Drug Discovery and Molecular Medicine
Research on using LLMs for drug discovery, molecular modeling, and pharmaceutical development
Drug Discovery and Molecular Medicine
Research on Large Language Models in Drug Discovery and Molecular Medicine
GP-MoLFormer: Revolutionizing Molecular Generation
A Billion-Scale Foundation Model for Drug Discovery
AI-Powered Genetic Discovery
An intelligent agent that designs and optimizes biological experiments
Word Embeddings for Drug Discovery
Predicting Drug-Gene Relations Through NLP Analogy Tasks
MolX: Supercharging LLMs for Molecular Understanding
Bridging the gap between language models and chemical structures
Smarter Drug Discovery with LLMs
Enhancing AI-driven molecule generation through entropy-reinforced planning
Smarter Drug Discovery with AI
How LLMs Make Chemical Search More Efficient
AI-Powered Antimicrobial Discovery
LLMs Design Novel Antibacterial Peptides with 94% Success Rate
DrugAgent: Multi-Agent LLMs for Drug Discovery
Enhancing drug-target interaction prediction with collaborative AI reasoning
Enhancing Drug Discovery with LLMs
Aligning language models to generate structurally diverse molecules
AI-Powered Chemistry Discovery
LLMs as Catalysts for Novel Chemical Hypotheses
Bridging LLMs and Graph Data
Enhancing AI's ability to understand relational structures
Bridging Words and Molecules
Enhancing drug discovery through modular language models
Generalists vs. Specialists in Biomolecule Optimization
Evaluating the performance gap between LLMs and specialized solvers
Hierarchical Molecular Graphs in AI
Enhancing LLMs with multi-level molecular representations
Bridging Protein Language and Structure
Optimizing alignment between language and geometric models for better protein understanding
Unlocking Chemical Knowledge at Scale
AI-powered recognition of molecular structures from documents
DrugAgent: AI Collaboration for Drug Discovery
Automating pharmaceutical research through multi-agent LLM frameworks
M³-20M: Revolutionizing AI-Driven Drug Discovery
A massive multi-modal molecule dataset 71× larger than existing resources
Enhancing Molecule Generation with LLMs
A novel approach for multi-property molecular design
Optimizing AI for Drug Discovery
Refining Reinforcement Learning Approaches for Chemical Language Models
Protein Language Models Under Constraints
Evaluating large protein models in limited-data scenarios
AI-Powered Antibody Activity Prediction
Using Large Language Models to Accelerate Therapeutic Development
Mol-LLM: Revolutionizing Molecular Understanding
Building Smarter AI for Drug Discovery & Molecular Research
Omni-DNA: Revolutionizing Genomic AI
A unified foundation model for multi-task DNA analysis
Enhancing Molecular Analysis with Graph-Based In-Context Learning
A novel approach using Morgan fingerprints to improve molecular property prediction
Enhancing Protein Interaction Analysis with Uncertainty-Aware LLMs
Advancing precision medicine through more reliable AI predictions
Rediscovering Biology's Central Dogma with AI
How multilingual transfer in LLMs reveals fundamental biological patterns
Bridging Molecules and Language
Using AI to Solve Annotation Scarcity in Drug Discovery
Prot2Chat: Revolutionizing Protein Analysis
A multimodal approach fusing protein sequence, structure, and natural language
Revolutionizing Drug Interaction Prediction
How LLMs are transforming pharmaceutical safety assessments
LLM-Powered Drug Optimization
Fine-tuning language models to enhance drug development
Decoding DNA with AI
A Genomic Foundation Model for Long-Context DNA Analysis
MDCrow: AI-Powered Molecular Dynamics
Automating complex scientific workflows with LLM-based agents
AI-Powered Cancer Vaccine Enhancement
Automating adjuvant identification using Large Language Models
ControllableGPT: Reimagining LLMs for Drug Innovation
A novel architecture inspired by biological evolution for molecule optimization
HybriDNA: Advancing DNA Language Models
Combining Transformer and Mamba architectures for ultra-long DNA sequence analysis
Neural Vector Fields for Molecular Representation
Advancing computational biology through novel molecule modeling techniques
EquiLLM: Merging LLMs with 3D Spatial Intelligence
Combining large language models with geometric understanding for better 3D structure prediction
MOLLM: Revolutionizing Molecular Design
Combining LLMs and Expert Knowledge for Multi-Objective Optimization
Enhancing LLM Reasoning with Flow-of-Options
Systematic diversity in AI reasoning pathways leads to major performance gains
Breaking GenAI's Efficiency Barrier
A novel approach to reduce data hunger in generative AI models
K-Paths: Revolutionizing Drug Discovery
A novel path-based approach to mining biomedical knowledge graphs
Revolutionizing Molecule Design with LLMs
Using AI to optimize multiple molecular properties simultaneously
Mol-LLaMA: Revolutionizing Molecular Understanding
Expanding Language Models for General-Purpose Molecular Assistance
AI Revolution in Catalyst Discovery
From Classical Machine Learning to Large Language Models
AI Revolutionizing Drug Discovery
An autonomous agent that accelerates pharmaceutical innovation
ChemHTS: Smarter Chemical AI Tools
Hierarchical Tool Stacking for Enhanced Chemical Analysis
Revolutionizing Peptide Identification with AI
PDeepPP: A Hybrid Transformer-CNN Model for Advanced Protein Analysis
AI-Powered Materials Discovery Revolution
Automating synthesis recipes with expert-level AI evaluation
BioMaze: Solving the Pathway Puzzle
Benchmarking LLM reasoning in complex biological systems
Bridging Protein Sequence and Structure
A Novel Deep Learning Framework Combining Language Models with Spatial Analysis
Protein LLMs: Transforming Biological Research
The first comprehensive taxonomy of protein language models
Smarter Drug Discovery with AI Collaboration
Using RAG-Enhanced LLM Agents to Transform Pharmaceutical Research
Illuminating Biological Pathways
AI-Powered Framework for Targeted Pathway Discovery
Quantum-Enhanced Transformer Models
Optimizing molecular generation through quantized self-attention
AI-Powered Cardiac Protein Analysis
Using LLMs to identify SERCA-binding proteins in heart tissue
AI-Powered Materials Discovery
Using Large Language Models to Revolutionize Chemical Search
ChatMol: AI-Powered Molecule Design
Revolutionizing drug discovery with language models enhanced by numerical capabilities
AI-Powered Drug Discovery
Knowledge-Distilled LLMs for Explainable Drug Recommendations
Advancing Protein Structure Analysis
The New Frontier in Protein Structure Tokenization
Revolutionizing Materials Discovery with LLMs
Using large language models to enhance multimodal fusion for material properties prediction
AI-Enhanced Drug Design
Improving drug discovery through LLM-human collaboration
AI-Powered Drug Combination Predictions
Bridging preclinical data to clinical outcomes with multimodal AI
Connecting Molecules to AI Language Models
Enabling LLMs to understand molecular structures without fine-tuning
MultiMol: Revolutionizing Drug Discovery
Leveraging Collaborative LLMs for Efficient Molecular Design
Enhanced Molecular Understanding Through Multi-View Learning
Improving LLMs for molecular interpretation using complementary structural views
Supercharging Optimization with LLMs
How AI learns from past experiments to accelerate scientific discovery
AI-Powered Chemical Reaction Extraction
Automating the conversion of chemical reaction images to structured data
LLMs as Chemical Reasoning Engines
Combining AI with traditional search algorithms for expert-level chemistry
AI-Powered Pharmaceutical Design
Using LLMs to Revolutionize Drug Formulation Development
AI-Powered Drug Discovery Breakthrough
Using LLMs to Generate Synthesizable Molecules
Unlocking Chemical Knowledge
AI-Powered Recognition of Complex Chemical Structure Templates
Unified 3D Modeling for Biology & Medicine
Bridging Generation & Understanding through Autoregressive Learning
AI-Powered Antibiotic Discovery
Using LLMs and Knowledge Graphs to accelerate pharmaceutical research
AI-Powered Pharmaceutical Formulation
Accelerating drug development with intelligent formulation pathways
Enhancing Drug Discovery with Dual-Modal AI
Combining language models to better predict molecular interactions
Virtual Pharma Revolution
AI Agents Transforming Drug Discovery
Unlocking Scientific Knowledge for LLMs
Reinforcement Learning with Database Feedback for Enhanced Scientific Capabilities
Revolutionizing Protein Engineering with AI
Target-aware protein binder generation without 3D structural constraints
AI Revolutionizing Drug Development
TxGemma: Bringing LLM Efficiency to Therapeutic Discovery
Scaling GNNs for Materials Science Breakthroughs
Optimizing Graph Neural Networks for Atomistic Modeling
Enhancing Chemical Reaction Optimization with LLMs
Leveraging Language Models to Improve Bayesian Optimization in Low-Data Settings
ProtFlow: Revolutionizing Protein Design
Accelerating protein sequence generation with flow matching and compressed embeddings
Combating Hallucinations in Molecular AI
A metric-driven approach to improving LLM reliability for drug research
