Article

CSLAN: Cross-Species Latent Alignment Network for Trauma-Related Cell-Type Classification

2025-06-12

Abstract excerpt

Understanding cellular identity and function across species is fundamental to deciphering conserved biological principles and translating insights from model organisms to human health. However, integrating single-cell transcriptomic data, particularly from resource-limited human studies, with comprehensive datasets from model organisms like mice remains a significant challenge due to evolutionary divergence and te...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work: 6e3efaf6-d7d8-5102-bf76-c9fb90fd442d
DOI: 10.1101/2025.06.09.655966

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

CSLAN: Cross-Species Latent Alignment Network for Trauma-Related Cell-Type ClassificationDOI 10.1101/2025.06.09.655966Read

Enhancement of Network Architecture Alignment in Comparative Single-Cell StudiesSemantic proximity Read

Deep learning enables cross-species annotation and attribution of ageing states in haematopoietic stem and immune cellsSemantic proximity Read

Species-Agnostic Transfer Learning for Cross-species Transcriptomics Data Integration without Gene OrthologySemantic proximity Read

Cell type matching across species using protein embeddings and transfer learningSemantic proximity Read

Unify: Learning Cellular Evolution with Universal Multimodal EmbeddingsSemantic proximity Read

Mouse-Geneformer: A Deep Learning Model for Mouse Single-Cell Transcriptome and Its Cross-Species UtilitySemantic proximity Read

Cross-Tissue Generalization of Rare Cell-Type Representations in Single-Cell Foundation Models: A Benchmark Using Public Reference AtlasesSemantic proximity Read

UniCell: Towards a Unified Solution for Cell Annotation, Nomenclature Harmonization, Atlas Construction in Single-Cell TranscriptomicsSemantic proximity Read

Transfer Learning Of Gene Expression Using ReactomeSemantic proximity Read

GeneCompass: Deciphering Universal Gene Regulatory Mechanisms with Knowledge-Informed Cross-Species Foundation ModelSemantic proximity Read

cFIT: Integration and transfer learning of single cell transcriptomes, illustrated by fetal brain cell developmentSemantic proximity Read

A deep-learning tool for species-agnostic integration of cancer cell statesSemantic proximity Read