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. …”

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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LNCRI: Long Non-Coding RNA Identifier in Multiple Species by Saleh Musleh (15279190)

“…<p>The pervasive nature of long non-coding RNA (lncRNA) transcription in the mammalian genomes has changed our protein-centric view of genomes. But the identification of lncRNAs is an important task to discover their functional role in species. …”

Single-Cell Transcriptome Analysis Highlights a Role for Neutrophils and Inflammatory Macrophages in the Pathogenesis of Severe COVID-19 by Hibah Shaath (5599658)

Scatter search for homology modeling by Mansour, Nashat

“…The metaheuristic optimizes the initial poor alignments and uses fitness functions. We assess our algorithm on a number of proteins whose structures are present in the Protein Data Bank and which have been used in previous literature. …”
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Structural alignment. (c2006) by Kazma, Layal

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Blood-Based Proteomic Profiling Identifies Potential Biomarker Candidates and Pathogenic Pathways in Dementia by Hanan Ehtewish (17149825)

“…We used a high-throughput proximity extension immunoassay to quantify 1090 proteins in 122 participants (22 with dementia, 64 with mild cognitive impairment (MCI), and 36 controls with normal cognitive function). …”

Exploring the Dynamic Interplay of Deleterious Variants on the RAF1–RAP1A Binding in Cancer: Conformational Analysis, Binding Free Energy, and Essential Dynamics by Abbas Khan (5141000)

“…Integrated machine learning algorithms showed that among the 134 mutations reported for these 2 proteins, only 13 and 35 were classified as deleterious mutations in <i>RAF1</i> and <i>RAP1P</i>, respectively. …”