GEN - Genetic Engineering and Biotechnology News

Tahoe, Arc Institute, and Biohub Join Forces on Massive Virtual Cell Dataset

The largest single cell perturbation dataset to-date will be generated and released open source in a new team effort.
Business Wire

NanoString Releases Single Cell Spatial Transcriptomics Dataset Highlighting Data Quality of CosMx Spatial Molecular Imager

SEATTLE--(BUSINESS WIRE)--NanoString Technologies, Inc. (NASDAQ: NSTG), a leading provider of life science tools for discovery and translational research, today announced a public release of new data ...
La Grande Observer

Vevo Therapeutics Open Sources Tahoe-100M, the World’s Largest Single-Cell Dataset, as the Inaugural Contribution to Arc Institute’s New Virtual Cell Atlas

300 million single cell atlas now accessible to the scientific community comprised of Vevo’s Tahoe-100M, mapping 60,000 drug-patient interactions, and Arc’s AI-curated scBaseCamp 200 million cell ...
Business Wire

Cellarity Releases Novel, Open-Source, Single-Cell Dataset and Invites the Machine Learning and Computational Biology Communities to Develop New Algorithms Capable of Learning ...

The dataset will be publicly available for a Kaggle competition presented at NeurIPS 2022 hosted by Open Problems in Single-Cell Analysis in collaboration with Chan Zuckerberg Initiative, Chan ...
EurekAlert!

Gene print-based cell subtypes annotation of human disease across heterogeneous datasets with gPRINT

(A) Selected human single-cell transcriptome profiles from HCL and other public datasets were utilized to train and validate gPRINT. The human single-cell data encompasses 159,302 cells from 26 ...
GEN

Xaira Therapeutics Releases Largest Perturb-Seq Dataset to Power the Virtual Cell

Ever since artificial intelligence (AI) drug developer Xaira Therapeutics launched in April 2024 with a jaw-dropping $1 billion in committed capital and a star-studded leadership lineup—including ...
JSTOR Daily

scMerge leverages factor analysis, stable expression, and pseudoreplication to merge multiple single-cell RNA-seq datasets

Concerted examination of multiple collections of single-cell RNA sequencing (RNA-seq) data promises further biological insights that cannot be uncovered with individual datasets. Here we present ...