently, a few methods have been proposed to extract training examples from user clickthrough log. Due to the low cost of getting user preference data, it is attractive to combine these examples in training ranking functions. However, because of the …

An Ontology-Driven Semantic Mash-Up Of Gene And Biological Pathway Information: Application To The Domain Of Nicotine Dependence, Satya S. Sahoo, Olivier Bodenreider, Joni L. Rutter, Karen J. Skinner, Amit P. Sheth

Kno.e.sis Publications

Objectives: This paper illustrates how Semantic Web technologies (especially RDF, OWL, and SPARQL) can support information integration and make it easy to create semantic mashups (semantically integrated resources). In the context of understanding the genetic basis of nicotine dependence, we integrate gene and pathway information and show how three complex biological queries can be answered by the integrated knowledge base.

Methods: We use an ontology-driven approach to integrate two gene resources (Entrez Gene and HomoloGene) and three pathway resources (KEGG, Reactome and BioCyc), for five organisms, including humans. We created the Entrez Knowledge Model (EKoM), an information model in OWL …

Description Logic Reasoning With Decision Diagrams: Compiling Shiq To Disjunctive Datalog, Sebastian Rudolph

Kno.e.sis Publications

We propose a novel method for reasoning in the description logic SHIQ. After a satisfiability preserving transformation from SHIQ to the description logic ALCIb, the obtained ALCIb Tbox T is converted into an ordered binary decision diagram (OBDD) which represents a canonical model for T. This OBDD is turned into a disjunctive datalog program that can be used for Abox reasoning. The algorithm is worst-case optimal w.r.t. data complexity, and admits easy extensions with DL-safe rules and ground conjunctive queries.

Word Sense Disambiguation In Biomedical Ontologies With Term Co-Occurrence Analysis And Document Clustering, Bill Andreopoulos, Dimitra Alexopoulou, Michael Schroeder

Faculty Publications, Computer Science

With more and more genomes being sequenced, a lot of effort is devoted to their annotation with terms from controlled vocabularies such as the GeneOntology. Manual annotation based on relevant literature is tedious, but automation of this process is difficult. One particularly challenging problem is word sense disambiguation. Terms such as |development| can refer to developmental biology or to the more general sense. Here, we present two approaches to address this problem by using term co-occurrences and document clustering. To evaluate our method we defined a corpus of 331 documents on development and developmental biology. Term co-occurrence analysis achieves an …

Word Sense Disambiguation In Biomedical Ontologies With Term Co-Occurrence Analysis And Document Clustering, Bill Andreopoulos, Dimitra Alexopoulou, Michael Schroeder

William B. Andreopoulos

Segmenting Brain Tumors Using Pseudo-Conditional Random Fields, Chi-Hoon Lee, Shaojun Wang, Albert Murtha, Matthew R.G. Brown, Russell Greiner

Kno.e.sis Publications

Locating Brain tumor segmentation within MR (magnetic resonance) images is integral to the treatment of brain cancer. This segmentation task requires classifying each voxel as either tumor or non-tumor, based on a description of that voxel. Unfortunately, standard classifiers, such as Logistic Regression (LR) and Support Vector Machines (SVM), typically have limited accuracy as they treat voxels as independent and identically distributed (iid). Approaches based on random fields, which are able to incorporate spatial constraints, have recently been applied to brain tumor segmentation with notable performance improvement over iid classifiers. However, previous random field systems involved computationally intractable …

A Faceted Classification Based Approach To Search And Rank Web Apis, Karthik Gomadam, Ajith Harshana Ranabahu, Meenakshi Nagarajan, Amit P. Sheth, Kunal Verma

Kno.e.sis Publications

Web application hybrids, popularly known as mashups, are created by integrating services on the Web using their APIs. Support for finding an API is currently provided by generic search engines or domain specific solutions such as Google and ProgrammableWeb. Shortcomings of both these solutions in terms of and reliance on user tags make the task of identifying an API challenging. Since these APIs are described in HTML documents, it is essential to look beyond the boundaries of current approaches to Web service discovery that rely on formal descriptions. In this work, we present a faceted approach to searching and ranking …

Semantics Enhanced Services: Meteor-S, Sawsdl And Sa-Rest, Amit P. Sheth, Karthik Gomadam, Ajith Harshana Ranabahu

Kno.e.sis Publications

Services Research Lab at the Knoesis center and the LSDIS lab at University of Georgia have played a significant role in advancing the state of research in the areas of workflow management, semantic Web services and service oriented computing. Starting with the METEOR workflow management system in the 90's, researchers have addressed key issues in the area of semantic Web services and more recently, in the domain of RESTful services and Web 2.0. In this article, we present a brief discussion on the various contributions of METEOR-S including SAWSDL, publication and discovery of semantic Web services, data mediation, dynamic configuration …

A Review Of Physiological Simulation Models Of Intracranial Pressure Dynamics, Wayne W. Wakeland, Brahm Goldstein

Systems Science Faculty Publications and Presentations

This paper reviews the literature regarding the development, testing, and application of physiology-based computer simulation models of intracranial pressure dynamics. Detailed comparative information is provided in tabular format about the model variables and logic, any data collected, model testing and validation methods, and model results. Several syntheses are given that summarize the research carried out by influential research teams and researchers, review important findings, and discuss the methods employed, limitations, and opportunities for further research.

Challenges Of Creating A Knowledge-Based Society: Education & Research For India & Gujarat, Amit P. Sheth

Kno.e.sis Publications

No abstract provided.

Pubmed Central Deposit And Author Rights: Pubmed Central Deposit And Author Rights, Ben Grillot

NIH PubMed Central Depositors' Information

Authors and publishers have long negotiated the ownership of copyright in scholarly works. However, with the rise of electronic publishing and a growing trend towards open and public access models, traditional authorpublisher agreements are changing. One of many forces bringing about this change is the National Institutes of Health’s (NIH) recently revised Public Access Policy, requiring authors of NIH-funded articles to submit their works to PubMed Central. As a result of this policy, authors of funded works are looking closely at their publication agreements and scientific, technical, and medical journal publishers are re-examining their author agreements to accommodate the author’s …

Novel Implementation Of Conditional Co-Regulation By Graph Theory To Derive Co-Expressed Genes From Microarray Data, Arun Rawat, Georg J. Seifert, Youping Deng

Faculty Publications

Background

Most existing transcriptional databases like Comprehensive Systems-Biology Database (CSB.DB) and Arabidopsis Microarray Database and Analysis Toolbox (GENEVESTIGATOR) help to seek a shared biological role (similar pathways and biosynthetic cycles) based on correlation. These utilize conventional methods like Pearson correlation and Spearman rank correlation to calculate correlation among genes. However, not all are genes expressed in all the conditions and this leads to their exclusion in these transcriptional databases that consist of experiments performed in varied conditions. This leads to incomplete studies of co-regulation among groups of genes that might be linked to the same or related biosynthetic pathway.

Results …

Mtap: The Motif Tool Assessment Platform, Daniel Quest, Kathryn Dempsey, Mohammad Shafiullah, Dhundy Raj Bastola, Hesham Ali

Information Systems and Quantitative Analysis Faculty Publications

Background: In recent years, substantial effort has been applied to de novo regulatory motif discovery. At this time, more than 150 software tools exist to detect regulatory binding sites given a set of genomic sequences. As the number of software packages increases, it becomes more important to identify the tools with the best performance characteristics for specific problem domains. Identifying the correct tool is difficult because of the great variability in motif detection software. Consequently, many labs spend considerable effort testing methods to find one that works well in their problem of interest.

Results: In this work, we propose a …

Connectionist Model Generation: A First-Order Approach, Sebastian Bader, Pascal Hitzler, Steffen Holldobler

Computer Science and Engineering Faculty Publications

Knowledge-based artificial neural networks have been applied quite successfully to propositional knowledge representation and reasoning tasks. However, as soon as these tasks are extended to structured objects and structure-sensitive processes as expressed e.g., by means of first-order predicate logic, it is not obvious at all what neural-symbolic systems would look like such that they are truly connectionist, are able to learn, and allow for a declarative reading and logical reasoning at the same time. The core method aims at such an integration. It is a method for connectionist model generation using recurrent networks with feed-forward core. We show in this …

Knowledge-Based Analysis Of Genomic Expression Data By Using Different Machine Learning Algorithms For The Purpose Of Diagnostic, Prognostic Or Therapeutic Application, Venkata Jagan Mohan Thodima

Dissertations

With more and more biological information generated, the most pressing task of bioinformatics has become to analyze and interpret various types of data, including nucleotide and amino acid sequences, protein structures, gene expression profiling and so on. In this dissertation, we apply the data mining techniques of feature generation, feature selection, and feature integration with learning algorithms to tackle the problems of disease phenotype classification, clinical outcome and patient survival prediction from gene expression profiles.

We analyzed the effect of batch noise in microarray data on the performance of classification. Batchmatch, a batch adjusting algorithm based on double scaling method …

Applications Of Voting Theory To Information Mashups, Alfredo Alba, Varun Bhagwan, Julia Grace, Daniel Gruhl, Kevin Haas, Meenakshi Nagarajan, Jan Pieper, Christine Robson, Nachiketa Sahoo

Kno.e.sis Publications

Blogs, discussion forums and social networking sites are an excellent source for people's opinions on a wide range of topics. We examine the application of voting theory to "information mashups" - the combining and summarizing of data from the multitude of often-conflicting sources. This paper presents an information mashup in the music domain: a Top 10 artist chart based on user comments and listening behavior from several Web communities. We consider different voting systems as algorithms to combine opinions from multiple sources and evaluate their effectiveness using social welfare functions. Different voting schemes are found to work better in some …

Text Analytics For Semantic Computing - The Good, The Bad And The Ugly, Meenakshi Nagarajan, Cartic Ramakrishnan, Amit P. Sheth

Kno.e.sis Publications

This tutorial was give at the Second IEEE International Conference on Semantic Computing Santa Clara, CA, USA - August 4-7, 2008.

Tcruzikb: Enabling Complex Queries For Genomic Data Exploration, Pablo N. Mendes, Bobby Mcknight, Amit P. Sheth, Jessica C. Kissinger

Kno.e.sis Publications

We developed a novel analytical environment to aid in the examination of the extensive amount of interconnected data available for genome projects. Our focus is to enable flexibility and abstraction from implementation details, while retaining the expressivity required for post-genomic research. To achieve this goal, we associated genomics data to ontologies and implemented a query formulation and execution environment with added visualization capabilities. We use ontology schemas to guide the user through the process of building complex queries in a flexible Web interface. Queries are serialized in SPARQL and sent to servers via Ajax. A component for visualization of the …