Article

How do Large Language Models understand Genes and Cells

2024-03-27

Abstract excerpt

Researching genes and their interactions is crucial for deciphering the fundamental laws of biological activity, advancing disease treatment, drug discovery and so on. Large language Models (LLMs), with their profound text comprehension and generation capabilities, have made significant strides across various natural science fields. However, their application in cell biology remains notably scarce. To alleviate th...

Topics

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

Identifiers and source

Literature Corpus work: aefbff94-488a-5bcd-86db-c2bfc9818739
DOI: 10.1101/2024.03.23.586383

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

How do Large Language Models understand Genes and CellsDOI 10.1101/2024.03.23.586383Read

Language may be all omics needs: Harmonizing multimodal data for omics understanding with CellHermesSemantic proximity Read

Toward mastering the cell language by learning to generateSemantic proximity Read

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

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

On Using Large Language Models to Understand the Language of LifeSemantic proximity Read

CellTosg2Sequence: A Unified Text-Omics-Signaling-Graph Large Language Model for Single-Cell AnalysisSemantic proximity Read

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

Cell-Graph Compass: Modeling Single Cells with Graph Structure Foundation ModelSemantic proximity Read

scGenePT: Is language all you need for modeling single-cell perturbations?Semantic proximity Read

Geometric Representations of Knowledge Inside Biological Large Language Models: an Empirical AnalysisSemantic proximity Read

Genolator: A Multimodal Large Language Model Fusing Natural Language, Genomic, and Structural Tokens for Protein Function InterpretationSemantic proximity Read

Generative single-cell transcriptomics via large language modelsSemantic proximity Read