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protein function » protein glycation (Expand Search)
algorithm both » algorithm goa (Expand Search), algorithm aoa (Expand Search), algorithm its (Expand Search)
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protein function » protein glycation (Expand Search)
algorithm both » algorithm goa (Expand Search), algorithm aoa (Expand Search), algorithm its (Expand Search)
both function » cost function (Expand Search)
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Computational evluation of protein energy functions
Published 2014“…A protein is characterized by its 3D structure, which defines its biological function. …”
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Evolutionary algorithm for protein structure prediction
Published 2010“…A protein is characterized by its 3D structure, which defines its biological function. …”
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Scatter Search algorithm for Protein Structure Prediction
Published 2016“…Given the protein's sequence of Amino Acids (AAs), our algorithm produces a 3D structure that aims to minimise the energy function associated with the structure. …”
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Evolutionary algorithm for predicting all-atom protein structure
Published 2011“…This algorithm produces a 3D structure of the whole protein, including back-bone and side-chain atoms, by minimizing the energy function associated with the structure. …”
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New enumeration algorithm for regular boolean functions
Published 2018“…After proving this equivalence, this paper introduces a novel data structure that may, with further tweaking, enable faster enumeration algorithms for both regular Boolean functions and all-capacities knapsack problem instances.…”
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Scatter search for protein structure prediction. (c2008)
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Consensus-Based Distributed Formation Control of Multi-Quadcopter Systems: Barrier Lyapunov Function Approach
Published 2023“…The method is firstly developed in a centralized scheme and then extended to a distributed framework using appropriate asymptotically convergent consensus algorithms. Therefore, the asymptotic convergence of the designed distributed algorithm to the centralized one is guaranteed. …”
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Design and Implementation of an Advanced Control and Guidance Algorithm of a Single Rotor Helicopter
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Distributed optimal coverage control in multi-agent systems: Known and unknown environments
Published 2024“…The proposed technique offers an optimal solution with a lower cost with respect to conventional Voronoi-based techniques by effectively handling the issue of agents remaining stationary in regions void of information using a ranking function. The proposed approach leverages a novel cost function for optimizing the agents’ coverage and the cost function eventually aligns with the conventional Voronoi-based cost function. …”
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Fragment-based computational protein structure prediction
Published 2014“…The 3-dimensional configuration determines a protein’s function. Hence, it is very important to determine the correct structure in order to identify the wrong folding that indicates a disease situation. …”
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Fragment based protein structure prediction. (c2013)
Published 2016“…The results, evaluated on three proteins, show that the algorithm produces tertiary structures with promising root mean square deviations, within reasonable times.…”
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Iterative Least Squares Functional Networks Classifier
Published 2007“…Both methodology and learning algorithm for this kind of computational intelligence classifier using the iterative least squares optimization criterion are derived. …”
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Cross entropy error function in neural networks
Published 2002“…The ANN is implemented using the cross entropy error function in the training stage. The cross entropy function is proven to accelerate the backpropagation algorithm and to provide good overall network performance with relatively short stagnation periods. …”
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An Introduction to the Special Issue “Protein Glycation in Food, Nutrition, Health and Disease”
Published 2022“…The keynote speaker was Lasker Laureate Professor Kazutoshi Mori, speaking on the unfolded protein response, and there were sessions on: glycation in obesity, diabetes, and diabetic complications; glycation in food; glycation through the life course—from maternal bonding to aging; glycation in plants—physiology, function, and food security; glycation in the COVID-19 response; glycation analytics and chemistry; glycation in kidney disease, cancer, and mental health; glycation-related imaging, diagnostic algorithms, and therapeutics; and methods and models in glycation research. …”
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AGEomics Biomarkers and Machine Learning—Realizing the Potential of Protein Glycation in Clinical Diagnostics
Published 2022“…The term AGEomics is defined as multiplexed quantitation of spontaneous modification of proteins damage and other usually low-level modifications associated with a change of structure and function—for example, citrullination and transglutamination. …”