Article

CellFM: a large-scale foundation model pre-trained on transcriptomics of 100 million human cells

2024-06-06

Abstract excerpt

The rapid evolution of single-cell sequencing technologies has facilitated precise transcriptomics profiling at the single-cell level, shedding light on the intricate heterogeneity within cellular populations. Despite these advances, the inherent diversity of cells and data challenges such as noise, batch effects, and sparsity, underscores the pressing need for a unified model to learn and represent cellular state...

Topics

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

Identifiers and source

Literature Corpus work: 2de7acfb-43f3-5ed3-ac14-a3ced968e9db
DOI: 10.1101/2024.06.04.597369

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

CellFM: a large-scale foundation model pre-trained on transcriptomics of 100 million human cellsDOI 10.1101/2024.06.04.597369Read

Large Scale Foundation Model on Single-cell TranscriptomicsSemantic proximity Read

Scaling Dense Representations for Single Cell with Transcriptome-Scale ContextSemantic proximity Read

scKEPLM: Knowledge enhanced large-scale pre-trained language model for single-cell transcriptomicsSemantic proximity Read

TabVI: Leveraging Lightweight Transformer Architectures to Learn Biologically Meaningful Cellular RepresentationsSemantic proximity Read

scLong: A Billion-Parameter Foundation Model for Capturing Long-Range Gene Context in Single-Cell TranscriptomicsSemantic proximity Read

Benchmarking single-cell foundation models in a zero-shot settingSemantic proximity Read

scLong: A Billion-Parameter Foundation Model for Capturing Long-Range Gene Context in Single-Cell TranscriptomicsSemantic proximity Read

scGenAI: A generative AI platform with biological context embedding of multimodal features enhances single cell state classificationSemantic proximity Read

Tokenizing single-cell transcriptomes as a native language for large language modelsSemantic proximity Read

Scaling Large Language Models for Next-Generation Single-Cell AnalysisSemantic proximity Read

RegFormer: A Single-Cell Foundation Model Powered by Gene Regulatory HierarchiesSemantic proximity Read

Harnessing the Power of Single Cell Large Language Models with Parameter Efficient Fine-Tuning using scPEFTSemantic proximity Read