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Our recent publications

Improving VAE based molecular representations for compound property prediction

Tevosyan A, Khondkaryan L, Khachatrian H, Tadevosyan G, Apresyan L, Babayan N, Stopper H, Navoyan Z. J Cheminform. 2022 Oct 14;14(1):69.

DOI: 10.1186/s13321-022-00648-x

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BARTSmiles: Generative Masked Language Models for Molecular Representations

Chilingaryan G, Tamoyan H, Tevosyan A, Babayan N, Khondkaryan L, Hambardzumyan K, Navoyan Z, Khachatrian H, Aghajanyan A. Machine Learning; Biomolecules: 2022. DOI: 10.48550/arXiv.2211.16349

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Datasets Construction and Development of QSAR Models for Predicting Micronucleus In Vitro and In Vivo Assay Outcomes

Khondkaryan, L.; Tevosyan, A.; Navasardyan, H.; Khachatrian, H.; Tadevosyan, G.; Apresyan, L.; Chilingaryan, G.; Navoyan, Z.; Stopper, H.; Babayan, N. Toxics 2023, 11, 785. DOI: 10.3390/toxics11090785

 

Other

Applications of machine learning in drug discovery and development

Vamathevan, J., Clark, D., Czodrowski, P. et al. . Nat Rev Drug Discov 18, 463–477 (2019). https://doi.org/10.1038/s41573-019-0024-5

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Non-clinical studies in the process of new drug development - Part II: Good laboratory practice, metabolism, pharmacokinetics, safety and dose translation to clinical studies

E.L. Andrade, A.F. Bento, J. Cavalli, S.K. Oliveira, R.C. Schwanke, J.M. Siqueira, C.S. Freitas, R. Marcon, J.B. Calixto Braz J Med Biol Res. 2016; 49(12): e5646. 

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A Review of Current In Silico Methods for Repositioning Drugs and Chemical Compounds

Binsheng He, Fangxing Hou, Changjing Ren, Pingping Bing and Xiangzuo Xiao. Front. Oncol., 22 July 2021 | https://doi.org/10.3389/fonc.2021.711225

 

Editorial: In silico Methods for Drug Design and Discovery

Simone Brogi, Teodorico Castro Ramalho, Kamil Kuca, José L. Medina-Franco and Marian Valko. Front. Chem., 07 August 2020 | https://doi.org/10.3389/fchem.2020.00612

 

Graph convolutional networks for computational drug development and discovery

Mengying Sun, Sendong Zhao, Coryandar Gilvary, Olivier Elemento, Jiayu Zhou, Fei Wang. 

Brief Bioinform​. 2020 May 21;21(3):919-935. doi: 10.1093/bib/bbz042.

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Drug discovery with explainable artificial intelligence

Jiménez-Luna, J., Grisoni, F. & Schneider, G. Drug discovery with explainable artificial intelligence. Nat Mach Intell 2, 573–584 (2020). https://doi.org/10.1038/s42256-020-00236-4

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Predicting Toxicity Properties through Machine Learning

Luz Adriana Borrero, Lilibeth Sanchez Guette, Enrique Lopez, Omar Bonerg, Pinedad Edgardo Buelvas Castro. Procedia Computer Science, Volume 170, 2020, Pages 1011-1016

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