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protein function » protein glycation (Expand Search)
algorithm steps » algorithm its (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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A New Penalty Function Algorithm For Convex Quadratic Programming
Published 2020“…In this paper, we develop an exterior point algorithm for convex quadratic programming using a penalty function approach. …”
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Scatter search for protein structure prediction. (c2008)
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Adaptive step-size sign least mean squares
Published 2004“…A powerful adaptation scheme is used to adapt the step-size of the sign function inside the recursion of the sign algorithm. …”
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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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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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Scatter search metaheuristic for homology based protein structure prediction. (c2015)
Published 2015“…Determining a protein’s structure is a challenging goal in structural bioinformatics, offering important insight towards understanding the function of a protein. …”
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Tracking analysis of normalized adaptive algorithms
Published 2003“…Close agreement between analytical analysis and simulation results is obtained for the case of the NLMS algorithm. The results show that, unlike the stationary case, the steady-state excess-mean-square error is not a monotonically increasing function of the step-size, while the ability of the adaptive algorithm to track the variations in the environment degrades by increasing the frequency offset.…”
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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. …”
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Particle swarm optimization approach for protein structure prediction in the 3D HP model
Published 2012“…Proteins fold, under the influence of several chemical and physical factors, into their 3D structures, which determine their biological functions and properties. …”
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A Comparative Study of Elgamal Based Cryptographic Algorithms
Published 2004“…In this work we implement the classical and modified ElGamal cryptosystem to compare and to test their functionality, reliability and security. To test the security of the algorithms we use a famous attack algorithm called Baby-Step-Giant algorithm which works in the domain of natural integers. …”
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Genetic and heuristic algorithms for regrouping service sites. (c2000)
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Convergence analysis of the variable weight mixed-norm LMS-LMFadaptive algorithm
Published 2000“…In this work, the convergence analysis of the variable weight mixed-norm LMS-LMF (least mean squares-least mean fourth) adaptive algorithm is derived. The proposed algorithm minimizes an objective function defined as a weighted sum of the LMS and LMF cost functions where the weighting factor is time varying and adapts itself so as to allow the algorithm to keep track of the variations in the environment. …”
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