Results 251 to 260 of about 1,141,381 (319)
Enhancing Spatial Transcriptomics via Spatially Constrained Matrix Decomposition with EDGES
Imaging‐based spatial transcriptomics technologies are currently limited by their restricted gene detection capacity and low measurement accuracy. Moreover, the insufficient integration of spatial context and single‐cell reference data poses a significant challenge for comprehensive data analysis.
Jinyue Zhao +5 more
wiley +1 more source
Tsallis Entropy in Consecutive <i>k</i>-out-of-<i>n</i> Good Systems: Bounds, Characterization, and Testing for Exponentiality. [PDF]
Alqefari AA, Alomani G, Kayid M.
europepmc +1 more source
Multiscale Cell–Cell Interactive Spatial Transcriptomics Analysis
In this study, we present the MultiScale Cell‐Cell Interactive Spatial Transcriptomics Analysis method, which unites the strengths of spatially resolved deep learning techniques with a topological representation of multi‐scale cell‐cell similarity relations.
Sean Cottrell, Guo‐Wei Wei
wiley +1 more source
Maximum likelihood estimation of log-affine models using detailed-balanced reaction networks. [PDF]
Henriksson O +3 more
europepmc +1 more source
A prior knowledge‐guided diffusion model augmented by physics‐constrained active learning is developed to design high‐asymmetry terahertz metamaterials. Trained on only a small set of classical structures, the model efficiently generates new high‐metrics designs.
Qiqi Dai +7 more
wiley +1 more source
A mathematical model of metacarpal subchondral bone adaptation, microdamage and repair in racehorses. [PDF]
Pan M +6 more
europepmc +1 more source
SpaBatch is an end‐to‐end multi‐slice spatial transcriptomics data integration framework. It simultaneously performs embedding learning, spatial feature denoising and reconstruction, batch effect correction, and spatial domain optimization, effectively correcting batch effects and achieving accurate 3D spatial domain identification.
Jinyun Niu +5 more
wiley +1 more source

