Life Sciences 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. …

Specialized Named Entity Recognition For Breast Cancer Subtyping, Griffith Scheyer Hawblitzel

Master's Theses

The amount of data and analysis being published and archived in the biomedical research community is more than can feasibly be sifted through manually, which limits the information an individual or small group can synthesize and integrate into their own research. This presents an opportunity for using automated methods, including Natural Language Processing (NLP), to extract important information from text on various topics. Named Entity Recognition (NER), is one way to automate knowledge extraction of raw text. NER is defined as the task of identifying named entities from text using labels such as people, dates, locations, diseases, and proteins. There …

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 …

Efficient Alignment Algorithms For Dna Sequencing Data, Nilesh Vinod Khiste

Electronic Thesis and Dissertation Repository

The DNA Next Generation Sequencing (NGS) technologies produce data at a low cost, enabling their application to many ambitious fields such as cancer research, disease control, personalized medicine etc. However, even after a decade of research, the modern aligners and assemblers are far from providing efficient and error free genome alignments and assemblies respectively. This is due to the inherent nature of the genome alignment and assembly problem, which involves many complexities. Many algorithms to address this problem have been proposed over the years, but there still is a huge scope for improvement in this research space.

Many new genome …

Developing An Application For Evolutionary Search For Computational Models Of Cellular Development, Nicolas Scott Cornia

Boise State University Theses and Dissertations

VPEvolve is a free and open source application that utilizes a Visual Programming Environment (VPE) for the setup of the Genetic Algorithm (GA), for optimization of computational models. Specifically, the User Interface uses connected glyphs to represent the genetic operators of mutation, reproduction, fitness and selection. These glyphs give the user an intuitive way to set the parameters for the GA, and better visualization of the population's flow through these operators.

VPEvolve is currently being developed alongside research being done in Biocomputing to create models of cellular regeneration based on the regenerative properties of Planaria or flatworms. Since these models …

Collaborative Research: North East Cyberinfrastructure Consortium, Michael Eckardt, Vicki Nemeth, Carolyn Mattingly

University of Maine Office of Research Administration: Grant Reports

The North East Cyberinfrastructure Consortium has finished its third year of Track-2 funding. In this report we summarize our overall progress and progress for Year 3.

In 2006, we began to organize as the five North Eastern EPSCoR states (ME, NH, VT, Rl, DE) around cyberinfrastructure. The box below describes the state of cyberinfrastructure in 2008 by which time we had developed the North East Cyberinfrastructure Consortium to position ourselves for grant opportunities that would help us to address our cyber deficits.

The Track-2 collaborative proposal submitted in January 2009 was designed to address these barriers in order enable our …