Computer Sciences Commons^™

Machine Learning Analysis Of Single Nucleotide Polymorphism (Snp) Data To Predict Bone Mineral Density In African American Women, Erick Githua Wakayu

UNLV Theses, Dissertations, Professional Papers, and Capstones

Osteoporosis is a debilitating disease in which an individual’s bones weaken, making bones fragile and more susceptible to fracture. While commonly found amongst postmenopausal Caucasian and Asian women based on previous studies, those of African descent (African American/Black) have largely been ignored when it comes to osteoporotic studies, especially when it comes to Genome Wide Association Studies (GWAS). From GWA studies, we gain access to single nucleotide poly-morphisms (SNPs) that may contribute to certain illnesses, such as osteoporosis. With low Bone Mineral Density (BMD) being one of the primary markers of potential osteoporosis, it is prudent that proper research is …

Evaluation Of Deep Neural Network Prospr For Accurate Protein Distance Predictions On Casp14 Targets, Jacob A. Stern, Bryce Eric Hedelius, Olivia Fisher, Wendy M. Billings, Dennis Della Corte

Faculty Publications

The field of protein structure prediction has recently been revolutionized through the introduction of deep learning. The current state-of-the-art tool AlphaFold2 can predict highly accurate structures; however, it has a prohibitively long inference time for applications that require the folding of hundreds of sequences. The prediction of protein structure annotations, such as amino acid distances, can be achieved at a higher speed with existing tools, such as the ProSPr network. Here, we report on important updates to the ProSPr network, its performance in the recent Critical Assessment of Techniques for Protein Structure Prediction (CASP14) competition, and an evaluation of its …

Three-Dimensional Graph Matching To Identify Secondary Structure Correspondence Of Medium-Resolution Cryo-Em Density Maps, Bahareh Behkamal, Mahmoud Naghibzadeh, Mohammad Reza Saberi, Zeinab Amiri Tehranizadeh, Andrea Pagnani, Kamal Al Nasr

Computer Science Faculty Research

Cryo-electron microscopy (cryo-EM) is a structural technique that has played a significant role in protein structure determination in recent years. Compared to the traditional methods of X-ray crystallography and NMR spectroscopy, cryo-EM is capable of producing images of much larger protein complexes. However, cryo-EM reconstructions are limited to medium-resolution (~4–10 Å) for some cases. At this resolution range, a cryo-EM density map can hardly be used to directly determine the structure of proteins at atomic level resolutions, or even at their amino acid residue backbones. At such a resolution, only the position and orientation of secondary structure elements (SSEs) such …

Comparison Of Multiple Imputation Algorithms And Verification Using Whole-Genome Sequencing In The Cmuh Genetic Biobank, Ting-Yuan Liu, Chih-Fan Lin, Hsing-Tsung Wu, Ya-Lun Wu, Yu-Chia Chen, Chi-Chou Liao, Yu-Pao Chou, Dysan Chao, Hsing-Fang Lu, Ya-Sian Chang, Jan-Gowth Chang, Kai-Cheng Hsu, Fuu‑Jen Tsai

BioMedicine

A genome-wide association study (GWAS) can be conducted to systematically analyze the contributions of genetic factors to a wide variety of complex diseases. Nevertheless, existing GWASs have provided highly ethnic specific data. Accordingly, to provide data specific to Taiwan, we established a large-scale genetic database in a single medical institution at the China Medical University Hospital. With current technological limitations, microarray analysis can detect only a limited number of single-nucleotide polymorphisms (SNPs) with a minor allele frequency of >1%. Nevertheless, imputation represents a useful alternative means of expanding data. In this study, we compared four imputation algorithms in terms of …

Classifying Mosquito Presence And Genera Using Median And Interquartile Values From 26-Filter Wingbeat Acoustic Properties, Hernan S. Alar, Proceso L. Fernandez Jr

Department of Information Systems & Computer Science Faculty Publications

Mosquitoes are known to be one of the deadliest creatures in the world. There have been several studies that aim to identify mosquito presence and species using various techniques. The most common ones involve automatic identification of mosquito species from the sounds produced by flapping its wings. The development of these important concepts and technologies can help reduce the spread of mosquito-borne diseases. This paper presents a simple model based on mean and interquartile values that aim to solve the mosquito classification. Despite its simplicity, the proposed model significantly outperforms a Convolutional Neural Network (CNN) model in identifying the mosquito …

Reconstructing Mathematical Models With Chaotic Attractors Via Genetic Algorithms, Luis A. Ramirez Islas, Paul A. Valle

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.

Artificial Intelligence Algorithms For Medical Imaging And Healthcare, Jonathan William Stubblefield

Student Theses and Dissertations

In this dissertation, we studied several applications of artificial intelligence applications to healthcare. In the first chapter, we examined a machine learning algorithm for classifying patients presenting to the emergency department with acute respiratory distress syndrome (ARDS). Patients presenting with this life-threatening condition require a quick and accurate assessment of whether the condition is infectious or cardiac in etiology as the treatments for these etiologies of ARDS differ significantly. We used a transfer learning approach to develop our model. The model used a combination of clinical data and a chest x-ray as its input and achieved an accuracy 0.675 on …

Machine Learning For Species Habitat Analysis, Abigail Lavallin

USF Tampa Graduate Theses and Dissertations

Management and conservation initiatives will always be controlled by finite resources, whether financialor temporal. Understanding a species’ spatial ecology, and how its requirements vary across habitats and locations is key to a successful species management plan. During recent decades, it has been noted how many species populations have declined, despite conservation practices working to increase their numbers. The most prevalent impacts affecting fauna populations have come from anthropogenic change in the form of habitat loss and destruction, along with fragmentation, and global climate change. There is a clear need for management practices to now operate on an entire landscape instead …

Simplifying The Development Of Portable, Scalable, And Reproducible Workflows, Stephen Piccolo, Zachary E. Ence, Elizabeth C. Anderson, Jeffrey T. Chang, Andrea H. Bild

Faculty Publications

Command-line software plays a critical role in biology research. However, processes for installing and executing software differ widely. The Common Workflow Language (CWL) is a community standard that addresses this problem. Using CWL, tool developers can formally describe a tool’s inputs, outputs, and other execution details. CWL documents can include instructions for executing tools inside software containers. Accordingly, CWL tools are portable—they can be executed on diverse computers—including personal workstations, high-performance clusters, or the cloud. CWL also supports workflows, which describe dependencies among tools and using outputs from one tool as inputs to others. To date, CWL has been used …

Statistical Potentials For Rna-Protein Interactions Optimized By Cma-Es, Takayuki Kimura, Nobuaki Yasuo, Masakazu Sekijima, Brooke Lustig

Faculty Research, Scholarly, and Creative Activity

Characterizing RNA-protein interactions remains an important endeavor, complicated by the difficulty in obtaining the relevant structures. Evaluating model structures via statistical potentials is in principle straight-forward and effective. However, given the relatively small size of the existing learning set of RNA-protein complexes optimization of such potentials continues to be problematic. Notably, interaction-based statistical potentials have problems in addressing large RNA-protein complexes. In this study, we adopted a novel strategy with covariance matrix adaptation (CMA-ES) to calculate statistical potentials, successfully identifying native docking poses.

Bone Quality And Fractures In Women With Osteoporosis Treated With Bisphosphonates For 1 To 14 Years, Hartmut H. Malluche, Jin Chen, Florence Lima, Lucas J. Liu, Marie-Claude Monier-Faugere, David A. Pienkowski

Internal Medicine Faculty Publications

Oral bisphosphonates are the primary medication for osteoporosis, but concerns exist regarding potential bone-quality changes or low-energy fractures. This cross-sectional study used artificial intelligence methods to analyze relationships among bisphosphonate treatment duration, a wide variety of bone-quality parameters, and low-energy fractures. Fourier transform infrared spectroscopy and histomorphometry quantified bone-quality parameters in 67 osteoporotic women treated with oral bisphosphonates for 1 to 14 years. Artificial intelligence methods established two models relating bisphosphonate treatment duration to bone-quality changes and to low-energy clinical fractures. The model relating bisphosphonate treatment duration to bone quality demonstrated optimal performance when treatment durations of 1 to 8 …

Molecular Dynamics Simulations Of Self-Assemblies In Nature And Nanotechnology, Phu Khanh Tang

Dissertations, Theses, and Capstone Projects

Nature usually divides complex systems into smaller building blocks specializing in a few tasks since one entity cannot achieve everything. Therefore, self-assembly is a robust tool exploited by Nature to build hierarchical systems that accomplish unique functions. The cell membrane distinguishes itself as an example of Nature’s self-assembly, defining and protecting the cell. By mimicking Nature’s designs using synthetically designed self-assemblies, researchers with advanced nanotechnological comprehension can manipulate these synthetic self-assemblies to improve many aspects of modern medicine and materials science. Understanding the competing underlying molecular interactions in self-assembly is always of interest to the academic scientific community and industry. …

Evaluation Of Wind Data Reliability By Using Logarithmic And Power Laws: A Case Study In Southern Iraq, Ahmed B. Khamees, Saif F. Yaseen, Khalid S. Heni, Mudar Ahmed Abdulsattar

Karbala International Journal of Modern Science

In this study, two sites were investigated in the southern region of Iraq: Ali AL-Gharbi and AL-Salman in Mesan and AL-Muthana provinces, respectively. A theoretical extrapolation between wind speed and height was carried out for both locations each month using the Logarithmic Law. Power Law was also applied to achieve calculations of wind shear coefficient (α) by using the actual data collected from the meteorological mast installed in each site at three levels of 10 m, 30 m, and 50 m, at an interval of ten minutes. To compare the effects of each law, two laws are employed.

Polystyrene Molecular Weight Determination Of Submicron Particles Shell, Airat Z. Sakhabutdinov, Safaa.M.R.H. Hussein, Alsu R. Ibragimova Ph.D., Vladimir Kuklin Ph.D., Maxim Petrovich Danilaev, L.Y. Zaharova

Karbala International Journal of Modern Science

The method of determination of the molecular weight of the polystyrene, which is formed as the shell on the surfaces of submicron aluminum oxide particles is considered in the paper. This method is based on the sedimentation of submicron particles, covered by polymer molecules, in a solvent for polystyrene. It is shown that the average polystyrene molecular weight is 39500±11250 amu, when the polymer shells on the surfaces of submicron particles (Al2O3) are formed by the vapor-phase method.

Adaptive Reconstruction Of The Heterogeneous Scan Line Etm+ Correction Technique, Heba Kh. Abbas, Salema S. Salman, Rash Awad Abtan, Anwar H. Al-Saleh, Ali A. Al-Zuky

Karbala International Journal of Modern Science

ETM+ is a land-imaging sensor with great and wide use in many fields, however, after May 2003, because of a technical defect in the sensor´s system scan line corrector SLC, it started giving images of earth containing black gap lines at a 22% rate. These gaps made the process of analyzing and extracting accurate information from these images difficult and complicated. Therefore, scientists have developed many techniques to remove the gap lines from all ETM+ band-images and complete the missing data. In this study, three different ETM+ time images with a 16-day interval between them were used to fill gap …

Two-Dimensional Quantitative Profiling Of Cell Morphology With Serous Effusion By Unsupervised Machine Learning Analysis, Safaa Al-Qaysi Ph.D., Ding Dai Md Ph.D., Heng Hong Md Ph.D., Yuhua Wen Ph.D., X.H. Hu Ph.D.

Karbala International Journal of Modern Science

Cytological evaluation of serous effusion specimens is an important part of cancer diagnosis. In this study we performed two-dimensional (2D) morphometric features and clustering analysis for development of useful techniques for identification and differentiation of malignant and begin cells in serous effusion specimens extracted from ten patients with clinical symptoms of pleural and peritoneal effusion. Our findings show that the two-dimensional (2D) morphometric features and clustering analysis are useful techniques for identification and differentiation of malignant and begin cells in serous effusion specimens, which can lead to development of new methods for rapid cells profiling in clinical application.

Editorial Board

Karbala International Journal of Modern Science

No abstract provided.

Efficient Load Balancing Algorithm In Long Term Evolution (Lte) Heterogeneous Network Based On Dynamic Cell Range Expansion Bias, Emmanuel Bakuza, Hashimu U. Iddi, Abdi T. Abdalla

Tanzania Journal of Science

The traditional scheme for load balancing in a homogeneous Long Term Evolution (LTE) Network where User Equipment (UEs) associate to a node with the strongest received signal strength is not practical for LTE Heterogeneous Network (LTE HetNet) due to power disparity between the nodes. Therefore, dynamic Cell Range Expansion (CRE) based load-balancing schemes were employed by several scholars to address the challenges in the LTE HetNet. However, the fairness index in achieving the desired average user throughput and UE offloading effect is relatively low. In this work, an efficient load-balancing algorithm for LTE HetNet based on dynamic Cell Range Expansion …

Mathematical Programming Model For The Two-Level Facility Location Problem: The Case Of Tanzanian Emergence Maize Distribution Network For 2004–2010 Maize Data, Said A. Sima

Tanzania Journal of Science

A two-level facility location problem (FLP) has been studied in the transportation network of emergence maize crop in Tanzania. The facility location problem is defined as the optimal location of facilities or resources so as to minimize costs in terms of money, time, distance and risks with the relation to supply and demand points. Distribution network design problems consist of determining the best way to transfer goods from the supply to the demand points by choosing the structure of the network such that the overall cost is minimized. The three layers, namely production centres (PCs), distribution centres (DCs) and customer …

Telomere Roles In Fungal Genome Evolution And Adaptation, Mostafa Rahnama, Baohua Wang, Jane Dostart, Olga Novikova, Daniel Yackzan, Andrew T. Yackzan, Haley Bruss, Maray Baker, Haven Jacob, Xiaofei Zhang, April Lamb, Alex Stewart, Melanie Heist, Joey Hoover, Patrick Calie, Li Chen, Jinze Liu, Mark L. Farman

Plant Pathology Faculty Publications

Telomeres form the ends of linear chromosomes and usually comprise protein complexes that bind to simple repeated sequence motifs that are added to the 3′ ends of DNA by the telomerase reverse transcriptase (TERT). One of the primary functions attributed to telomeres is to solve the “end-replication problem” which, if left unaddressed, would cause gradual, inexorable attrition of sequences from the chromosome ends and, eventually, loss of viability. Telomere-binding proteins also protect the chromosome from 5′ to 3′ exonuclease action, and disguise the chromosome ends from the double-strand break repair machinery whose illegitimate action potentially generates catastrophic chromosome aberrations. Telomeres …

Automated Parsing Of Flexible Molecular Systems Using Principal Component Analysis And K-Means Clustering Techniques, Matthew J. Nwerem

Computational and Data Sciences (MS) Theses

Computational investigation of molecular structures and reactions of biological and pharmaceutical interests remains a grand scientific challenge due to the size and conformational flexibility of these systems. The work requires parsing and analyzing thousands of conformations in each molecular state for meaningful chemical information and subjecting the ensemble to costly quantum chemical calculations. The current status quo typically involves a manual process where the investigator must look at each conformation, separating each into structural families. This process is time-intensive and tedious, making this process infeasible in some cases, and limiting the ability of theoreticians to study these systems. However, the …

Computational Techniques For Elucidating Plant-Pathogen Interactions: A Case Study On Citrus-Hlb Interactome, Cristian D. Loaiza

All Graduate Theses and Dissertations, Spring 1920 to Summer 2023

The Citrus fruit industry in the United States has been affected during the last two decades because of the outbreak of the citrus greening disease, also known as Huanglongbing (HLB). Many people and organizations are working in therapeutics to help mitigate the impact of this disease, unfortunately there is not a cure yet. There are many mechanisms that needs to be understood about this disease, especially at the molecular level. Not only HLB, but many other infectious diseases are controlled by the interaction of proteins from the host (Citrus in this case) and from the pathogen that causes the disease. …

Graphical Models In Reconstructability Analysis And Bayesian Networks, Marcus Harris, Martin Zwick

Complex Systems Faculty Publications and Presentations

Reconstructability Analysis (RA) and Bayesian Networks (BN) are both probabilistic graphical modeling methodologies used in machine learning and artificial intelligence. There are RA models that are statistically equivalent to BN models and there are also models unique to RA and models unique to BN. The primary goal of this paper is to unify these two methodologies via a lattice of structures that offers an expanded set of models to represent complex systems more accurately or more simply. The conceptualization of this lattice also offers a framework for additional innovations beyond what is presented here. Specifically, this paper integrates RA and …

Graph-Theoretic Partitioning Of Rnas And Classification Of Pseudoknots-Ii, Louis Petingi

Publications and Research

Dual graphs have been applied to model RNA secondary structures with pseudoknots, or intertwined base pairs. In previous works, a linear-time algorithm was introduced to partition dual graphs into maximally connected components called blocks and determine whether each block contains a pseudoknot or not. As pseudoknots can not be contained into two different blocks, this characterization allow us to efficiently isolate smaller RNA fragments and classify them as pseudoknotted or pseudoknot-free regions, while keeping these sub-structures intact. Moreover we have extended the partitioning algorithm by classifying a pseudoknot as either recursive or non-recursive in order to continue with our research …

Awegnn: Auto-Parametrized Weighted Element-Specific Graph Neural Networks For Molecules., Timothy Szocinski, Duc Duy Nguyen, Guo-Wei Wei

Mathematics Faculty Publications

While automated feature extraction has had tremendous success in many deep learning algorithms for image analysis and natural language processing, it does not work well for data involving complex internal structures, such as molecules. Data representations via advanced mathematics, including algebraic topology, differential geometry, and graph theory, have demonstrated superiority in a variety of biomolecular applications, however, their performance is often dependent on manual parametrization. This work introduces the auto-parametrized weighted element-specific graph neural network, dubbed AweGNN, to overcome the obstacle of this tedious parametrization process while also being a suitable technique for automated feature extraction on these internally complex …

An Automated Method To Enrich And Expand Consumer Health Vocabularies Using Glove Word Embeddings, Mohammed Ibrahim

Graduate Theses and Dissertations

Clear language makes communication easier between any two parties. However, a layman may have difficulty communicating with a professional due to not understanding the specialized terms common to the domain. In healthcare, it is rare to find a layman knowledgeable in medical jargon, which can lead to poor understanding of their condition and/or treatment. To bridge this gap, several professional vocabularies and ontologies have been created to map laymen medical terms to professional medical terms and vice versa. Many of the presented vocabularies are built manually or semi-automatically requiring large investments of time and human effort and consequently the slow …

Economically Optimal Nitrogen Side-Dressing Based On Vegetation Indices From Satellite Images Through On-Farm Experiments, Qianqian Du

Department of Agricultural Economics: Dissertations, Theses, and Student Research

Optimal N fertilizer rates for corn (Zea mays L.) vary substantially within and among fields, and by corn growth stages. Improving N side-dressing management can improve fertilizer use efficiency, farmers’ profitability, and the sustainability of crop production. The objective of this study is to introduce a framework along with a methodology that can find the site-specific economically optimal N rates (EONRs) within one field for a particular growing season. An on-farm experiment was conducted in the 2019 corn growing season. A base N rate was applied uniformly on the field. NDRE images from the Sentinel-2 satellite were observed during …

Analysis Of The Slo Bay Microbiome From A Network Perspective, Lien Viet Nguyen

Master's Theses

Microorganisms are key players in the ecosystem functioning. In this thesis, we developed a framework to preprocess raw microbiome data, build a correlation network, and analyze co-occurrence patterns between microbes. We then applied this framework to a marine microbiome dataset. The dataset used in this study comes from a year-long time-series to characterize the microbial communities in our coastal waters off the Cal Poly Pier. In analyzing this dataset, we were able to observe and confirm previously discovered patterns of interactions and generate hypotheses about new patterns. The analysis of co-occurrences between prokaryotic and eukaryotic taxa is relatively novel and …

A Constitutive-Based Deep Learning Model For The Identification Of Active Contraction Parameters Of The Left Ventricular Myocardium, Igor Augusto Paschoalotte Nobrega

USF Tampa Graduate Theses and Dissertations

Modern breakthroughs in biomedical engineering, computer science, and data mining have created new opportunities for detecting important mechanical properties of soft tissues that can be employed to identify possible signs of diseases or physiological difficulties. However, the scarcity of different mechanical properties obtained through noninvasive testing emphasizes the importance of incorporating authentic biological data into computer models capable of replicating the behavior of soft tissues.

The field of continuum theory of large deformation hyperactivity permits the formulation of highly descriptive mathematical research and computational models capable of perfectly describing the minute mechanical characteristics of soft materials. By including features about …

Functional Role Of The N-Terminal Domain In Connexin 46/50 By In Silico Mutagenesis And Molecular Dynamics Simulation, Umair Khan

University Honors Theses

Connexins form intercellular channels known as gap junctions that facilitate diverse physiological roles, from long-range electrical and chemical coupling to nutrient exchange. Recent structural studies on Cx46 and Cx50 have defined a novel and stable open state and implicated the amino-terminal (NT) domain as a major contributor to functional differences between connexin isoforms. This thesis presents two studies which use molecular dynamics simulations with these new structures to provide mechanistic insight into the function and behavior of the NTH in Cx46 and Cx50. In the first, residues in the NTH that differ between Cx46 and Cx50 are swapped between the …