A specialized learner for inferring structured cis-regulatory modules

BACKGROUND: The process of transcription is controlled by systems of transcription factors, which bind to specific patterns of binding sites in the transcriptional control regions of genes, called cis-regulatory modules (CRMs). We present an expressive and easily comprehensible CRM representation which is capable of capturing several aspects of a CRM's structure and distinguishing between DNA sequences which do or do not contain it. We also present a learning algorithm tailored for this domain, and a novel method to avoid overfitting by controlling the expressivity of the model. RESULTS: We are able to find statistically significant CRMs more often then a current state-of-the-art approach on the same data sets. We also show experimentally that each aspect of our expressive CRM model space makes a positive contribution to the learned models on yeast and fly data. CONCLUSION: Structural aspects are an important part of CRMs, both in terms of interpreting them biologically and learning them accurately. Source code for our algorithm is available at

A Novel Approach to Ontology Management

The term ontology is defined as the explicit specification of a conceptualization. While much of the prior research has focused on technical aspects of ontology management, little attention has been paid to the investigation of issues that limit the widespread use of ontologies and the evaluation of the effectiveness of ontologies in improving task performance. This dissertation addresses this void through the development of approaches to ontology creation, refinement, and evaluation. This study follows a multi-paper model focusing on ontology creation, refinement, and its evaluation. The first study develops and evaluates a method for ontology creation using knowledge available on the Web. The second study develops a methodology for ontology refinement through pruning and empirically evaluates the effectiveness of this method. The third study investigates the impact of an ontology in use case modeling, which is a complex, knowledge intensive organizational task in the context of IS development. The three studies follow the design science research approach, and each builds and evaluates IT artifacts. These studies contribute to knowledge by developing solutions to three important issues in the effective development and use of ontologies

Semantic discovery and reuse of business process patterns

Patterns currently play an important role in modern information systems (IS) development and their use has mainly been restricted to the design and implementation phases of the development lifecycle. Given the increasing significance of business modelling in IS development, patterns have the potential of providing a viable solution for promoting reusability of recurrent generalized models in the very early stages of development. As a statement of research-in-progress this paper focuses on business process patterns and proposes an initial methodological framework for the discovery and reuse of business process patterns within the IS development lifecycle. The framework borrows ideas from the domain engineering literature and proposes the use of semantics to drive both the discovery of patterns as well as their reuse

GVSU Undergraduate and Graduate Catalog, 2019-2020

Grand Valley State University 2019-2020 undergraduate and/or graduate course catalog published annually to provide students with information and guidance for enrollment.https://scholarworks.gvsu.edu/course_catalogs/1094/thumbnail.jp