ArticleFrontiers in pharmacology2020
Molecular Generation for Desired Transcriptome Changes With Adversarial Autoencoders.
Article in Frontiers in pharmacology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
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Who cites it
19 citing papers in PubMed, 42 citations in OpenAlex.
- AET5: A transcriptome-guided molecular generation framework with contrastive self-supervised learning.PLoS computational biology · 2026Article
- Target identification and assessment in the era of AI.Nature reviews. Drug discovery · 2026Review
- Multiscale analysis and optimal glioma therapeutic candidate discovery using the CANDO platform.Journal of cheminformatics · 2026Article
- Transcriptome-conditioned molecule generation via gene interaction-aware fragment modeling with a GPT-based architecture.Scientific reports · 2025Article
- Precision cardiovascular medicine: shifting the innovation paradigm.Frontiers in science · 2025Article
- GexMolGen: cross-modal generation of hit-like molecules via large language model encoding of gene expression signatures.Briefings in bioinformatics · 2024Article
- Deep representation learning of chemical-induced transcriptional profile for phenotype-based drug discovery.Nature communications · 2024Article
- nach0: multimodal natural and chemical languages foundation model.Chemical science · 2024Article
- TransGEM: a molecule generation model based on Transformer with gene expression data.Bioinformatics (Oxford, England) · 2024Article
- GLDM: hit molecule generation with constrained graph latent diffusion model.Briefings in bioinformatics · 2024Article
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- Deep learning facilitates multi-data type analysis and predictive biomarker discovery in cancer precision medicine.Computational and structural biotechnology journal · 2023Review
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- Deep Learning Applied to Ligand-Based De Novo Drug Design.Methods in molecular biology (Clifton, N.J.) · 2022Review
- FAME: Fragment-based Conditional Molecular Generation for Phenotypic Drug Discovery.Proceedings of the ... SIAM International Conference on Data Mining. SIAM International Conference on Data Mining · 2022Article
- A Deep-Learning Proteomic-Scale Approach for Drug Design.Pharmaceuticals (Basel, Switzerland) · 2021Article
- Generative chemistry: drug discovery with deep learning generative models.Journal of molecular modeling · 2021Review
- Application of lung microphysiological systems to COVID-19 modeling and drug discovery: a review.Bio-design and manufacturing · 2021Review
- The Advent of Generative Chemistry.ACS medicinal chemistry letters · 2020Article
Corrections and comments
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Gene expression profiles are useful for assessing the efficacy and side effects of drugs. In this paper, we propose a new generative model that infers drug molecules that could induce a desired change in gene expression. Our model-the Bidirectional Adversarial Autoencoder-explicitly separates cellular processes captured in gene expression changes into two feature sets: those
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.