Cargando…
ScLSTM: single-cell type detection by siamese recurrent network and hierarchical clustering
MOTIVATION: Categorizing cells into distinct types can shed light on biological tissue functions and interactions, and uncover specific mechanisms under pathological conditions. Since gene expression throughout a population of cells is averaged out by conventional sequencing techniques, it is challe...
Autores principales: | Jiang, Hanjing, Huang, Yabing, Li, Qianpeng, Feng, Boyuan |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10629177/ https://www.ncbi.nlm.nih.gov/pubmed/37932672 http://dx.doi.org/10.1186/s12859-023-05494-8 |
Ejemplares similares
-
Improving the Community Question Retrieval Performance Using Attention-Based Siamese LSTM
por: Othman, Nouha, et al.
Publicado: (2020) -
Siamese hierarchical feature fusion transformer for efficient tracking
por: Dai, Jiahai, et al.
Publicado: (2022) -
Siamese Neural Networks for Class Activity Detection
por: Li, Hang, et al.
Publicado: (2020) -
SiamHAS: Siamese Tracker with Hierarchical Attention Strategy for Aerial Tracking
por: Liu, Faxue, et al.
Publicado: (2023) -
SiamHSFT: A Siamese Network-Based Tracker with Hierarchical Sparse Fusion and Transformer for UAV Tracking
por: Hu, Xiuhua, et al.
Publicado: (2023)