Haoxiang Gao

Dec 22, 2024 | biorxiv.org | Chen Li |Haoxiang Gao |Haiyang Bian |Qing Chen

AbstractUnderstanding perturbations at the single-cell level is essential for unraveling cellular mechanisms and their implications in health and disease. The growing availability of biological data has driven the development of a variety of in silico perturbation methods designed for single-cell analysis, which offer a means to address many inherent limitations of experimental approaches.

Apr 28, 2024 | arxiv.org | Haoxiang Gao

arXiv:2404.18043 (cs) View PDF Subjects: Computation and Language (cs.CL); Machine Learning (cs.LG) Cite as: arXiv:2404.18043 [cs.CL] (or arXiv:2404.18043v1 [cs.CL] for this version) Submission history From: Haoxiang Gao [ view email] [v1] Sun, 28 Apr 2024 01:38:38 UTC (19 KB) Bibliographic Tools Bibliographic Explorer Toggle Bibliographic Explorer () Litmaps Toggle Litmaps (What is Litmaps?) scite.ai Toggle scite Smart Citations (What are Smart Citations?) Code, Data, Media Links to Code...