Network models to enhance the translational impact of cross-species studies

JK Brynildsen, K Rajan, MX Henderson… - Nature Reviews …, 2023 - nature.com
Neuroscience studies are often carried out in animal models for the purpose of
understanding specific aspects of the human condition. However, the translation of findings …

Representing and extracting knowledge from single-cell data

IS Mihai, S Chafle, J Henriksson - Biophysical Reviews, 2024 - Springer
Single-cell analysis is currently one of the most high-resolution techniques to study biology.
The large complex datasets that have been generated have spurred numerous …

CIForm as a transformer-based model for cell-type annotation of large-scale single-cell RNA-seq data

J Xu, A Zhang, F Liu, L Chen… - Briefings in …, 2023 - academic.oup.com
Single-cell omics technologies have made it possible to analyze the individual cells within a
biological sample, providing a more detailed understanding of biological systems …

Whole brain alignment of spatial transcriptomics between humans and mice with BrainAlign

B Zhang, S Zhang, S Zhang - Nature Communications, 2024 - nature.com
The increasing utilization of mouse models in human neuroscience research places higher
demands on computational methods to translate findings from the mouse brain to the human …

[HTML][HTML] Application and prospects of single-cell and spatial omics technologies in woody plants

S Liang, Y Li, Y Chen, H Huang, R Zhou, T Ma - Forestry Research, 2023 - maxapress.com
Over the past decade, high-throughput sequencing and high-resolution single-cell
transcriptome sequencing technologies have undergone rapid development, leading to …

Cross-species transcriptomics reveals bifurcation point during the arterial-to-hemogenic transition

S Mo, K Qu, J Huang, Q Li, W Zhang, K Yen - Communications Biology, 2023 - nature.com
Hemogenic endothelium (HE) with hematopoietic stem cell (HSC)-forming potential emerge
from specialized arterial endothelial cells (AECs) undergoing the endothelial-to …

[HTML][HTML] SIMS: A deep-learning label transfer tool for single-cell RNA sequencing analysis

J Gonzalez-Ferrer, J Lehrer, A O'Farrell, B Paten… - Cell Genomics, 2024 - cell.com
Cell atlases serve as vital references for automating cell labeling in new samples, yet
existing classification algorithms struggle with accuracy. Here we introduce SIMS (scalable …

scSwinFormer: A Transformer-Based Cell-Type Annotation Method for scRNA-Seq Data Using Smooth Gene Embedding and Global Features

H Qin, X Shi, H Zhou - Journal of Chemical Information and …, 2024 - ACS Publications
Single-cell omics techniques have made it possible to analyze individual cells in biological
samples, providing us with a more detailed understanding of cellular heterogeneity and …

Cell type matching across species using protein embeddings and transfer learning

K Biharie, L Michielsen, MJT Reinders… - …, 2023 - academic.oup.com
Motivation Knowing the relation between cell types is crucial for translating experimental
results from mice to humans. Establishing cell type matches, however, is hindered by the …

Artificial intelligence and machine learning applications for cultured meat

ME Todhunter, S Jubair, R Verma, R Saqe… - arXiv preprint arXiv …, 2024 - arxiv.org
Cultured meat has the potential to provide a complementary meat industry with reduced
environmental, ethical, and health impacts. However, major technological challenges …