ArticleACS omega2022
TransDTI: Transformer-Based Language Models for Estimating DTIs and Building a Drug Recommendation Workflow.
Article in ACS omega, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 40 papers, 1 of them a synthesis that pooled it.
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The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
40 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Protein Sequence Analysis landscape: A Systematic Review of Task Types, Databases, Datasets, Word Embeddings Methods, and Language Models.Database : the journal of biological databases and curation · 2025Pooled it
- A survey of transformer and LLM-based architectures, workflows, and systems in drug discovery.Journal of computer-aided molecular design · 2026Review
- Advancing bioinformatics with language models: components, applications, and perspectives.Briefings in bioinformatics · 2026Review
- Protein and ligand novelty in drug-target interaction prediction: a dual-encoder fusion strategy for more interpretable and generalizable modeling.BMC bioinformatics · 2026Article
- Large language models for bioinformatics.Quantitative biology (Beijing, China) · 2026Review
- Scaling Biomedical Text-Mining: Transformers, GenAI, and Drug Discovery.Methods in molecular biology (Clifton, N.J.) · 2026Article
- Repurposing AI for protein interactions and dynamics: opportunities, limitations, and lessons.Frontiers in bioinformatics · 2026Review
- DCGAT-DTI: dynamic cross-graph attention network for drug-target interaction prediction.Bioinformatics advances · 2026Article
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- AI and organoid platforms for brain-targeted theranostics.Theranostics · 2026Review
- Large language models in bioinformatics: a comprehensive survey.Frontiers in genetics · 2026Review
- AI-enabled language models (LMs) to large language models (LLMs) and multimodal large language models (MLLMs) in drug discovery and development.Journal of advanced research · 2025Review
- Data-driven strategies for drug repurposing: insights, recommendations, and case studies.Briefings in bioinformatics · 2025Article
- Pattern Recognition Algorithms in Pharmacogenomics and Drug Repurposing-Case Study: Ribavirin and Lopinavir.Pharmaceuticals (Basel, Switzerland) · 2025Review
- Advancing virulence factor prediction using protein language models.BMC biology · 2025Article
- QSAR and machine learning methods for prediction of albumin-ligand binding.Biophysical reviews · 2025Review
- Bridging artificial intelligence and biological sciences: a comprehensive review of large language models in bioinformatics.Briefings in bioinformatics · 2025Review
- Innovative Formulation Strategies for Biosimilars: Trends Focused on Buffer-Free Systems, Safety, Regulatory Alignment, and Intellectual Property Challenges.Pharmaceuticals (Basel, Switzerland) · 2025Review
- H2GnnDTI: hierarchical heterogeneous graph neural networks for drug-target interaction prediction.Bioinformatics (Oxford, England) · 2025Article
- Natural Language Processing Methods for the Study of Protein-Ligand Interactions.Journal of chemical information and modeling · 2025Review
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The identification of novel drug-target interactions is a labor-intensive and low-throughput process. In silico alternatives have proved to be of immense importance in assisting the drug discovery process. Here, we present TransDTI, a multiclass classification and regression workflow employing transformer-based language models to segregate interactions between drug-target pairs as active, inactive, and intermediate. The models were trained with large-scale drug-target interaction (DTI) data sets, which reported an improvement in performance in terms of the area under receiver operating characteristic (auROC), the area under precision recall (auPR), Matthew's correlation coefficient (MCC), and
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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.