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Showing 1–9 of 9 results

Advanced filters: Author: Maria Brbic Clear advanced filters

Toward universal cell embeddings: integrating single-cell RNA-seq datasets across species with SATURN

SATURN performs cross-species integration and analysis using both single-cell gene expression and protein representations generated by protein language models.

Yanay Rosen
Maria Brbić
Jure Leskovec
ResearchOpen Access16 Feb 2024
Nature Methods

Volume: 21, P: 1492-1500
Systema: a framework for evaluating genetic perturbation response prediction beyond systematic variation

An evaluation framework isolates perturbation-specific effects in perturbation datasets.

Ramon Viñas Torné
Maciej Wiatrak
Maria Brbić
ResearchOpen Access25 Aug 2025
Nature Biotechnology

P: 1-10
Annotation of spatially resolved single-cell data with STELLAR

STELLAR (spatial cell learning) is a geometric deep learning model that works with spatially resolved single-cell datasets to both assign cell types in unannotated datasets based on a reference dataset and discover new cell types.

Maria Brbić
Kaidi Cao
Jure Leskovec
Research24 Oct 2022
Nature Methods

Volume: 19, P: 1411-1418
Leveraging the Cell Ontology to classify unseen cell types

Classifying cells into unseen cell types remains challenging in scRNA-seq analysis. Here we show that Cell Ontology enables an accurate classification of unseen cell types through considering the cell type relationships in the Cell Ontology graph.

Sheng Wang
Angela Oliveira Pisco
Russ B. Altman
ResearchOpen Access21 Sept 2021
Nature Communications

Volume: 12, P: 1-11
Organization of the human intestine at single-cell resolution

Intestinal cell types are organized into distinct neighbourhoods and communities within the healthy human intestine, with distinct immunological niches.

John W. Hickey
Winston R. Becker
Michael Snyder
ResearchOpen Access19 Jul 2023
Nature

Volume: 619, P: 572-584
MARS: discovering novel cell types across heterogeneous single-cell experiments

MARS uses a meta-learning strategy for annotating known cell types and identifying novel ones across single-cell RNA-seq datasets.

Maria Brbić
Marinka Zitnik
Jure Leskovec
Research19 Oct 2020
Nature Methods

Volume: 17, P: 1200-1206
Mammary intraepithelial lymphocytes and intestinal inputs shape T cell dynamics in lactogenesis

Here Ramanan and colleagues provide an analysis of mammary T cells during late pregnancy and lactation. This revealed an increase in intraepithelial lymphocytes in the lactating mammary gland, which was driven by thymic and intestinal inputs and was sensitive to changes in the microbiota

Abigail Jaquish
Eleni Phung
Deepshika Ramanan
Research29 Jul 2025
Nature Immunology

Volume: 26, P: 1411-1422
Towards multimodal foundation models in molecular cell biology

The development of multimodal foundation models, pretrained on diverse omics datasets, to unravel the intricate complexities of molecular cell biology is envisioned.

Haotian Cui
Alejandro Tejada-Lapuerta
Bo Wang
Reviews16 Apr 2025
Nature

Volume: 640, P: 623-633
A synthesis of bacterial and archaeal phenotypic trait data

Joshua S. Madin
Daniel A. Nielsen
Mark Westoby
ResearchOpen Access05 Jun 2020
Scientific Data

Volume: 7, P: 1-8