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Canada-0-EMBLEMS Azienda Directories
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Azienda News:
- Cross-Species and Tissue-Agnostic Prediction of Human Cancer Treatment . . .
The biological process (BP) derived from enrichment analysis for CMB250 in human and mouse samples shows a significant overlap in essential biological processes across species, emphasizing the translatability of mouse-derived CMBs to human cancer studies
- Translating Brain Anatomy and Disease from Mouse to Human in Latent . . .
The VAE improves the cross-species comparison compared with the gene expression and the MLP 440 approaches a – 2-D Umap for visualisation of regional data distributions, where each dot represents a mouse 441 or human ROI, as defined per the atlases described in the methods
- Cross-Species Graph Neural Network for Translating Animal Disease . . .
We introduce CENTAURGNN, a cross-species graph neural network (GNN) that leverages species-specific message passing to integrate animal disease resistance (ADR) data and human genomic data for novel target discovery
- Mouse-Geneformer: A deep learning model for mouse single-cell . . .
These results demonstrate the feasibility of analyzing mouse data with mouse-Geneformer and highlight the robustness of the Geneformer architecture, applicable to any species with large-scale transcriptome data available Furthermore, we found that mouse-Geneformer can analyze human transcrip-tome data in a cross-species manner
- Cross-Species and Tissue-Agnostic Prediction of Human Cancer Treatment . . .
The success of drug development relies heavily on the use of animal models However, increasing evidence shows that discoveries in these models often fail to translate to human patients In this study, we developed an AI framework to discovery cross-species and tissue-agnostic cellular morphometric biomarkers (CMBs) as a new avenue to improve translatability Using this framework, we
- Abstract 5166: Increasing translatability of syngeneic mouse models of . . .
AbstractBackground: Syngeneic mouse models serve as invaluable tools in preclinical research Implanting cancer cells into immunocompetent mice allows immunotherapy responses to be assessed in a physiologically relevant setting To further improve the translatability of syngeneic models, we (1) characterized the immune landscape of different syngeneic models using human-validated immune gene
- TransBrain: a computational framework for translating brain-wide . . .
In addition, the detached model revealed consistent cross-species transcriptional similarities at finer scale, both between mouse higher-order regions (such as the prelimbic area) and the human
- Cross-Species Graph Neural Network for Translating Animal Disease . . .
Therapeutic target discovery has traditionally relied on data from human patients and mouse models, which primarily capture disease states rather than mechanisms of resistance or repair Animals with evolved disease-protective adaptations offer complementary insights that, when properly combined with human data, can drive more discoveries Here, we introduce CentaurGNN, a cross-species graph
- Artificial intelligence-based biomarkers for treatment decisions in . . .
Artificial intelligence (AI)-based biomarkers derived from routine clinical data could enhance the accessibility of personalized medicine by providing rapid and cost-effective alternatives to traditional molecular biomarkers
- A deep-learning tool for species-agnostic integration of cancer cell . . .
Genetically engineered mouse models (GEMM) of cancer are a useful tool for exploring the development and biological composition of human tumors and, when combined with single-cell RNA-sequencing (scRNA-seq), provide a transcriptomic snapshot of cancer data to explore heterogeneity of cell states in an immunocompetent context However, cross-species comparison often suffers from biological
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