-
Feeding Lab Protocols to AI With Private Knowledge Base
Private knowledge bases enable RAG in labs, letting AI answer protocol questions using your own documents while preserving data security and traceability.
-
MLflow Gradient Boosting Tutorial
Learn how MLflow enhances gradient boosting for tabular data with experiment tracking, model registry, champion/challenger aliases, and stable deployment.
-
This weeks top spatial transcriptomics paper – Week 31 🧬
Spatiotemporal single-cell multiomics map tumor ecosystem dynamics from seeding to metastasis, revealing microenvironment-driven cancer progression.
-
Spatial Transcriptomics: Assigning Spots to Cell Types
Spatial Transcriptomics reveals how spots mix signals from multiple cells, and how deconvolution and segmentation map spots to cell types and…
-
Digital Lab Audit Trail: What It Is and Why It Matters
Discover how digital lab audit trails and data lineage ensure data integrity, traceability, and compliant, trustworthy lab results.
-
Scanpy Pathway Analysis with decoupler
Leverage decoupler for Scanpy-ready pathway analysis and per-cell GSEA in AnnData to obtain interpretable pathway scores.
-
From Prompt to Paper: AI Scientist in‑Silico Loops
An AI scientist speeds up ideation, experimentation, and drafting in in-silico research loops, with self-reflection and responsible publishing.
-
This weeks top spatial transcriptomics paper Week 28 🧬
Spatial transcriptomics reveals AI-enabled biomarkers and activity-driven synapse changes across neuroscience and cancer, guiding precision medicine.
-
AI Knowledge Base for AI Models From Lab Protocols
Building an AI knowledge base for AI models from lab protocols enables an AI assistant to answer questions, cite sources, and…
-
MSigDB and GSEA Explained: A Primer on Molecular Signatures
Learn how MSigDB and GSEA turn gene activity into interpretable pathway scores, guiding cancer genomics research with NES and FDR.