pBRICS: a novel fragmentation method for explainable property prediction of drug-like small molecules
Generative artificial intelligence algorithms have shown to be successful in exploring large
chemical spaces and designing novel and diverse molecules. There has been considerable …
chemical spaces and designing novel and diverse molecules. There has been considerable …
De Novo Design of Molecules with Multiaction Potential from Differential Gene Expression using Variational Autoencoder
N Pravalphruekul, M Piriyajitakonkij… - Journal of chemical …, 2023 - ACS Publications
The modulating effect of chemical compounds and therapeutics on gene transcription is well-
reported and has been intensively studied for both clinical and research purposes …
reported and has been intensively studied for both clinical and research purposes …
[HTML][HTML] TransGEM: a molecule generation model based on Transformer with gene expression data
Y Liu, H Yu, X Duan, X Zhang, T Cheng, F Jiang… - …, 2024 - academic.oup.com
Motivation It is difficult to generate new molecules with desirable bioactivity through ligand-
based de novo drug design, and receptor-based de novo drug design is constrained by …
based de novo drug design, and receptor-based de novo drug design is constrained by …
RM-GPT: Enhance the comprehensive generative ability of molecular GPT model via LocalRNN and RealFormer
W Fan, Y He, F Zhu - Artificial Intelligence in Medicine, 2024 - Elsevier
Due to the surging of cost, artificial intelligence-assisted de novo drug design has
supplanted conventional methods and become an emerging option for drug discovery …
supplanted conventional methods and become an emerging option for drug discovery …
Target-specific novel molecules with their recipe: Incorporating synthesizability in the design process
Application of Artificial intelligence (AI) in drug discovery has led to several success stories
in recent times. While traditional methods mostly relied upon screening large chemical …
in recent times. While traditional methods mostly relied upon screening large chemical …
Deep Learning in Computational Biology: Advancements, Challenges, and Future Outlook
S Kumar, D Guruparan, P Aaron, P Telajan… - arXiv preprint arXiv …, 2023 - arxiv.org
Deep learning has become a powerful tool in computational biology, revolutionising the
analysis and interpretation of biological data over time. In our article review, we delve into …
analysis and interpretation of biological data over time. In our article review, we delve into …
GexMolGen: Cross-modal Generation of Hit-like Molecules via Large Language Model Encoding of Gene Expression Signatures
The design of custom drugs with specific biological activity is a extremely difficult task, but it
holds the potential to generate molecules without the discovery of target genes, beyond the …
holds the potential to generate molecules without the discovery of target genes, beyond the …