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Full-Text Articles in Physical Sciences and Mathematics
A Review Of Threat Vectors To Dna Sequencing Pipelines, Tyler Rector
A Review Of Threat Vectors To Dna Sequencing Pipelines, Tyler Rector
Cybersecurity Undergraduate Research Showcase
Bioinformatics is a steadily growing field that focuses on the intersection of biology with computer science. Tools and techniques developed within this field are quickly becoming fixtures in genomics, forensics, epidemiology, and bioengineering. The development and analysis of DNA sequencing and synthesis have enabled this significant rise in demand for bioinformatic tools. Notwithstanding, these bioinformatic tools have developed in a research context free of significant cybersecurity threats. With the significant growth of the field and the commercialization of genetic information, this is no longer the case. This paper examines the bioinformatic landscape through reviewing the biological and cybersecurity threats within …
Tracing And Segmentation Of Molecular Patterns In 3-Dimensional Cryo-Et/Em Density Maps Through Algorithmic Image Processing And Deep Learning-Based Techniques, Salim Sazzed
Computer Science Theses & Dissertations
Understanding the structures of biological macromolecules is highly important as they are closely associated with cellular functionalities. Comprehending the precise organization of actin filaments is crucial because they form the dynamic cytoskeleton, which offers structural support to cells and connects the cell’s interior with its surroundings. However, determining the precise organization of actin filaments is challenging due to the poor quality of cryo-electron tomography (cryo-ET) images, which suffer from low signal-to-noise (SNR) ratios and the presence of missing wedge, as well as diverse shape characteristics of actin filaments. To address these formidable challenges, the primary component of this dissertation focuses …
Wearable Sensor Gait Analysis For Fall Detection Using Deep Learning Methods, Haben Girmay Yhdego
Wearable Sensor Gait Analysis For Fall Detection Using Deep Learning Methods, Haben Girmay Yhdego
Electrical & Computer Engineering Theses & Dissertations
World Health Organization (WHO) data show that around 684,000 people die from falls yearly, making it the second-highest mortality rate after traffic accidents [1]. Early detection of falls, followed by pneumatic protection, is one of the most effective means of ensuring the safety of the elderly. In light of the recent widespread adoption of wearable sensors, it has become increasingly critical that fall detection models are developed that can effectively process large and sequential sensor signal data. Several researchers have recently developed fall detection algorithms based on wearable sensor data. However, real-time fall detection remains challenging because of the wide …
A Growth Model For Arctica Islandica: The Performance Of Tanaka And The Temptation Of Von Bertalanffy—Can The Two Coexist?, John M. Klinck, Eric N. Powell, Kathleen M. Hemeon, Jillian R. Sower, Daniel R. Hennen
A Growth Model For Arctica Islandica: The Performance Of Tanaka And The Temptation Of Von Bertalanffy—Can The Two Coexist?, John M. Klinck, Eric N. Powell, Kathleen M. Hemeon, Jillian R. Sower, Daniel R. Hennen
CCPO Publications
Organisms increase in size over time (age) due to excess assimilation over metabolic (respiration) energy demands. Most organisms reach a maximum size with increasing age as gain and loss balance. The von Bertalanffy length-at-age relationship, which is commonly used in fishery assessment calculations, imposes such a maximum size. However, some fished species, such as ocean quahogs, Arctica islandica, are long lived and continue to grow at old age. The Tanaka age-at-length relationship has continued growth at old age, but is rarely used in stock assessment models. A modified form of the von Bertalanffy model is presented, which mimics the …
Analysis Of Ab Initio Protein Structure Prediction Methods, Maytha Alshammari, Jing He
Analysis Of Ab Initio Protein Structure Prediction Methods, Maytha Alshammari, Jing He
College of Sciences Posters
Protein structure prediction produces atomic models of three-dimensional structure of a protein from its amino acid sequence. Understanding the function mechanism of proteins requires knowledge of three-dimensional structures. When developing new enzymes and drugs, it's essential to understand the structure of the target protein. In this study, we analyze models predicted using two ab initio protein structure prediction methods, trRosetta and Quark. A set of thirty protein chains was used to evaluate the effectiveness of the methods. The thirty chains were collected from Protein Data Bank (June – November, 2020). The length and the relative position of the predicted secondary …