-
Cluster TCRs from 10x with TCRdist
Cluster TCRs from 10x data using TCRdist to group related receptors by similarity, turning exact clonotypes into biologically meaningful clusters.
-
Spatial Transcriptomics Meets scRNA-seq: Seurat & Scanpy
Learn to integrate spatial transcriptomics with scRNA-seq using Seurat and Scanpy for richer tissue maps.
-
Digital lab essentials: Audit trails and data lineage
Trust in modern digital labs comes from transparent records: audit trails show who did what, when, and why, while data lineage…
-
Spatial transcriptomics: practical intro for data scientists
Spatial transcriptomics links gene expression to tissue architecture, highlighting SVGs and cellular neighborhoods for data scientists.
-
Quality Criteria for Laboratory Databases: A Primer
Quality metrics, governance, and security criteria for trusted laboratory databases in the digital lab.
-
Best Free Spatial Omics Datasets: IHC, WSIs & Multi-Omics
Open spatial omics datasets for benchmarking: HuBMAP, SODB, METASPACE, GDC, and HPA—covering IHC, WSIs, and multi-omics.
-
AI-powered lab reports: turning results into conversations
In a Digital Lab, turn static PDFs into living conversations with an AI Assistant that explains terms and speeds customer support.
-
Spatial Transcriptomics: Assigning Cell Types in Tissue
Spatial Transcriptomics often mixes signals from neighboring cells. Learn to assign cell types and regions using deconvolution and reference maps.
-
Foundation Models for Cell Biology: An Overview
Foundation models for cell biology unlock fast, cross-dataset insights from massive single-cell data, enabling rapid annotation and perturbation ideas.
-
Digital Twin Models for the Laboratory: Turning HPLC Data into Digital Products
A Laboratory Digital Twin learns from rich analytical records—especially from HPLC—and becomes a digital product that optimizes methods and shortens development…