Inspired by the temporal subspace clustering (TSC) method and low-rank matrix approximation constraint, a new model is proposed termed as temporal plus low-rank subspace clustering (TLRSC) by utilizing both the local and global structural information. On one hand, to solve the drawback that the...
Finding structure with randomness: probabilistic algorithms for constructing approximate matrix decompositions SIAM Rev., 53 (2011) Google Scholar [21] C. Bach, D. Ceglia, L. Song, F. Duddeck Randomized low-rank approximation methods for projection-based model order reduction of large nonlinear dyna...
Spatial omics technologies can reveal the molecular intricacy of the brain. While mass spectrometry imaging (MSI) provides spatial localization of compounds, comprehensive biochemical profiling at a brain-wide scale in three dimensions by MSI with single
Here, we report that cholesterol biosynthesis is reprogrammed in serrated tumors. We demonstrate that low aPKC expression, a driving characteristic of serrated tumors, upregulates the activity of SREBP2 by suppressing the ubiquitin-mediated degradation cascade of its chaperone protein SCAP. Subsequent dy...
Extracellular matrix ELISA: Enzyme-linked immunosorbent assay EMT: Epithelial-mesenchymal transition EndMT: Endothelial-to-mesenchymal transition FASL: Fas ligand HE: Hematoxylin-eosin GO: Gene Ontology GzmA: Granzyme A HLA: Human leukocyte antigen HPD: Hyperprogressive disease HuNCG: Humani...
This technique’s major drawback lies in the instability associated with rank deficiency in the stiffness matrix which appears under compressive states [95], which remains an open question in the Computational Mechanics field. Having also been applied to non-local damage approaches such as PF ...
DL can learn very complex non-linear mapping from a partially filled spectrum map to its full-resolution map, with the DL network trained with simulation data; while the traditional matrix completion (MC) method is used for post-processing the DL output map to keep its low-rank property, ...
extracellular matrix (ECM) is an energy-intensive step for cells in the tumor margin [5]. To meet this demand, leader cells in the invasive front will enhance the energy status to respond to the higher metabolic costs for ECM remodeling while moving forward compared to the cells behind the ...
Then knowledge graph representation learning techniques are used to learn low-dimensional vector representations for knowledge graph components. In the following a neural collaborative filtering framework is used which benefits from no extra weights on layers. It is only dependent on matrix operations. ...
Non-invading cells and EC matrix were gently scraped off with a cotton swab following a 48-h incubation. On the lower side of the chamber, migrated and invaded cells were stained with crystal violet (0.5 %) to air dry, photographed and calculated with ImageJ. Cell viability assay EMT-...