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This week’s top spatial transcriptomics papers 🧬 Week 26
Spatial transcriptomics reveals a disease-associated motor neuron state in ALS and maps heart, reproductive biology, and cancer tissue atlases.
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Why paper processes hinder lab automation and paperless labs
A paperless laboratory uses ELN and LIMS to automate workflows, reduce errors, and speed up audits with structured data.
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Genomic Data Commons Data Portal: Data Types and Tools
The GDC Data Portal harmonizes cancer genomics data with a user-friendly UI, API access, and scalable tools to accelerate research.
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Databricks: Unified data catalog to fix fragmented lab data
In a digital lab, data scatter across ELNs, LIMS, and instruments. A unified data catalog on Databricks brings shared meaning, governance,…
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Foundation Models for Single-Cell Biology: Geneformer
Geneformer and foundation models unlock scalable single-cell biology by learning shared representations of cells and genes for annotation and perturbations.
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Building a knowledge base for AI models from lab protocols
Turning lab protocols into a machine-readable knowledge base powers AI assistants, boosts traceability, and cuts errors in digital labs.
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Spatial Omics in Neurodegenerative Drug & Biomarker Discovery
Spatial omics links gene and protein signals to tissue context, revealing biomarker candidates and drug targets in Alzheimer’s, Parkinson’s, and ALS.
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Encrpytion for Laboratory Data: A primer
By EVOBYTE Your partner for the digital lab In a modern digital lab, encryption is the simplest, most powerful step you…
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Predicting Antigen-Specific T Cells: An Overview
Explore practical workflows for predicting antigen-specific T cells, from TCR–pMHC modeling with NetTCR and TCRmodel2 to structure-based insights.
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Working with Patient Data: Anonymous or Pseudonymous?
An overview of anonymization and pseudonymization in the digital lab to protect privacy while enabling science.