Peptic Ulcer Disease

Proteomic Learning of Gamma-Aminobutyric Acid (GABA) Receptor-Mediated Anesthesia

Anesthetics are crucial in surgical procedures and therapeutic interventions, but they come with side effects and varying levels of effectiveness, calling for novel anesthetic agents that offer more precise and controllable effects. Targeting Gamma-aminobutyric acid (GABA) receptors, the primary inhibitory receptors in the central nervous system, could enhance their inhibitory action, potentiall...

Machine Learning-Based Prediction of ICU Readmissions in Intracerebral Hemorrhage Patients: Insights from the MIMIC Databases

Intracerebral hemorrhage (ICH) is a life-risking condition characterized by bleeding within the brain parenchyma. ICU readmission in ICH patients is a critical outcome, reflecting both clinical severity and resource utilization. Accurate prediction of ICU readmission risk is crucial for guiding clinical decision-making and optimizing healthcare resources. This study utilized the Medical Informat...

XL-Ranker: A Computational Workflow for Prioritizing Protein-Protein Interactions from Cross-Linking Mass Spectrometry Data

Protein-protein interactions (PPIs) are central to virtually all biological processes, and their disruption can lead to a wide spectrum of human disea...

ProtLoc-GRPO: Cell line-specific subcellular localization prediction using a graph-based model and reinforcement learning

Subcellular localization prediction is crucial for understanding protein functions and cellular processes. Subcellular localization is dependent on ti...

GeoGAT-site: A Face-Centered Geometric Graph Attention Network for Protein-Protein Interface Prediction

Protein-protein interactions (PPIs) underpin the intricate machinery of cellular life, orchestrating processes from signal transduction to metabolic r...

ProteomeLM: A proteome-scale language model allowing fast prediction of protein-protein interactions and gene essentiality across taxa

Language models starting from biological sequence data are advancing many inference problems, both at the scale of single proteins, and at the scale o...

HPInet: Interpretable prediction of Host-Pathogen protein-protein Interactions using a transformer-based neural network

Gram-negative bacteria utilize a series of secretion systems (T1SS-T10SS) to deliver secreted effector proteins (T1SE-T10SE) into host cells, leading ...

Decoding Helicobacter pylori Resistance: Machine Learning–Enhanced Prediction of Antibiotic Susceptibility using Whole-Genome Sequencing

Helicobacter pylori is a significant risk factor for gastric cancer, peptic ulcers, and MALT lymphoma. Rising antibiotic resistance rates complicate t...

C3PI: Component Puzzle Protein-Protein Interaction Prediction

Proteins primarily perform their functions through interactions with other proteins, making the accurate prediction of protein-protein interactions (P...

Improving Protein Interaction Prediction in GenPPi: A Novel Interaction Sampling Approach Preserving Network Topology

Computational prediction of protein-protein interactions (PPIs) is crucial for understanding cell biology and drug development, offering an alternativ...

In Silico Design of APOE ɛ4 Interaction Inhibitor Peptides for Alzheimer’s Disease

Protein-protein interactions (PPIs) are essential for cellular functions, and their aberrant formation contributes to neurodegenerative diseases. Alzh...

Instruction-tuned extraction of virus-host interactions from integrated scientific evidence

Viral infectious diseases continue to pose a major threat to global health. Understanding protein-protein interactions (PPIs) and RNA-protein interact...

Protein-protein interaction priors shape biologically coherent latent spaces for causally concordant cross-omic translation

Deep learning models routinely compress omics into low-dimensional codes, yet many equally accurate embeddings fail to reflect how cells are wired, wh...

Multiplex mapping of protein-protein interaction interfaces

We describe peptide mapping through Split Antibiotic Resistance Complementation (SpARC-map), a method to identify the probable interface between two i...

GREmLN: A Cellular Graph Structure Aware Transcriptomics Foundation Model

The ever-increasing availability of large-scale single-cell profiles presents an opportunity to develop foundation models to capture cell properties a...

Protein Language Models are Accidental Taxonomists

Protein-protein interactions (PPIs) are fundamental to nearly all biological processes, yet their experimental characterization remains costly and tim...

Discovery of molecular glues by modeling ternary complex conformational ensembles and thermodynamic stability

The rational design of molecular glue degraders is challenging because glue-mediated protein degradation depends on a complex interplay of molecular m...

Systematic discovery of single-cell protein networks in cancer with Shusi

Context-specific protein-protein interaction (PPI) drive heterogeneity of primary tumor, forming a formidable challenge to effective cancer therapy. H...

Language may be all omics needs: Harmonizing multimodal data for omics understanding with CellHermes

Decoding cellular systems requires integrating diverse omics data, yet most models are trained from scratch on a single modality, restricting generali...

ProtAttn-QuadNet: An attention-based deep learning framework for protein–protein interaction prediction using ProtBERT embeddings

Protein–protein interactions (PPIs) form the backbone of most cellular processes, governing signal transduction, gene regulation, and metabolic contro...