Computer Engineering Commons^™

An Investigation Of Information Structures In Dna, Joel Mohrmann

Department of Electrical and Computer Engineering: Dissertations, Theses, and Student Research

The information-containing nature of the DNA molecule has been long known and observed. One technique for quantifying the relationships existing within the information contained in DNA sequences is an entity from information theory known as the average mutual information (AMI) profile. This investigation sought to use principally the AMI profile along with a few other metrics to explore the structure of the information contained in DNA sequences.

Treating DNA sequences as an information source, several computational methods were employed to model their information structure. Maximum likelihood and maximum a posteriori estimators were used to predict missing bases in DNA sequences. …

Modeling And Analysis Of Subcellular Protein Localization In Hyper-Dimensional Fluorescent Microscopy Images Using Deep Learning Methods, Yang Jiao

UNLV Theses, Dissertations, Professional Papers, and Capstones

Hyper-dimensional images are informative and become increasingly common in biomedical research. However, the machine learning methods of studying and processing the hyper-dimensional images are underdeveloped. Most of the methods only model the mapping functions between input and output by focusing on the spatial relationship, whereas neglect the temporal and causal relationships. In many cases, the spatial, temporal, and causal relationships are correlated and become a relationship complex. Therefore, only modeling the spatial relationship may result in inaccurate mapping function modeling and lead to undesired output. Despite the importance, there are multiple challenges on modeling the relationship complex, including the model …

A Study Of Scalability And Cost-Effectiveness Of Large-Scale Scientific Applications Over Heterogeneous Computing Environment, Arghya K. Das

LSU Doctoral Dissertations

Recent advances in large-scale experimental facilities ushered in an era of data-driven science. These large-scale data increase the opportunity to answer many fundamental questions in basic science. However, these data pose new challenges to the scientific community in terms of their optimal processing and transfer. Consequently, scientists are in dire need of robust high performance computing (HPC) solutions that can scale with terabytes of data.

In this thesis, I address the challenges in three major aspects of scientific big data processing as follows: 1) Developing scalable software and algorithms for data- and compute-intensive scientific applications. 2) Proposing new cluster architectures …

Protein Fold Classification With Grow-And-Learn Network, Özlem Polat, Zümray Dokur

Turkish Journal of Electrical Engineering and Computer Sciences

Protein fold classification is an important subject in computational biology and a compelling work from the point of machine learning. To deal with such a challenging problem, in this study, we propose a solution method for the classification of protein folds using Grow-and-Learn (GAL) neural network together with one-versus-others (OvO) method. To classify the most common 27 protein folds, 125 dimensional data, constituted by the physicochemical properties of amino acids, are used. The study is conducted on a database including 694 proteins: 311 of these proteins are used for training and 383 of them for testing. Overall, the classification system …

Using Latent Semantic Analysis For Automated Keyword Extraction From Large Document Corpora, Tuğba Önal Süzek

Turkish Journal of Electrical Engineering and Computer Sciences

In this study, we describe a keyword extraction technique that uses latent semantic analysis (LSA) to identify semantically important single topic words or keywords. We compare our method against two other automated keyword extractors, Tf-idf (term frequency-inverse document frequency) and Metamap, using human-annotated keywords as a reference. Our results suggest that the LSA-based keyword extraction method performs comparably to the other techniques. Therefore, in an incremental update setting, the LSA-based keyword extraction method can be preferably used to extract keywords from text descriptions from big data when compared to existing keyword extraction methods.

Meta-Analysis Of Transcriptome Data Identifies A Novel 5-Gene Pancreatic Adenocarcinoma Classifier, Manoj K. Bhasin, Kenneth Ndebele, Octavian Bucur, Eric U. Yee, Hasan H. Otu, Jessica Plati, Andrea Bullock, Xuesong Gu, Eduardo Castan, Peng Zhang, Robert Najarian, Maria S. Muraru, Rebecca Miksad, Roya Khosravi-Far, Towia A. Libermann

Department of Electrical and Computer Engineering: Faculty Publications

Purpose: Pancreatic ductal adenocarcinoma (PDAC) is largely incurable due to late diagnosis. Superior early detection biomarkers are critical to improving PDAC survival and risk stratification.

Experimental Design: Optimized meta-analysis of PDAC transcriptome datasets identified and validated key PDAC biomarkers. PDAC-specific expression of a 5-gene biomarker panel was measured by qRT-PCR in microdissected patient-derived FFPE tissues. Cell-based assays assessed impact of two of these biomarkers, TMPRSS4 and ECT2, on PDAC cells.

Results: A 5-gene PDAC classifier (TMPRSS4, AHNAK2, POSTN, ECT2, SERPINB5) achieved on average 95% sensitivity and 89% specificity in discriminating PDAC from non-tumor samples in four training sets and similar …

Novel Dynamic Partial Reconfiguration Implementations Of The Support Vector Machine Classifier On Fpga, Hanaa Hussain, Khaled Benkrid, Hüseyi̇n Şeker

Turkish Journal of Electrical Engineering and Computer Sciences

The support vector machine (SVM) is one of the highly powerful classifiers that have been shown to be capable of dealing with high-dimensional data. However, its complexity increases requirements of computational power. Recent technologies including the postgenome data of high-dimensional nature add further complexity to the construction of SVM classifiers. In order to overcome this problem, hardware implementations of the SVM classifier have been proposed to benefit from parallelism to accelerate the SVM. On the other hand, those implementations offer limited flexibility in terms of changing parameters and require the reconfiguration of the whole device. The latter interrupts the operation …

Signage Recognition Based Wayfinding System For The Visually Impaired, Abdullah Khalid Ahmed

Masters Theses

Persons of visual impairment make up a growing segment of modern society. To cater to the special needs of these individuals, society ought to consider the design of special constructs to enable them to fulfill their daily necessities. This research proposes a new method for text extraction from indoor signage that will help persons of visual impairment maneuver in unfamiliar indoor environments, thus enhancing their independence and quality of life.

In this thesis, images are acquired through a video camera mounted on glasses of the walking person. Frames are then extracted and used in an integrated framework that applies Maximally …

An Automated Signal Alignment Algorithm Based On Dynamic Time Warping For Capillary Electrophoresis Data, Fethullah Karabi̇ber

Turkish Journal of Electrical Engineering and Computer Sciences

Correcting the retention time variation and measuring the similarity of time series is one of the most popular challenges in the area of analyzing capillary electrophoresis (CE) data. In this study, an automated signal alignment method is proposed by modifying the dynamic time warping (DTW) approach to align the time-series data. Preprocessing tools and further optimizations were developed to increase the performance of the algorithm. As a demonstrative case study, the developed algorithm is applied to the analysis of CE data from a selective 2'-hydroxyl acylation analyzed by primer extension (SHAPE) evaluation of the RNA secondary structure. The time-shift problem …

System Designs To Perform Bioinformatics Sequence Alignment, Çağlar Yilmaz, Mustafa Gök

Turkish Journal of Electrical Engineering and Computer Sciences

The emerging field of bioinformatics uses computing as a tool to understand biology. Biological data of organisms (nucleotide and amino acid sequences) are stored in databases that contain billions of records. In order to process the vast amount of data in a reasonable time, high-performance analysis systems are developed. The main operation shared by the analysis tools is the search for matching patterns between sequences of data (sequence alignment). In this paper, we present 2 systems that can perform pairwise and multiple sequence alignment operations. Through the optimized design methods, proposed systems achieve up to 3.6 times more performance compared …

Data Compression Concepts And Algorithms And Their Applications To Bioinformatics, Ozkan U. Nalbantoglu, David J. Russell, Khalid Sayood

Department of Electrical and Computer Engineering: Faculty Publications

Data compression at its base is concerned with how information is organized in data. Understanding this organization can lead to efficient ways of representing the information and hence data compression. In this paper we review the ways in which ideas and approaches fundamental to the theory and practice of data compression have been used in the area of bioinformatics. We look at how basic theoretical ideas from data compression, such as the notions of entropy, mutual information, and complexity have been used for analyzing biological sequences in order to discover hidden patterns, infer phylogenetic relationships between organisms and study viral …

Pathologyxgrid Implementation For The Interproscan Bioinformatics Software, Cody K. Bumgardner

Cody Bumgardner

SoftwareInterProScan is an essential step in the Epichloëfestucae genome project’s pipeline. Complete determination of the genome sequence for Epichloëfestucae, requires substantial programmatic and computing efforts. Due to the running time requirements the computational volume of some of its subtasks exceed the power of a traditional single processor computation and high performance approaches, such as grid computing, are needed.

The Personal Digital Assistant (Pda) As A Tool For Telementoring Endoscopic Procedures., Cody K. Bumgardner

Cody Bumgardner

Abstract: The telementoring of surgical procedures is currently achieved via a wired infrastructure that usually requires sophisticated videoconference systems. This project represents the first step in assessing the potential for using handheld computers as a mobile alternative to current telementoring systems. Specifically, this project compares a handheld computer to a standard CRT monitor regarding their capability to accurately display video images from an endoscopic procedure. Video images from two previously recorded endoscopic procedures were transmitted from a standard VCR to: 1) a handheld computer (iPAQ 3670 running Pocket PC) via a wireless LAN and 2) a standard CRT monitor via …