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Articles 1 - 8 of 8
Full-Text Articles in Life Sciences
Reports Of Autosomal Recessive Disease And Consanguineous Mating Within The Human Population, Johnathon L. Schluter
Reports Of Autosomal Recessive Disease And Consanguineous Mating Within The Human Population, Johnathon L. Schluter
Master's Theses
It is anecdotally evident when investigating published reports of autosomal recessive disease that a substantial number of cases are the result of related (consanguineous) mating. This research seeks to quantify the percent of manuscripts describing autosomal recessive diseases published between 2000 and 2020 in which consanguineous mating is indicated. We analyzed 602 peer-reviewed manuscripts to identify the percentage of cases presented in which consanguineous mating was indicated, the underlying genes (novel gene or new mutation) and geographical region. These papers were accessed through a specific set of parameters on the free access PubMed Central (PMC) database. A total of 552 …
Improvements On Segment Based Contours Method For Dna Microarray Image Segmentation, Yang Li
Improvements On Segment Based Contours Method For Dna Microarray Image Segmentation, Yang Li
Doctoral Dissertations
DNA microarray is an efficient biotechnology tool for scientists to measure the expression levels of large numbers of genes, simultaneously. To obtain the gene expression, microarray image analysis needs to be conducted. Microarray image segmentation is a fundamental step in the microarray analysis process. Segmentation gives the intensities of each probe spot in the array image, and those intensities are used to calculate the gene expression in subsequent analysis procedures. Therefore, more accurate and efficient microarray image segmentation methods are being pursued all the time.
In this dissertation, we are making efforts to obtain more accurate image segmentation results. We …
A Mathematical Model And Numerical Method For Thermoelectric Dna Sequencing, Liwei Shi
A Mathematical Model And Numerical Method For Thermoelectric Dna Sequencing, Liwei Shi
Doctoral Dissertations
DNA sequencing is the process of determining the precise order of nucleotide bases, adenine, guanine, cytosine, and thymine within a DNA molecule. It includes any method or technology that is used to determine the order of the four bases in a strand of DNA. The advent of rapid DNA sequencing methods has greatly accelerated biological and medical research and discovery. Thermoelectric DNA sequencing is a novel method to sequence DNA by measuring the heat that is released when DNA polymerase inserts a deoxyribonucleoside triphosphate into a growing DNA strand. The thermoelectric device for this project is composed of four parts: …
A Study Of Cellular Calcium Dynamics In Culture Using Fluorescence Microscopy – A Statistical And Mathematical Approach, Richard Adekola Idowu
A Study Of Cellular Calcium Dynamics In Culture Using Fluorescence Microscopy – A Statistical And Mathematical Approach, Richard Adekola Idowu
Doctoral Dissertations
Calcium in its ionic form is very dynamic, especially in excitable cells such as muscle and brain cells, moving from the high concentration exterior of the cell to much lower concentrations inside the cell, where calcium is used as a second messenger. In brain cells, and neurons especially, calcium is a key signaling ion involved in memory and learning with excitatory neurotransmitters such as glutamate turning neurons "on." Glutamate excites the neurons in part by causing large and dynamic changes in the intracellular calcium concentration. While these dynamics are essential for normal signaling in the brain, excessive and sustained elevations …
Associative Pattern Mining For Supervised Learning, Harpreet Singh
Associative Pattern Mining For Supervised Learning, Harpreet Singh
Doctoral Dissertations
The Internet era has revolutionized computational sciences and automated data collection techniques, made large amounts of previously inaccessible data available and, consequently, broadened the scope of exploratory computing research. As a result, data mining, which is still an emerging field of research, has gained importance because of its ability to analyze and discover previously unknown, hidden, and useful knowledge from these large amounts of data. One aspect of data mining, known as frequent pattern mining, has recently gained importance due to its ability to find associative relationships among the parts of data, thereby aiding a type of supervised learning known …
Discrete Nondeterministic Modeling Of Biochemical Networks, John R. Jack
Discrete Nondeterministic Modeling Of Biochemical Networks, John R. Jack
Doctoral Dissertations
The ideas expressed in this work pertain to biochemical modeling. We explore our technique, the Nondeterministic Waiting Time algorithm, for modeling molecular signaling cascades. The algorithm is presented with pseudocode along with an explanation of its implementation. The entire source code can be found in the Appendices. This algorithm builds on earlier work from the lab of Dr. Andrei Nun, the advisor for this dissertation. We discuss several important extensions including: (i) a heap with special maintenance functions for sorting reaction waiting times, (ii) a nondeterministic component for handling reaction competition, and (iii) a memory enhancement allowing slower reactions to …
Integrated Mining Of Feature Spaces For Bioinformatics Domain Discovery, Pradeep Chowriappa
Integrated Mining Of Feature Spaces For Bioinformatics Domain Discovery, Pradeep Chowriappa
Doctoral Dissertations
One of the major challenges in the field of bioinformatics is the elucidation of protein folding for the functional annotation of proteins. The factors that govern protein folding include the chemical, physical, and environmental conditions of the protein's surroundings, which can be measured and exploited for computational discovery purposes. These conditions enable the protein to transform from a sequence of amino acids to a globular three-dimensional structure. Information concerning the folded state of a protein has significant potential to explain biochemical pathways and their involvement in disorders and diseases. This information impacts the ways in which genetic diseases are characterized …
Membrane Systems With Limited Parallelism, Bianca Daniela Popa
Membrane Systems With Limited Parallelism, Bianca Daniela Popa
Doctoral Dissertations
Membrane computing is an emerging research field that belongs to the more general area of molecular computing, which deals with computational models inspired from bio-molecular processes. Membrane computing aims at defining models, called membrane systems or P systems, which abstract the functioning and structure of the cell. A membrane system consists of a hierarchical arrangement of membranes delimiting regions, which represent various compartments of a cell, and with each region containing bio-chemical elements of various types and having associated evolution rules, which represent bio-chemical processes taking place inside the cell.
This work is a continuation of the investigations aiming to …