Artificial Intelligence Medical Compendium

Explore the latest research on artificial intelligence and machine learning in medicine.

Showing 26,291 to 26,300 of 217,905 articles

Integrating AI and molecular modeling for structural prediction of a closed state of the hERG channel

bioRxiv
The voltage-gated potassium channel hERG (Kv11.1) plays a central role in cardiac repolarisation by mediating the rapid delayed rectifier K current (IKr). Blockage of hERG by small molecules can lead to delayed repolarisation, QT interval prolongatio... read more 

scConcept enables concept-level exploration of single-cell transcriptomic data

bioRxiv
Interpreting high-dimensional single-cell transcriptomic data remains challenging, as existing methods rely on latent representations or prior knowledge that require extensive post hoc analysis to derive biologically meaningful insights. Topic models... read more 

Probabilistic coupling of cellular and microenvironmental heterogeneity by masked self-supervised learning

bioRxiv
Spatial omics technologies have advanced to single-cell resolution, enabling systematic analysis of tissue microenvironments alongside cellular-state heterogeneity. However, computationally defining microenvironmental states at single-cell resolution... read more 

Systematic Evaluation of AlphaFold2 and OpenFold3 on Protein-Peptide Complexes

bioRxiv
Protein-peptide interactions are important mediators of diverse biological processes. While deep learning has revolutionized protein structure prediction, comparative evaluation of these methods, specifically for protein-peptide complexes, remains an... read more 

H2O: A Foundation Model Bridging Histopathology to Spatial Multi-Omics Profiling

bioRxiv
Spatial omics technologies have revolutionized the molecular profiling of tissues but remain constrained by high costs and limited scalability. While hematoxylin and eosin (H&E) staining is ubiquitous, it lacks molecular specificity. Here, we present... read more 

Turep: Detecting cross-cancer tumor-reactive T cells in single-cell and spatial transcriptomics data

bioRxiv
Tumor-infiltrating lymphocytes are essential for anti-tumor immunity, yet distinguishing tumor-reactive T cells from non-reactive bystander cells remains a significant challenge. Existing signatures, often derived from single cohorts, lack robustness... read more 

CellChem: Cellular transcriptional responses reshape molecular representation space for efficient and multi-scale drug discovery

bioRxiv
Despite decades of progress in computational drug discovery, deep learning-based molecular representation models remain largely structure-centric, assuming that chemical similarity approximates functional similarity. However, drug effects in cells ar... read more 

Integrating Metabolic Networks into Hybrid Bioprocess Models

bioRxiv
The optimization and control of bioprocesses require robust in silico models that can accurately capture the complex and dynamic behavior of living cells. While hybrid models that combine machine learning with mechanistic equations have emerged as a ... read more 

CellPulse: A Foundation Model of Coordinated Gene Dynamics Simulating Viral Infectious Diseases

bioRxiv
Understanding how cells respond to perturbations like viral infections requires models capturing coordinated gene dynamics. However, current gene expression foundation models are predominantly reliant on single-cell data and static gene expression, l... read more 

SNPic: SNP Topic Modeling for Interpretable Clustering of Complex phenotypes

bioRxiv
Genome-wide association studies (GWAS) have cataloged thousands of disease-associated variants, yet a central challenge remains: decoding the shared, pleiotropic architecture that links complex phenotypes. Existing approaches, including dimensionalit... read more