Computer Sciences Commons^™

K-Spmm: A Database Of Murine Spermatogenic Promoters Modules & Motifs, Yi Lu, Adrian E. Platts, G Charles Ostermeier, Stephen A. Krawetz

Wayne State University Associated BioMed Central Scholarship

Abstract

Background

Understanding the regulatory processes that coordinate the cascade of gene expression leading to male gamete development has proven challenging. Research has been hindered in part by an incomplete picture of the regulatory elements that are both characteristic of and distinctive to the broad population of spermatogenically expressed genes.

Description

K-SPMM, a database of murine Spermatogenic Promoters Modules and Motifs, has been developed as a web-based resource for the comparative analysis of promoter regions and their constituent elements in developing male germ cells. The system contains data on 7,551 genes and 11,715 putative promoter regions …

Information Systems And Health Care Xiii: Examining The Critical Requirements, Design Approaches And Evaluation Methods For A Public Health Emergency Response System, Ann L. Fruhling

Information Systems and Quantitative Analysis Faculty Publications

Research pertaining to emergency response systems has accelerated over the past few years, particularly since 9/11 events, and more recently due to Hurricane Katrina and concern over a potential of an avian flu pandemic. This study examines the requirements that are the most demanding with respect to software and hardware, and the associated design strategies for a public health emergency response system (ERS) for electronic laboratory diagnostics consultation. In addition, this study illustrates ways to evaluate the design decisions.

An important goal of a public health ERS is to improve the communication and notification of life-threatening diseases and harmful agents. …

Hybrid Committee Classifier For A Computerized Colonic Polyp Detection System, Jiang Li, Jianhua Yao, Nicholas Petrick, Ronald M. Summers, Amy K. Hara, Joseph M. Reinhardt (Ed.), Josien P.W. Pluim (Ed.)

Electrical & Computer Engineering Faculty Publications

We present a hybrid committee classifier for computer-aided detection (CAD) of colonic polyps in CT colonography (CTC). The classifier involved an ensemble of support vector machines (SVM) and neural networks (NN) for classification, a progressive search algorithm for selecting a set of features used by the SVMs and a floating search algorithm for selecting features used by the NNs. A total of 102 quantitative features were calculated for each polyp candidate found by a prototype CAD system. 3 features were selected for each of 7 SVM classifiers which were then combined to form a committee of SVMs classifier. Similarly, features …

Reconstructability Analysis As A Tool For Identifying Gene-Gene Interactions In Studies Of Human Diseases: Ieee Version, Martin Zwick, Stephen Shervais, Patricia Kramer

Complex Systems Faculty Publications and Presentations

There are a number of human diseases that are caused by the epistatic interaction of multiple genes. Detecting these interactions with standard statistical tools is difficult, because there may be an interaction effect, but minimal or no main effect. Reconstructability analysis uses Shannon’s information theory to detect relationships between variables in categorical datasets. We apply reconstructability analysis to data generated by five different models of gene-gene interaction, with heritability levels from 0.053 to 0.008, using 200 controls and 200 cases. We find that even with heritability levels as low as 0.008, and with the inclusion of 50 non-associated genes in …

Towards Knowledge Morphing: A Triangulation Approach To Link Tacit And Explicit Knowledge, Fehmida Hussain, Syed Sibte Raza Abidi, Syed Ali Raza

International Conference on Information and Communication Technologies

Current knowledge management systems are largely designed to deal with a single knowledge modality. Given the diversity of knowledge modalities that encompass any given topic/problem it is reasonable to demand access and use of all available knowledge, irrespective of their representation modality, to derive a knowledge-mediated solution. This calls for selecting all knowledge elements (represented in different modalities) that are relevant to the solution of the problem at hand. Thus here we pursue the specification and implementation of such a knowledge-mediated solution using a triangulation approach leading to Knowledge Morphing. In this paper we present a tacit-explicit knowledge morphing (TEKM) …

Effects Of Information And Machine Learning Algorithms On Word Sense Disambiguation With Small Datasets, Gondy Leroy, Thomas C. Rindflesch

CGU Faculty Publications and Research

Current approaches to word sense disambiguation use (and often combine) various machine learning techniques. Most refer to characteristics of the ambiguity and its surrounding words and are based on thousands of examples. Unfortunately, developing large training sets is burdensome, and in response to this challenge, we investigate the use of symbolic knowledge for small datasets. A naïve Bayes classifier was trained for 15 words with 100 examples for each. Unified Medical Language System (UMLS) semantic types assigned to concepts found in the sentence and relationships between these semantic types form the knowledge base. The most frequent sense of a word …

Reconstructability Analysis And Log-Linear Modeling, Martin Zwick

Complex Systems Faculty Publications and Presentations

Reconstructability Analysis (RA) is a method developed within the systems community for analyzing nominal (or discretized) data. RA both overlaps and extends Log-Linear (LL) modeling, and the purpose of this talk is to introduce RA to researchers unfamiliar with it. Two aspects of RA will be focused on: (1) its use for exploratory, as opposed to confirmatory, modeling – searching for good models in a vast space of possible models, and (2) state-based RA – analyzing data not in terms of relations among variables but in terms of relations among specific states of variables. Examples of applications to social science …

An Analysis Of Biometric Technology As An Enabler To Information Assurance, Darren A. Deschaine

Theses and Dissertations

The use of and dependence on, Information technology (IT) has grown tremendously in the last two decades. Still, some believe the United States is only in the infancy of this growth. This explosive growth has opened the door to capabilities that were only dreamed of in the past. As easy as it is to see how advantageous this technology is, it also is clear that with its advantages come distinct responsibilities and new problems that must be addressed. For instance, the minute one begins using information processing systems, the world of information assurance (IA) becomes far more complex. As a …

Method For Identifying Individuals, Manoj Thulasidas

Research Collection School Of Computing and Information Systems

A method and system for identifying a subject comprises obtaining a digitised recording of an electrocardiogram measurement of the subject to be identified, the digitised recording being a cyclic waveform having a peak amplitude. The digitised recording is normalised to reduce variations due to physiological effects, and the normalised recording is processed to determine a feature vector in the frequency domain. The distance between the determined feature vector and a predetermined feature vector is measured to identify the subject.

Probabilistic Disease Classification Of Expression-Dependent Proteomic Data From Mass Spectrometry Of Human Serum, Ryan H. Lilien, Hany Farid, Bruce R. Donald

Dartmouth Scholarship

We have developed an algorithm called Q5 for probabilistic classification of healthy vs. disease whole serum samples using mass spectrometry. The algorithm employs Principal Components Analysis (PCA) followed by Linear Discriminant Analysis (LDA) on whole spectrum Surface-Enhanced Laser Desorption/Ionization Time of Flight (SELDI-TOF) Mass Spectrometry (MS) data, and is demonstrated on four real datasets from complete, complex SELDI spectra of human blood serum.

Q5 is a closed-form, exact solution to the problem of classification of complete mass spectra of a complex protein mixture. Q5 employs a novel probabilistic classification algorithm built upon a dimension-reduced linear discriminant analysis. Our solution is …

Incremental Genetic K-Means Algorithm And Its Application In Gene Expression Data Analysis, Yi Lu, Shiyong Lu, Farshad Fotouhi, Youping Deng, Susan J. Brown

Wayne State University Associated BioMed Central Scholarship

Abstract

Background

In recent years, clustering algorithms have been effectively applied in molecular biology for gene expression data analysis. With the help of clustering algorithms such as K-means, hierarchical clustering, SOM, etc, genes are partitioned into groups based on the similarity between their expression profiles. In this way, functionally related genes are identified. As the amount of laboratory data in molecular biology grows exponentially each year due to advanced technologies such as Microarray, new efficient and effective methods for clustering must be developed to process this growing amount of biological data.

Results

In this paper, we propose a new clustering …

Reconstructability Analysis: Theory And Applications [Editorial Introduction], Martin Zwick, Guangfu Shu, Yi Lin

Complex Systems Faculty Publications and Presentations

Reconstructability analysis (RA) dates back to the pioneering work of Ashby in the mid-1960s. In the 1970s and 1980s, RA was the subject of very active research in the systems community. It receded for a time as a focus of activity, but the special issue of the International Journal of General Systems in 1996 on the General Systems Problem Solver and the special IJGS issue in 2000 on Reconstructability Analysis in China marked the renewal of interest in this area. The current volume is part of this resurgence of activity. It collects together papers from the group at Portland State …

Data Analysis In The Antes System, Yavuz Tor

Theses and Dissertations - UTB/UTPA

Acanthosis nigricans is a skin condition that can be used as an indicator for the risk of developing type 2 diabetes in the future. Border Health Office, in University of Texas - Pan American, organizes screenings in schools for acanthosis nigricans. Screening results are, then, collected and evaluated in the Border Health Office. The ANTES System is a computer system that stores and manages the data collected in those screenings.

This study is on the analysis of those collected data to track the progress of data entry, to evaluate the progress on obesity and related problems, and to discover the …

Antes: A Web-Based Acanthosis Nigricans And Other Obesity Related Information System, Chunyue Wang

Theses and Dissertations - UTB/UTPA

Acanthosis nigricans is a cutaneous marker associated with systemic disorders and may serve as an indicator for risk of Type 2 diabetes. Acanthosis nigricans screening can help identify children who have high insulin levels and who may be at-risk for developing Type 2 diabetes. The ANTES system is a computerization attempt for acanthosis nigricans control of the student population from elementary schools and secondary schools in Texas. A general description of the system and the medical and history background of the ANTES program is given. The technology applied to the system is demonstrated. An overview of the system operation status …

A Computer-Based Articulation Training Aid For Short Words (Cata), Mukund Devarajan

Electrical & Computer Engineering Theses & Dissertations

Several improvements in the vowel articulation training aid (VATA) are described, as well as the efforts to extend the visual feedback system to operate with short words in the form of consonant, vowel and consonant (CVC). The extended version of the visual feedback system is referred to as CATA (Computer-based Articulation Training Aid); the vowel version of the aid (VATA) only operates with ten American English monopthong vowels. Improvements in VATA include the use of a neural network (NN) recognizer method to prune a large database of vowel recordings to eliminate noisy and/or mispronounced tokens. The spectral jitter problem, previously …

Genescene: Biomedical Text And Data Mining, Gondy Leroy, Hsinchun Chen, Jesse D. Martinez, Shauna Eggers, Ryan R. Falsey, Kerri L. Kislin, Zan Huang, Jiexun Li, Jie Xu, Daniel M. Mcdonald, Gavin Ng

CGU Faculty Publications and Research

To access the content of digital texts efficiently, it is necessary to provide more sophisticated access than keyword based searching. GeneScene provides biomedical researchers with research findings and background relations automatically extracted from text and experimental data. These provide a more detailed overview of the information available. The extracted relations were evaluated by qualified researchers and are precise. A qualitative ongoing evaluation of the current online interface indicates that this method to search the literature is more useful and efficient than keyword based searching.

Modeling The Decision Process Of A Joint Task Force Commander, John Anthony Sokolowski

Computational Modeling & Simulation Engineering Theses & Dissertations

The U.S. military uses modeling and simulation as a tool to help meet its warfighting needs. A key element within military simulations is the ability to accurately represent human behavior. This is especially true in a simulation's ability to emulate realistic military decisions. However, current decision models fail to provide the variability and flexibility that human decision makers exhibit. Further, most decision models are focused on tactical decisions and ignore the decision process of senior military commanders at the operational level of warfare. In an effort to develop a better decision model that would mimic the decision process of a …

Automatic Speaker Identification Using Reusable And Retrainable Binary-Pair Partitioned Neural Networks, Ashutosh Mishra

Electrical & Computer Engineering Theses & Dissertations

This thesis presents an extension of the work previously done on speaker identification using Binary Pair Partitioned (BPP) neural networks. In the previous work, a separate network was used for each pair of speakers in the speaker population. Although the basic BPP approach did perform well and had a simple underlying algorithm, it had the obvious disadvantage of requiring an extremely large number of networks for speaker identification with large speaker populations. It also requires training of networks proportional to the square of the number of speakers under consideration, leading to a very large number of networks to be trained …

Health Care Informatics, Keng Siau

Research Collection School Of Computing and Information Systems

The health care industry is currently experiencing a fundamental change. Health care organizations are reorganizing their processes to reduce costs, be more competitive, and provide better and more personalized customer care. This new business strategy requires health care organizations to implement new technologies, such as Internet applications, enterprise systems, and mobile technologies in order to achieve their desired business changes. This article offers a conceptual model for implementing new information systems, integrating internal data, and linking suppliers and patients.

Mining Of Correlated Rules In Genome Sequences, L. Lin, L. Wong, Tze-Yun Leong, P. S. Lai

Research Collection School Of Computing and Information Systems

With the huge amount of data collected by scientists in the molecular genetics community in recent years, there exists a need to develop some novel algorithms based on existing data mining techniques to discover useful information from genome databases. We propose an algorithm that integrates the statistical method, association rule mining, and classification rule mining in the discovery of allelic combinations of genes that are peculiar to certain phenotypes of diseased patients.

Yet Another Algorithm For Pitch Tracking (Yaapt), Kavita Kasi

Electrical & Computer Engineering Theses & Dissertations

This thesis presents a pitch detection algorithm that is extremely robust for both high quality and telephone speech. The kernel method for this algorithm is the Normalized Cross Correlation (NCCF) reported by David Talkin [16]. Major innovations include: processing of the original acoustic signal and a nonlinearly processed version of the signal to partially restore very weak F0 components; intelligent peak picking to select multiple F0 candidates and assign merit factors; and, incorporation of highly robust pitch contours obtained from smoothed versions of low frequency portions of spectrograms. Dynamic programming is used to find the ''best" pitch track among all …

Modular Machine Learning Methods For Computer-Aided Diagnosis Of Breast Cancer, Mia Kathleen Markey '94

Doctoral Dissertations

The purpose of this study was to improve breast cancer diagnosis by reducing the number of benign biopsies performed. To this end, we investigated modular and ensemble systems of machine learning methods for computer-aided diagnosis (CAD) of breast cancer. A modular system partitions the input space into smaller domains, each of which is handled by a local model. An ensemble system uses multiple models for the same cases and combines the models' predictions.

Five supervised machine learning techniques (LDA, SVM, BP-ANN, CBR, CART) were trained to predict the biopsy outcome from mammographic findings (BIRADS™) and patient age based on a …

Western Michigan University Occupational Therapy Department Web Page, Holly Pietrzak, Melissa Byrne

Honors Theses

Website designed for WMU's Occupational Therapy department.

Filling Preposition-Based Templates To Capture Information From Medical Abstracts, Gondy Leroy, Hsinchun Chen

CGU Faculty Publications and Research

Due to the recent explosion of information in the biomedical field, it is hard for a single researcher to review the complex network involving genes, proteins, and interactions. We are currently building GeneScene, a toolkit that will assist researchers in reviewing existing literature, and report on the first phase in our development effort: extracting the relevant information from medical abstracts. We are developing a medical parser that extracts information, fills basic prepositional-based templates, and combines the templates to capture the underlying sentence logic. We tested our parser on 50 unseen abstracts and found that it extracted 246 templates with a …

Cognitive Rehab Solutions: A Computer-Assisted Cognitive Training Program, Avani Rajnikant Patel

Theses Digitization Project

The purpose of this project is to offer a functionally comprehensive application, Cognitive Rehab Solutions (CRS), that is designed for neuropsychologists to deliver restorative cognitive training in areas of attention and memory of persons with brain impairment.

Medtextus: An Ontology-Enhanced Medical Portal, Gondy Leroy, Hsinchun Chen

CGU Faculty Publications and Research

In this paper we describe MedTextus, an online medical search portal with dynamic search and browse tools. To search for information, MedTextus lets users request synonyms and related terms specifically tailored to their query. A mapping algorithm dynamically builds the query context based on the UMLS ontology and then selects thesaurus terms that fit this context. Users can add these terms to their query and meta-search five medical databases. To facilitate browsing, the search results can be reviewed as a list of documents per database, as a set of folders into which all the documents are automatically categorized based on …

Level Set Segmentation Of Mr Images For Extraction Of Femur Bone And Tissues, Christina Shanti Nayagam

Student Works (2000-2009)

This research explores a potentially useful segmentation algorithm, known as the level set method. It is suitable for images obtained from the Magnetic Resonance Imaging (MRJ) modality, despite the fact that MR images have low contrast between bone and tissue. The level set method is a numerical technique designed to track the evolution of an interface. The fast marching version of the method is implemented for two-dimensional (2-D) and three-dimensional (3-D) segmentation in this research. Femur segmentation is the main thrust of this thesis, however brain and heart images are also presented. Pre-processing steps are first performed for the 2-0 …

Internet Usage Among Medical Doctors In Malaysia, Surendran Jaganathan

Student Works (2000-2009)

In Malaysia, there were 20,000 Internet subscribers in 1996, 1.5 Million in 2000 and it is predicted to reach 4.5 Million in 2004. Malaysia is experiencing an explosive growth of Internet users. There is also a growing importance of "e -health businesses" as shown in the existing 20,000 healthcare sites currently online with an additional 1,500 sites being added every month. This translates to increasing healthcare site users for instance in America alone, out of 11 o million Internet users, 70 million searched the Web for health information. For healthcare consumers worldwide, the Internet has now become a tool for …

Meeting Medical Terminology Needs: The Ontology-Enhanced Medical Concept Mapper, Gondy Leroy, Hsinchun Chen

CGU Faculty Publications and Research

This paper describes the development and testing of the Medical Concept Mapper, a tool designed to facilitate access to online medical information sources by providing users with appropriate medical search terms for their personal queries. Our system is valuable for patients whose knowledge of medical vocabularies is inadequate to find the desired information, and for medical experts who search for information outside their field of expertise. The Medical Concept Mapper maps synonyms and semantically related concepts to a user's query. The system is unique because it integrates our natural language processing tool, i.e., the Arizona (AZ) Noun Phraser, with human-created …

Nonparametric Techniques To Extract Fuzzy Rules For Breast Cancer Diagnosis Problem, Manish Sarkar, Tze-Yun Leong

Research Collection School Of Computing and Information Systems

This paper addresses breast cancer diagnosis problem as a pattern classification problem. Specifically, the problem is studied using Wisconsin-Madison breast cancer data set. Fuzzy rules are generated from the input-output relationship so that the diagnosis becomes easier and transparent for both patients and physicians. For each class, at least one training pattern is chosen as the prototype, provided (a) the maximum membership of the training pattern is in the given class, and (b) among all the training patterns, the neighborhood of this training pattern has the least fuzzy-rough uncertainty in the given class. Using the fuzzy-rough uncertainty, a cluster is …