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ORCIDRamil I. Nugmanov
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2020 – today
- 2024
[j12]Ramil I. Nugmanov
:
PaCh (Packed Chemicals): Computationally Effective Binary Format for Chemical Structure Encoding. J. Chem. Inf. Model. 64(8): 3173-3179 (2024)- [c1]Alessio Fallani, José Antonio Arjona-Medina, Konstantin Chernichenko, Ramil I. Nugmanov, Jörg Kurt Wegner, Alexandre Tkatchenko:
Atom-Level Quantum Pretraining Enhances the Spectral Perception of Molecular Graphs in Graphormer. AIDD@ICANN 2024: 71-81 - [i2]Aline Hartgers, Ramil I. Nugmanov, Kostiantyn Chernichenko, Jörg Kurt Wegner:
ReacLLaMA: Merging chemical and textual information in chemical reactivity AI models. CoRR abs/2401.17267 (2024) - [i1]Jose A. Arjona-Medina, Ramil I. Nugmanov:
Analysis of Atom-level pretraining with Quantum Mechanics (QM) data for Graph Neural Networks Molecular property models. CoRR abs/2405.14837 (2024) - 2023
- [j11]Paulo Neves, Kelly McClure, Jonas Verhoeven, Natalia Dyubankova, Ramil I. Nugmanov, Andrey Gedich, Sairam Menon, Zhicai Shi, Jörg K. Wegner:
Global reactivity models are impactful in industrial synthesis applications. J. Cheminformatics 15(1): 20 (2023) - [j10]Paulo Neves, Kelly McClure, Jonas Verhoeven, Natalia Dyubankova, Ramil I. Nugmanov, Andrey Gedich, Sairam Menon, Zhicai Shi, Jörg K. Wegner:
Correction: Global reactivity models are impactful in industrial synthesis applications. J. Cheminformatics 15(1): 30 (2023) - 2022
- [j9]Timur Gimadiev, Ramil I. Nugmanov, Aigul Khakimova, Adeliya Fatykhova, Timur I. Madzhidov, Pavel Sidorov, Alexandre Varnek:
CGRdb2.0: A Python Database Management System for Molecules, Reactions, and Chemical Data. J. Chem. Inf. Model. 62(9): 2015-2020 (2022) - [j8]Ramil I. Nugmanov, Natalia Dyubankova, Andrey Gedich, Jörg Kurt Wegner:
Bidirectional Graphormer for Reactivity Understanding: Neural Network Trained to Reaction Atom-to-Atom Mapping Task. J. Chem. Inf. Model. 62(14): 3307-3315 (2022) - 2021
- [j7]Timur Gimadiev, Ramil I. Nugmanov, Dinar Batyrshin, Timur I. Madzhidov, Satoshi Maeda, Pavel Sidorov, Alexandre Varnek:
Combined Graph/Relational Database Management System for Calculated Chemical Reaction Pathway Data. J. Chem. Inf. Model. 61(2): 554-559 (2021) - [j6]Dmitry V. Zankov, Mariia Matveieva, Aleksandra V. Nikonenko, Ramil I. Nugmanov, Igor I. Baskin, Alexandre Varnek, Pavel G. Polishchuk, Timur I. Madzhidov:
QSAR Modeling Based on Conformation Ensembles Using a Multi-Instance Learning Approach. J. Chem. Inf. Model. 61(10): 4913-4923 (2021)
2010 – 2019
- 2019
- [j5]Ramil I. Nugmanov, Ravil N. Mukhametgaleev, Tagir Akhmetshin, Timur Gimadiev, Valentina A. Afonina, Timur I. Madzhidov, Alexandre Varnek:
CGRtools: Python Library for Molecule, Reaction, and Condensed Graph of Reaction Processing. J. Chem. Inf. Model. 59(6): 2516-2521 (2019) - [j4]Dmitry V. Zankov, Timur I. Madzhidov, Asima I. Rakhimbekova, Timur Gimadiev, Ramil I. Nugmanov, Marina A. Kazymova, Igor I. Baskin, Alexandre Varnek:
Conjugated Quantitative Structure-Property Relationship Models: Application to Simultaneous Prediction of Tautomeric Equilibrium Constants and Acidity of Molecules. J. Chem. Inf. Model. 59(11): 4569-4576 (2019) - 2018
- [j3]Timur Gimadiev, Timur I. Madzhidov, Ramil I. Nugmanov, Igor I. Baskin, Igor S. Antipin, Alexandre Varnek:
Assessment of tautomer distribution using the condensed reaction graph approach. J. Comput. Aided Mol. Des. 32(3): 401-414 (2018) - 2017
- [j2]Pavel G. Polishchuk, Timur I. Madzhidov, Timur Gimadiev, Andrey Bodrov, Ramil I. Nugmanov, Alexandre Varnek:
Structure-reactivity modeling using mixture-based representation of chemical reactions. J. Comput. Aided Mol. Des. 31(9): 829-839 (2017) - 2016
- [j1]Arkadii I. Lin, Timur I. Madzhidov, Olga Klimchuk, Ramil I. Nugmanov, Igor S. Antipin, Alexandre Varnek:
Automatized Assessment of Protective Group Reactivity: A Step Toward Big Reaction Data Analysis. J. Chem. Inf. Model. 56(11): 2140-2148 (2016)
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