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Formation of water channels in the crystalline hydrates of macrocyclic compounds [dataset]
(2018)
RSP and matrix zip files contain .sfrm files that have both the photographic data and metadata desicribing the instrument, readable with scientific software. The work zip file subfolder contains a .p4p file generated after ...
A rare event classification in the advanced manufacturing system: focused on imbalanced datasets
(University of Missouri--Columbia, 2022)
In many industrial applications, classification tasks are often associated with imbalanced class labels in training datasets. Imbalanced datasets can severely affect the accuracy of class predictions, and thus they need to be handled by appropriate...
Machine and Deep Learning Approach for Type 2 Diabetes Prediction Using the CDC’s BRFSS Dataset: A Retrospective Analysis
(2022)
Type 2 diabetes mellitus (T2DM) is a complex metabolic disease which is characterized by persistent hyperglycemia caused by insulin resistance. It is the most prevalent type of diabetes mellitus (DM). T2DM presents a heterogenous etiology...
Fully automated deep supervised and unsupervised learning approaches for 3D protein cryo-EM density map reconstruction
(University of Missouri--Columbia, 2019)
process, a limited electron dose is used as the high-energy electrons can greatly damage the specimen during imaging and results in extremely noisy micrographs. Hence, single particle images picking still present significant challenges due to that much...
An interpretable protein localization prediction framework
(University of Missouri--Columbia, 2021)
. This enables MULocDeep, to predict multiple localizations of a protein at both subcellular and suborganellar levels. We collected a dataset with 44 suborganellar localization annotations in 10 major subcellular compartments--the most comprehensive suborganelle...
Scholar Team Finder - link prediction model for identifying scholars in academic social networks
(University of Missouri--Columbia, 2023)
of federal grant awards, scholars' publication data, and two other widely used datasets. They also propose a beam-search algorithm for scholar team prediction based on the model. The results show that the ScholarTeamFinder outperforms state...
Improving protein structure prediction by deep learning and computational optimization
(University of Missouri--Columbia, 2019)
Protein structure prediction is one of the most important scientific problems in the field of bioinformatics and computational biology. The availability of protein three-dimensional (3D) structure is crucial for studying ...
Identification of demographics and comorbidities associated with Vascular Hamartomas
(2016)
Vascular hamartomas (VH) are tumor like growths that typically appear in
infants and manifest as a blemish on the skin. The goal of this study is to
substantiate clinical data on the demographic characteristics and ...
Protein contact distance and structure prediction driven by deep learning
(University of Missouri--Columbia, 2023)
, consequently impacting the prediction of protein tertiary and quaternary structures. This dissertation presents four contributions. First, DNSS2, an innovative approach based on one-dimensional deep convolutional networks, is proposed for the accurate...
Building datasets from scratch : data journalists offer best practices based on their experiences
(University of Missouri--Columbia, 2017)
[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI--COLUMBIA AT REQUEST OF AUTHOR.]
A descriptive analysis of fees at four-year public universities : differentiating between tuition and fees
(University of Missouri--Columbia, 2012)
Despite the overabundance of data collected and analyzed about tuition as a primary cost of public higher education, little to no attention has been paid to fees as a portion of that cost. Most of the existing research combines tuition and required...
Data mining and machine learning methods for chromosome conformation data analysis
(University of Missouri--Columbia, 2019)
, GSDB, a comprehensive and common repository that contains 3D structures for Hi-C datasets from novel 3D structure reconstruction tools developed over the years, third, ClusterTAD, a method for topological associated domains (TAD) extraction from Hi...
Applications of deep neural networks to protein structure prediction
(University of Missouri--Columbia, 2018)
. In extensive experiments on multiple datasets, the proposed deep neural architectures outperformed the best existing methods and other deep neural networks significantly: The proposed DeepNRN achieved highest Q8 75.33, 72.9, 70.8 on CASP 10, 11, 12 higher than...
Predicting student performance in an augmented reality learning environment using eye-tracking data
(University of Missouri--Columbia, 2023)
-Columbia participated in an AR biomechanics lecture consisting of 14 modules. Following each module students answered learning comprehension questions to test their understanding of the lecture material. An additional dataset was recorded for each module in which...
Protein-ion binding site prediction using deep learning
(University of Missouri--Columbia, 2023)
More than 50 percent of proteins bind to ions and these interactions are essential for various biological functions such as enzymatic catalysis, structural stability, signal transduction, protein function modulation, and ...
Development of advanced chemometric methods for the analysis of deep-UV resonance Raman spectra of proteins
(University of Missouri--Columbia, 2009)
spectra can be problematic due to the difficulty of determining the pure secondary structure Raman spectra. The use of multi-excitation datasets can help to alleviate the difficulty in determining the pure secondary structure Raman spectra, but due...
Stagnate summers : climate induced changes in physical mixing parameters in Missouri reservoirs
(University of Missouri--Columbia, 2017)
chemistry. Using a historical dataset to find both break points and monotonic trends that may indicate climate having influenced our reservoirs we found little in terms of monotonic trends. However, we did witness changes in all systems in regards to break...
Mizzou weekly, volume 19, number 07
(University of Missouri--Columbia. University Affairs. Publications and Alumni Communication., 1997)
Methods for high-resolution soil-landscape modeling in midwest upland landscapes
(University of Missouri--Columbia, 2008)
of peak functions across the landscape to produce a continuous numerical soil-landscape model. Coherent depth translation (CDT) was introduced as a method to transform and combine sparse soil profile data into a single dataset for improved modeling...