Applying Machine Learning Methods to Suggest Network Involvement and Functionality of Genes in Saccharomyces cerevisiae

Elucidating genetic networks provides the foundation for the development of new treatments or cures for diseased pathways, and determining novel gene functionality is critical for bringing a better understanding on how an organism functions as a whole. In this dissertation, I developed a methodology that correctly locates genes that may be involved in genetic networks with a given gene based on its location over 50% of the time or based on its description over 43% of the time. I also developed a methodology that makes it easier to predict how a gene product behaves in a cellular context by suggesting the correct Gene Ontology term over 80% of the time. The designed software provides researchers with a way to focus their search for coregulated genes which will lead to better microarray chip design and limits the list of possible functions of a gene product. This ultimately saves the researcher time and money

Classifying genes to the correct Gene Ontology Slim term in Saccharomyces cerevisiae using neighbouring genes with classification learning

Article discussing research on classifying genes to the correct gene ontology slim term in Saccharomyces cerevisiae using neighbouring genes with classification learning

Bioinformatics process management: information flow via a computational journal

This paper presents the Bioinformatics Computational Journal (BCJ), a framework for conducting and managing computational experiments in bioinformatics and computational biology. These experiments often involve series of computations, data searches, filters, and annotations which can benefit from a structured environment. Systems to manage computational experiments exist, ranging from libraries with standard data models to elaborate schemes to chain together input and output between applications. Yet, although such frameworks are available, their use is not widespread–ad hoc scripts are often required to bind applications together. The BCJ explores another solution to this problem through a computer based environment suitable for on-site use, which builds on the traditional laboratory notebook paradigm. It provides an intuitive, extensible paradigm designed for expressive composition of applications. Extensive features facilitate sharing data, computational methods, and entire experiments. By focusing on the bioinformatics and computational biology domain, the scope of the computational framework was narrowed, permitting us to implement a capable set of features for this domain. This report discusses the features determined critical by our system and other projects, along with design issues. We illustrate the use of our implementation of the BCJ on two domain-specific examples

The Implementation of Douglas Biber’s Multi-Dimensional Approach to Text Classification

Color poster with text.The goal for this research project is to implement the text classification algorithm described by Douglas Biber in Variations across speech and writing. By creating this program, I will have created an automated tool to be used in and simply future research of text classification, allowing for the study of larger text samples. Biber’s algorithm identifies seven factors on which to classify text based on the patterns of co-occurrence between linguistic features. The program will read files and compute the factor scores for each text file, enabling the factor scores to be computed quickly and consistently. Once the program is created and accurately generates the factor scores, the resulting factor scores will be able to be used to search for correlations between text genre and other factors, for example how different groups of people might respond differently to various genres of text. This program will be a tool that can be used for many future research projects relating to text genres.University of Wisconsin--Eau Claire Office of Research and Sponsored Program

Analyzing Pronoun Usage in Yelp Reviews

Color poster with text, charts, and graphs.The pronouns an individual chooses when speaking or writing can reveal a considerable amount about him or her. This research project examines whether the emotional aspect of an experience has any influence on the types of pronouns that a person uses. We accomplish this task by analyzing Yelp reviews and determining whether the pronouns a person chooses when writing a review correspond to the rating, he or she gives that experience on a scale of one to five stars. This research is significant because any correlation we find would indicate that people use different types of pronouns when describing positive experiences as opposed to negative experiences. Our conclusions could be used to infer the emotional state of the author of any informal piece of writing, which would help readers determine if the author has any underlying bias toward the subject.University of Wisconsin--Eau Claire Office of Research and Sponsored Program

Finding Clusters of Similar Events within Clinical Incident

This paper discusses a novel methodological approach for identifying clusters of similar medical incidents by analyzing large databases of incident reports. The discovery of similar events allows the identification of patterns and trends, and makes possible the prediction of future events and the establishment of barriers and best practices. In our work we integrated two techniques from the fields of Information Science and Artificial Intelligence, namely Case-Based Reasoning and Information Retrieval, and achieved very good clustering accuracies on a test data set of transfusion medicine incident reports. Our work showed that clustering should integrate the features of an in1 Corresponding author cident captured in traditional form-based records, together with the detailed information found in the narrative included in event reports