G
Georgia Melagraki
Researcher at Hellenic Military Academy
Publications - 99
Citations - 2730
Georgia Melagraki is an academic researcher from Hellenic Military Academy. The author has contributed to research in topics: Quantitative structure–activity relationship & Cheminformatics. The author has an hindex of 26, co-authored 89 publications receiving 2128 citations. Previous affiliations of Georgia Melagraki include University of Cyprus & National Technical University of Athens.
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Journal ArticleDOI
Synthesis and evaluation of the antioxidant and anti-inflammatory activity of novel coumarin-3-aminoamides and their alpha-lipoic acid adducts
Georgia Melagraki,Antreas Afantitis,Olga Igglessi-Markopoulou,Anastasia Detsi,Maria Koufaki,Christos Kontogiorgis,Dimitra Hadjipavlou-Litina +6 more
TL;DR: In the present work a series of novel coumarin-3-carboxamides and their hybrids with the alpha-lipoic acid were designed, synthesized and tested as potent antioxidant and anti-inflammatory agents.
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Collaborative development of predictive toxicology applications
Barry Hardy,Nicki Douglas,Christoph Helma,Micha Rautenberg,Nina Jeliazkova,Vedrin Jeliazkov,Ivelina Nikolova,Romualdo Benigni,Olga Tcheremenskaia,Stefan Kramer,Tobias Girschick,Fabian Buchwald,Jörg Wicker,Andreas Karwath,Martin Gütlein,Andreas Maunz,Haralambos Sarimveis,Georgia Melagraki,Antreas Afantitis,Pantelis Sopasakis,David Gallagher,Vladimir Poroikov,Dmitry Filimonov,Alexey V. Zakharov,Alexey Lagunin,Tatyana A. Gloriozova,Sergey V. Novikov,Natalia Skvortsova,D. S. Druzhilovsky,Sunil Chawla,Indira Ghosh,Surajit Ray,Hitesh Patel,Sylvia Escher +33 more
TL;DR: Because of the extensible nature of the standardised Framework design, barriers of interoperability between applications and content are removed, as the user may combine data, models and validation from multiple sources in a dependable and time-effective way.
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Ligand-based virtual screening procedure for the prediction and the identification of novel β-amyloid aggregation inhibitors using Kohonen maps and Counterpropagation Artificial Neural Networks.
Antreas Afantitis,Georgia Melagraki,Panayiotis A. Koutentis,Haralambos Sarimveis,George Kollias +4 more
TL;DR: An in silico model to predict the inhibition of β-amyloid aggregation by small organic molecules is developed and a search for optimized pharmacophore patterns by insertions, substitutions, and ring fusions of pharmacophoric substituents of the main building block scaffolds is described.
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A novel QSAR model for predicting induction of apoptosis by 4-aryl-4H-chromenes.
Antreas Afantitis,Georgia Melagraki,Haralambos Sarimveis,Panayiotis A. Koutentis,John Markopoulos,Olga Igglessi-Markopoulou +5 more
TL;DR: A linear quantitative structure-activity relationship (QSAR) model is presented for modeling and predicting induction of apoptosis by 4-aryl-4H-chromenes and the domain of applicability which indicates the area of reliable predictions is defined.
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Nanotechnology and artificial intelligence to enable sustainable and precision agriculture.
TL;DR: In this article, the convergence of precision agriculture, in which farmers respond in real-time to changes in crop growth with nanotechnology and artificial intelligence, offers exciting opportunities for sustainable food production.