AIMC Journal:
bioRxiv

Showing 1891 to 1900 of 4956 articles

Shape2Fate: a morphology-aware deep learning framework for tracking endocytic and exocytic carriers at nanoscale.

bioRxiv Mar 30, 2026
Plasma membrane homeostasis requires balanced exocytosis and endocytosis, yet their coordination at the single-event level in non-neuronal cells is unresolved. We present Shape2Fate, a morphology-aware deep-learning pipeline that detects, tracks, and...
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Evolutionary exploration of drug-like chemical space utilizing generative AI and virtual screening

bioRxiv Mar 30, 2026
The identification of suitable lead molecules in the vast chemical space is a critical and challenging task in drug discovery campaigns. Recently, it has been demonstrated that large-scale virtual screening provides a powerful approach to accelerate ...
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Integrated single-cell and bulk transcriptomic analysis leverages liver metastasis-related genes to develop a prognostic model for colorectal cancer patients

bioRxiv Mar 30, 2026
Based on single-cell RNA sequencing data, differentially expressed genes (LMR DEGs) between colorectal cancer liver metastasis epithelium and primary colorectal cancer epithelium show potential as novel biomarkers for colorectal cancer prognosis. Thi...
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BrainYears: A functional EEG-based brain age clock enables intervention-ready measurements of brain aging

bioRxiv Mar 30, 2026
Biological brain aging is a major determinant of cognitive decline and neurodegenerative disease, yet scalable and intervention-ready brain aging biomarkers remain limited. Here, we develop an electroencephalography (EEG)-based brain age clock using ...
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The End of Aging Clocks: Training Foundation Models to Reason in Aging and Longevity

bioRxiv Mar 30, 2026
The aging clock paradigm has yielded dozens of specialist models that can estimate chronological age or mortality from virtually any biodata type. Yet each such model operates within a fixed modality, relies on a predetermined feature set, and produc...
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CLOP-DiT: Structured-Metadata-Conditioned Single-Cell Latent Generation via Contrastive Language-Omics Pretraining and Diffusion Transformers

bioRxiv Mar 30, 2026
Generating realistic single-cell transcriptomic profiles from structured biological descriptions would enable controlled simulation, data augmentation, and hypothesis-driven cell-state creation---yet no existing method combines text--cell alignment w...
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AINN-P1: A Compact Sequence-Only Protein Language Model Achieves Competitive Fitness Prediction on ProteinGym

bioRxiv Mar 30, 2026
Protein language models (PLMs) are increasingly central to protein engineering and drug discovery. Many high-performing systems, however, rely on large parameter counts, multiple sequence alignments (MSAs), explicit structural inputs, or computationa...
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PHENOCAUZ: Linking Human Symptoms, Drug Side Effects and Efficacy to Their Molecular Causes Using Mendelian Disease Biology

bioRxiv Mar 30, 2026
Human diseases and adverse drug reactions are ultimately recognized through clinical symptoms, yet the molecular determinants of most symptoms remain unknown. To address this key issue, we present PHENOCAUZ, a computational framework that links sympt...
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Naturalistic Stimulus Reconstruction from fMRI: A Primer in the Natural Scenes Dataset

bioRxiv Mar 30, 2026
Reconstructing natural images from brain activity represents one of the most compelling demonstrations of the synergy between modern neuroimaging and machine learning. However, the computational pipelines underlying these results remain scarcely acce...
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MAMGL: A memory-augmented meta-graph learning framework for adolescent major depression disorder diagnosis

bioRxiv Mar 30, 2026
Adolescent major depressive disorder (AMDD) is a prevalent and heterogeneous psychiatric condition that emerges during a critical period of brain development. Neuroimaging based biomarkers derived from resting state functional magnetic resonance imag...
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