-
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 regions.
-
Cell-Cell Communication in scRNA-seq
CellPhoneDB links cell types in scRNA-seq via receptor-ligand interactions, turning clustering into interpretable signaling insights.
-
Conformational AI after AlphaFold: From Motion to State
Conformational AI blends dynamics, state prediction, and design to move from static folds to ensembles and binder design.
-
SiLA 2, OPC UA, and the Modern Lab Stack
Modern Digital Labs rely on SiLA 2 and OPC UA to unify devices, enable interoperable automation, and improve traceability across LIMS,…
-
This weeks top spatial transcriptomics paper – Week 20 🧬
Eosinophils orchestrate gut remodeling and innate defense in mammalian reproduction, linking barrier immunity to fertility and maternal health.
-
GSEA for Single-Cell Data in Scanpy
GSEA adds a functional layer to single-cell analysis with Scanpy, enabling pathway insights from ranked cluster markers.
-
Hybrid Biology Models: Mechanistic Pathways Meet ML
Hybrid AI-plus-mechanistic modeling is converging, combining mechanistic pathways with machine learning for more accurate, interpretable translational research.
-
CRISPR Design Meets Foundation Models
Foundation models boost CRISPR guide ranking with context-aware on-target predictions and cell-type–aware off-target risk.
-
KEGG Pathway Analysis in R
Learn KEGG pathway analysis in R with clusterProfiler, enrichplot, and pathview to interpret gene lists and visualize enriched pathways.
-
Benchmarking Cell Atlases for Label Transfer
Hands-on guide to evaluating public cell atlases before production label transfer, focusing on annotation quality, batch diversity, and transferability.