Agents for Drug Discovery: From Target to Molecule
Drug discovery is the highest-value application of agentic omics. Agents can orchestrate the entire pipeline from target identification through lead optimization, dramatically compressing timelines.
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Agentic Omics
Building Biological Tool-Use Agents: Architecture and Patterns
A practical guide to building agentic systems for omics research. What tools do agents need? How do you handle the unique challenges of biological data? What does a reference architecture look like?
The Agentic Omics Vision: LLMs Meet Domain-Specific AI
The central thesis of this series: Agentic Omics combines LLM reasoning with domain-specific biological AI models to create autonomous systems capable of end-to-end biological discovery.
What Is Agentic AI? From Chatbots to Autonomous Scientific Agents
Agentic AI is not just LLMs answering questions — it's AI systems that autonomously plan, reason, use tools, and execute multi-step scientific workflows. This post defines the paradigm and surveys its emergence in …
Single-Cell Multi-Omics: The Cellular Resolution Revolution
Single-cell technologies now measure multiple omics layers simultaneously in individual cells. AI models for single-cell multi-omics are enabling unprecedented resolution in understanding cellular heterogeneity, …
AI for Phenomics: When Images Meet Molecules
Phenomics bridges the molecular and the visible—using high-throughput imaging, clinical phenotypes, and electronic health records to connect genotype to phenotype. AI is central to this effort.
AI for Metagenomics: Decoding the Microbiome
How deep learning and transformer models are transforming metagenomics, from assembly and taxonomic classification to predicting microbiome-disease associations and antibiotic resistance.
AI for Metabolomics: The Chemical Fingerprint of Life
Metabolomics is the least 'language-model-ready' omics field, yet deep learning is transforming metabolite identification, pathway analysis, and biomarker discovery.
AI for Proteomics: From AlphaFold to Protein Design
Protein AI is the most mature omics AI field. But structure prediction was just the beginning—the frontier is now protein design, function prediction, and interaction modeling.
AI for Transcriptomics: Understanding Gene Expression at Scale
Exploring the rise of single-cell foundation models like scGPT and Geneformer, spatial transcriptomics, and how transformer architectures are deciphering the complex language of gene expression.
