Bioinformatics Commons^™

Bayesian Analysis Of Cell-Cycle Gene Expression Data, Chuan Zhou, Jon Wakefield, Linda Breeden

UW Biostatistics Working Paper Series

The study of the cell-cycle is important in order to aid in our understanding of the basic mechanisms of life, yet progress has been slow due to the complexity of the process and our lack of ability to study it at high resolution. Recent advances in microarray technology have enabled scientists to study the gene expression at the genome-scale with a manageable cost, and there has been an increasing effort to identify cell-cycle regulated genes. In this chapter, we discuss the analysis of cell-cycle gene expression data, focusing on a model-based Bayesian approaches. The majority of the models we describe …

Openws-Transaction: Enabling Reliable Web Service Transactions, Ivan Vasquez, John A. Miller, Kunal Verma, Amit P. Sheth

Kno.e.sis Publications

OpenWS-Transaction is an open source middleware that enables Web services to participate in a distributed transaction as prescribed by the WS-Coordination and WS-Transaction set of specifications. Central to the framework are the Coordinator and Participant entities, which can be integrated into existing services by introducing minimal changes to application code. OpenWS-Transaction allows transaction members to recover their original state in case of operational failure by leveraging techniques in logical logging and recovery at the application level. Depending on transaction style, system recovery may involve restoring key application variables and replaying uncommitted database activity. Transactions are assumed to be defined in …

Demonstrating Dynamic Configuration And Execution Of Web Processes, Karthik Gomadam, Kunal Verma, Amit P. Sheth, John A. Miller

Kno.e.sis Publications

Web processes are next generation workflows on the web, created using Web services. In this paper we demonstrate the METEOR-S Configuration and Execution Environment (MCEE) system. It will illustrate the capabilities of the system to a) Discover partners b) Optimize partner selection using constraint analysis, c) Perform interaction protocol and data mediation. A graphical execution monitor to monitor the various phases of execution will be used to demonstrate various aspects of the system.

Discovering Informative Connection Subgraphs In Multi-Relational Graphs, Cartic Ramakrishnan, William Milnor, Matthew Perry, Amit P. Sheth

Kno.e.sis Publications

Discovering patterns in graphs has long been an area of interest. In most approaches to such pattern discovery either quantitative anomalies, frequency of substructure or maximum flow is used to measure the interestingness of a pattern. In this paper we introduce heuristics that guide a subgraph discovery algorithm away from banal paths towards more "informative" ones. Given an RDF graph a user might pose a question of the form: "What are the most relevant ways in which entity X is related to entity Y?" the response to which is a subgraph connecting X to Y. We use our heuristics to …

Optimal Feature Selection For Nearest Centroid Classifiers, With Applications To Gene Expression Microarrays, Alan R. Dabney, John D. Storey

UW Biostatistics Working Paper Series

Nearest centroid classifiers have recently been successfully employed in high-dimensional applications. A necessary step when building a classifier for high-dimensional data is feature selection. Feature selection is typically carried out by computing univariate statistics for each feature individually, without consideration for how a subset of features performs as a whole. For subsets of a given size, we characterize the optimal choice of features, corresponding to those yielding the smallest misclassification rate. Furthermore, we propose an algorithm for estimating this optimal subset in practice. Finally, we investigate the applicability of shrinkage ideas to nearest centroid classifiers. We use gene-expression microarrays for …

A New Approach To Intensity-Dependent Normalization Of Two-Channel Microarrays, Alan R. Dabney, John D. Storey

UW Biostatistics Working Paper Series

A two-channel microarray measures the relative expression levels of thousands of genes from a pair of biological samples. In order to reliably compare gene expression levels between and within arrays, it is necessary to remove systematic errors that distort the biological signal of interest. The standard for accomplishing this is smoothing "MA-plots" to remove intensity-dependent dye bias and array-specific effects. However, MA methods require strong assumptions. We review these assumptions and derive several practical scenarios in which they fail. The "dye-swap" normalization method has been much less frequently used because it requires two arrays per pair of samples. We show …

Ontoqa: Metric-Based Ontology Quality Analysis, Samir Tartir, I. Budak Arpinar, Michael Moore, Amit P. Sheth, Boanerges Aleman-Meza

Kno.e.sis Publications

As the Semantic Web gains importance for sharing knowledge on the Internet this has lead to the development and publishing of many ontologies in different domains. When trying to reuse existing ontologies into their applications, users are faced with the problem of determining if an ontology is suitable for their needs. In this paper, we introduce OntoQA, an approach that analyzes ontology schemas and their populations (i.e. knowledgebases) and describes them through a well defined set of metrics. These metrics can highlight key characteristics of an ontology schema as well as its population and enable users to make an informed …

An Introduction To Low-Level Analysis Methods Of Dna Microarray Data, Wolfgang Huber, Anja Von Heydebreck, Martin Vingron

Bioconductor Project Working Papers

This article gives an overview over the methods used in the low--level analysis of gene expression data generated using DNA microarrays. This type of experiment allows to determine relative levels of nucleic acid abundance in a set of tissues or cell populations for thousands of transcripts or loci simultaneously. Careful statistical design and analysis are essential to improve the efficiency and reliability of microarray experiments throughout the data acquisition and analysis process. This includes the design of probes, the experimental design, the image analysis of microarray scanned images, the normalization of fluorescence intensities, the assessment of the quality of microarray …

Semantics For Scientific Experiments And The Web: The Implicit, The Formal And The Powerful, Amit P. Sheth

Kno.e.sis Publications

No abstract provided.

Modeling Fuzzy Rules With Description Logics, Sudhir Agarwal, Pascal Hitzler

Computer Science and Engineering Faculty Publications

In real application scenarios, input data and knowledge is often vague. Likewise, it is often the case that exact reasoning over data is impossible due to complex dependencies between input data and target outputs. For practical applications, however, good approximations often suffice, and efficient calculation of an approximate answer is often preferable over complex processing which may take a long time to come up with an exact answer. Fuzzy logic supports both features by providing fuzzy membership functions and fuzzy IF-THEN rule bases. In this paper, we show how fuzzy membership functions and fuzzy rules can be modeled by means …

Dlp Isn't So Bad After All, Peter Haase, Markus Krotzsch, York Sure, Rudi Studer, Pascal Hitzler

Computer Science and Engineering Faculty Publications

We discuss some of the recent controversies concerning the DLP fragment of OWL. We argue that it is a meaningful fragment and can serve as a basic interoperability layer between OWL and logic programming-based ontology languages.

Optimal Adaptation In Autonomic Web Processes With Inter-Service Dependencies, Kunal Verma, Prashant Doshi, Karthik Gomadam, John A. Miller, Amit P. Sheth

Kno.e.sis Publications

We present methods for optimally adapting Web processes to exogenous events while preserving inter-service dependencies. For example, in a supply chain process, orders placed by the manufacturer may get delayed in arriving. In response to this event, the manufacturer has the choice of either waiting out the delay or changing the supplier.

A Method Of Precise Mrna/Dna Homology-Based Gene Structure Prediction, Alexander Churbanov, Mark Pauley, Daniel Quest, Hesham Ali

Information Systems and Quantitative Analysis Faculty Publications

Background: Accurate and automatic gene finding and structural prediction is a common problem in bioinformatics, and applications need to be capable of handling non-canonical splice sites, microexons and partial gene structure predictions that span across several genomic clones.

Results: We present a mRNA/DNA homology based gene structure prediction tool, GIGOgene. We use a new affine gap penalty splice-enhanced global alignment algorithm running in linear memory for a high quality annotation of splice sites. Our tool includes a novel algorithm to assemble partial gene structure predictions using interval graphs. GIGOgene exhibited a sensitivity of 99.08% and a specificity of 99.98% on …

Computing For Human Experience And Wellness, Amit P. Sheth

Kno.e.sis Publications

No abstract provided.

Work In Progress: The Wsu Model For Engineering Mathematics Education, Nathan W. Klingbeil, Richard Mercer, Kuldip S. Rattan, Michael L. Raymer, David B. Reynolds

Kno.e.sis Publications

This paper summarizes progress to date on the WSU model for engineering mathematics education, an NSF funded curriculum reform initiative at Wright State University. The WSU model seeks to increase student retention, motivation and success in engineering through application-driven, just-in-time engineering math instruction. The WSU approach involves the development of a novel freshman-level engineering mathematics course EGR 101, as well as a large-scale restructuring of the engineering curriculum. By removing traditional math prerequisites and moving core engineering courses earlier in the program, the WSU model shifts the traditional emphasis on math prerequisite requirements to an emphasis on engineering motivation for …

Evolutionary Conservation Suggests A Regulatory Function Of Aug Triplets In 50 -Utrs Of Eukaryotic Genes, Alexander Churbanov, Igor B. Rogozin, Vladimir N. Babenko, Hesham Ali, Eugene V. Koonin

Information Systems and Quantitative Analysis Faculty Publications

By comparing sequences of human, mouse and rat orthologous genes, we show that in 50 -untranslated regions (50 -UTRs) of mammalian cDNAs but not in 30 - UTRs or coding sequences, AUG is conserved to a significantly greater extent than any of the other 63 nt triplets. This effect is likely to reflect, primarily, bona fide evolutionary conservation, rather than cDNA annotation artifacts, because the excess of conserved upstream AUGs (uAUGs) is seen in 50 -UTRs containing stop codons in-frame with the start AUG and many of the conserved AUGs are found in different frames, consistent with the location in …

Simultaneous And Exact Interval Estimates For The Contrast Of Two Groups Based On An Extremely High Dimensional Response Variable: Application To Mass Spec Data Analysis, Yuhyun Park, Sean R. Downing, Cheng Li Dr., William C. Hahn, Philip W. Kantoff, L. J. Wei

Harvard University Biostatistics Working Paper Series

No abstract provided.

The Optimal Discovery Procedure: A New Approach To Simultaneous Significance Testing, John D. Storey

UW Biostatistics Working Paper Series

Significance testing is one of the main objectives of statistics. The Neyman-Pearson lemma provides a simple rule for optimally testing a single hypothesis when the null and alternative distributions are known. This result has played a major role in the development of significance testing strategies that are used in practice. Most of the work extending single testing strategies to multiple tests has focused on formulating and estimating new types of significance measures, such as the false discovery rate. These methods tend to be based on p-values that are calculated from each test individually, ignoring information from the other tests. As …

The Optimal Discovery Procedure For Large-Scale Significance Testing, With Applications To Comparative Microarray Experiments, John D. Storey, James Y. Dai, Jeffrey T. Leek

UW Biostatistics Working Paper Series

As much of the focus of genetics and molecular biology has shifted toward the systems level, it has become increasingly important to accurately extract biologically relevant signal from thousands of related measurements. The common property among these high-dimensional biological studies is that the measured features have a rich and largely unknown underlying structure. One example of much recent interest is identifying differentially expressed genes in comparative microarray experiments. We propose a new approach aimed at optimally performing many hypothesis tests in a high-dimensional study. This approach estimates the Optimal Discovery Procedure (ODP), which has recently been introduced and theoretically shown …

Ga-Facilitated Knn Classifier Optimization With Varying Similarity Measures, Michael R. Peterson, Travis E. Doom, Michael L. Raymer

Kno.e.sis Publications

Genetic algorithms are powerful tools for k-nearest neighbors classifier optimization. While traditional knn classification techniques typically employ Euclidian distance to assess pattern similarity, other measures may also be utilized. Previous research demonstrates that GAs can improve predictive accuracy by searching for optimal feature weights and offsets for a cosine similarity-based knn classifier. GA-selected weights determine the classification relevance of each feature, while offsets provide alternative points of reference when assessing angular similarity. Such optimized classifiers perform competitively with other contemporary classification techniques. This paper explores the effectiveness of GA weight and offset optimization for knowledge discovery using knn classifiers with …

Charge-Switch Nucleotides, John G. K. Williams, Gregory R. Bashford, Jiyan Chen, Dan Draney, Nara Narayanan, Bambi L. Reynolds, Pamela Sheaff

Biomedical Imaging and Biosignal Analysis Laboratory

The present invention provides compounds, methods and systems for sequencing nucleic acid using single molecule detection. Using labeled NPs that exhibit charge-switching behavior, single-molecule DNA sequencing in a microchannel sorting system is realized. In operation, sequencing products are detected enabling real-time sequencing as successive detectable moieties flow through a detection channel. By electrically sorting charged molecules, the cleaved product molecules are detected in isolation Without interference from unincorporated NPs and Without illuminating the polymerase-DNA complex.

Analysis Of Affymetrix Genechip Data Using Amplified Rna, Leslie Cope, Scott M. Hartman, Hinrich W.H. Gohlmann, Jay P. Tiesman, Rafael A. Irizarry

Johns Hopkins University, Dept. of Biostatistics Working Papers

The standard method of target synthesis for hybridization to Affymetrix GeneChip® expression microarrays requires a relatively large amount of input total RNA (1-15 micrograms). When small biological samples are collected by microdissection or other methods, amplification techniques are required to provide sufficient target for hybridization to expression arrays. One amplification technique used is to perform two successive rounds of T7-based in vitro transcription. However, the use of random primers required to re-generate cDNA from the first round transcription reaction results in shortened copies of the cDNA, and ultimately the cRNA, transcripts from which the 5' end is missing. In this …

Extracting Reduced Logic Programs From Artificial Neural Networks, Jens Lehmann, Sebastian Bader, Pascal Hitzler

Computer Science and Engineering Faculty Publications

Artificial neural networks can be trained to perform excellently in many application areas. While they can learn from raw data to solve sophisticated recognition and analysis problems, the acquired knowledge remains hidden within the network architecture and is not readily accessible for analysis or further use: Trained networks are black boxes. Recent research efforts therefore investigate the possibility to extract symbolic knowledge from trained networks, in order to analyze, validate, and reuse the structural insights gained implicitly during the training process. In this paper, we will study how knowledge in form of propositional logic programs can be obtained in such …

Integrating First-Order Logic Programs And Connectionist Systems - A Constructive Approach, Sebastian Bader, Andreas Witzel, Pascal Hitzler

Computer Science and Engineering Faculty Publications

Significant advances have recently been made concerning the integration of symbolic knowledge representation with artificial neural networks (also called connectionist systems). However, while the integration with propositional paradigms has resulted in applicable systems, the case of first-order knowledge representation has so far hardly proceeded beyond theoretical studies which prove the existence of connectionist systems for approximating first-order logic programs up to any chosen precision. Advances were hindered severely by the lack of concrete algorithms for obtaining the approximating networks which were known to exist: the corresponding proofs are not constructive in that they do not yield concrete methods for building …

Ontology Learning As A Use-Case For Neural-Symbolic Integration, Pascal Hitzler, Sebastian Bader, Artur Garcez

Computer Science and Engineering Faculty Publications

We argue that the field of neural-symbolic integration is in need of identifying application scenarios for guiding further research. We furthermore argue that ontology learning - as occurring in the context of semantic technologies - provides such an application scenario with potential for success and high impact on neural-symbolic integration.

Enterprise Applications Of Semantic Web: The Sweet Spot Of Risk And Compliance, Amit P. Sheth

Kno.e.sis Publications

Semantic Web is in the transition from vision and research to reality. In this early state, it is important to study the technical capabilities in the context of real-world applications, and how applications built using the Semantic Web technology meet the real market needs. Beyond push from research, it is the market pull and the ability of the technology to meet real business needs that is a key to ultimate success of any technology. In this paper, we discuss the market of Risk and Compliance which presents unique market opportunity combined with challenging technical requirements. We discuss how the Semantic …

Peer-To-Peer Discovery Of Semantic Associations, Matthew Perry, Maciej Janik, Cartic Ramakrishnan, Conrad Ibanez, I. Budak Arpinar, Amit P. Sheth

Kno.e.sis Publications

The Semantic Web vision promises an extension of the current Web in which all data is annotated with machine understandable metadata. The relationship-centric nature of this data has led to the definition of Semantic Associations, which are complex relationships between resources. Semantic Associations attempt to answer queries of the form “how are resource A and resource B related?” Knowing how two entities are related is a crucial question in knowledge discovery applications. Much the same way humans collaborate and interact to form new knowledge, discovery of Semantic Associations across repositories on a peer-to-peer network can allow peers to share their …

A Semantic Template Based Designer For Semantic Web Processes, Ranjit Mulye, John A. Miller, Kunal Verma, Karthik Gomadam, Amit P. Sheth

Kno.e.sis Publications

The growing popularity of service oriented computing based on Web services standards is creating a need for paradigms to represent and design business processes. Significant work has been done in the representation aspects with regards to WSBPEL. However, design and modeling of business processes is still an open issue. In this paper, we present a novel designer for business processes, which allows for intuitive modeling of Web processes, as well as using a template based approach for semi-automatically integrating partners either at design time or at deployment time. This work has been done as part of the METEOR-S project, which …

On Embedding Machine-Processable Semantics Into Documents, Krishnaprasad Thirunarayan

Kno.e.sis Publications

Most Web and legacy paper-based documents are available in human comprehensible text form, not readily accessible to or understood by computer programs. Here, we investigate an approach to amalgamate XML technology with programming languages for representational purposes that can enhance traceability, thereby facilitating semiautomatic extraction and update. Specifically, we propose a modular technique to embed machine-processable semantics into a text document with tabular data via annotations, resulting sometimes in ill-formed XML fragments, and evaluate this technique vis a vis document querying, manipulation, and integration. The ultimate aim is to be able to author and extract human-readable and machine-comprehensible parts of …

Faster Owl Using Split Programs, Denny Vrandecic, Pascal Hitzler

Computer Science and Engineering Faculty Publications

Knowledge representation and reasoning on the Semantic Web is done by means of ontologies. While the quest for suitable ontology languages is still ongoing, OWL [5] has been established as a core standard. It comes in three flavours, as OWL Full, OWL DL and OWL Lite, where OWL Full contains OWL DL, which in turn contains OWL Lite. The latter two coincide semantically with certain description logics and can thus be considered fragments of first-order predicate logic.