Computational evluation of protein energy functions by Mansour, Nashat

“…A protein is characterized by its 3D structure, which defines its biological function. …”
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Evolutionary algorithm for protein structure prediction by Mansour, Nashat

“…A protein is characterized by its 3D structure, which defines its biological function. …”
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Scatter Search algorithm for Protein Structure Prediction by Mansour, Nashat

“…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 by Mansour, Nashat

“…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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Scatter search for protein structure prediction. (c2008) by Kehyayan, Christine Houry

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Particle swarm optimization based algorithm for protein structure prediction in the 3D HP model. (c2008) by Kanj, Fatima Hassan

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Improved scatter search algorithm for predicting all-atoms protein structures using charmm22 energy model. (c2010) by Ghalayini, Iman Adnan

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Detecting protein complexes in protein interaction networks using Mapper and Graph Convolution Networks by Daou, Leonardo

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Fragment-based computational protein structure prediction by Mansour, Nashat

“…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) by Terzian, Meghrig Ohanes

“…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” by Naila Rabbani (291722)

“…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. …”

Scatter search metaheuristic for homology based protein structure prediction. (c2015) by Stamboulian, Mouses Hrag

“…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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AGEomics Biomarkers and Machine Learning—Realizing the Potential of Protein Glycation in Clinical Diagnostics by Naila Rabbani (291722)

“…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. …”

A Stochastic Newton-Raphson Method with Noisy Function Measurements by Saab, Khaled Kamal

“…The development of the proposed optimal algorithm is based on minimizing a stochastic performance index. …”
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Particle swarm optimization approach for protein structure prediction in the 3D HP model by Mansour, Nashat

“…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 new genetic algorithm approach for unit commitment by Mantawy, A.H.

“…A fitness function is constructed from the total operating cost of the generating units without penalty terms. …”
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Integrating genetic algorithms, tabu search, and simulatedannealing for the unit commitment problem by Mantawy, A.H.

“…The fitness function is constructed from the total operating cost of the generating units without penalty terms. …”
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A New Genetic-Based Tabu Search Algorithm For Unit Commitment Problem by Mantawy, A. H.

“…A fitness function is constructed from the total operating cost of the generating units without penalty terms. …”
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Integrating Genetic Algorithms, Tabu Search, And Simulated Annealing For The Unit Commitment Problem by Montawy, A.H.

“…The fitness function is constructed from the total operating cost of the generating units without penalty terms. …”
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Rigorous Phase Equilibrium Calculation Methods for Strong Electrolyte Solutions: The Isothermal Flash by Ilias K. Nikolaidis (9217172)

“…Based on the new approach, named Electrochemical Ionic Approach (EIA), two new numerical methods are presented; a successive substitution method similar to the classical Rachford-Rice method and a second-order one, which is based on Newton's method. The new algorithms are general and can be readily applied to mixtures of multiple solvents and one or multiple salts without any modifications. …”