AIMC Journal:
bioRxiv

Showing 2011 to 2020 of 4956 articles

Calcium transient detection and segmentation with the astronomically motivated algorithm for background estimation and transient segmentation (Astro-BEATS)

bioRxiv Mar 17, 2026
Fluorescence-based calcium-imaging is a powerful tool for studying localized neuronal activity, including miniature Synaptic Calcium Transients, providing real-time insights into synaptic activity. These transients induce only subtle changes in the f...
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Multimodal Molecular Mapping of the Vasculature in Human Cortex Reveals Lipid Markers of Cerebral Amyloid Angiopathy

bioRxiv Mar 17, 2026
Cerebral amyloid angiopathy (CAA) commonly co-occurs with Alzheimer's disease (AD), yet the molecular changes that accompany vascular beta-amyloid deposition in human tissue remain incompletely defined. Herein, we use a novel imaging approach that co...
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AI for Fisheries Science: Neural Network Tools for Forecasting, Spatial Standardization, and Policy Optimization

bioRxiv Mar 17, 2026
The development of Artificial Intelligence (AI) presents novel opportunities for tackling complex marine resource management challenges. Among AI models, neural networks are a powerful class of tools capable of learning nonlocal and lagged patterns f...
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Integrated Artificial Intelligence and Quantum Chemistry Approach for the Rational Design of Novel Antibacterial Agents against Ralstonia solanacearum.

bioRxiv Mar 17, 2026
Antimicrobial resistance (AMR) in plant pathogenic bacteria poses a serious threat to global agriculture, necessitating the development of novel antibacterial agents targeting virulence mechanisms. This study presents an integrated bioinformatics-dri...
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Glydentify: An explainable deep learning platform for glycosyltransferase donor substrate prediction

bioRxiv Mar 17, 2026
Glycosyltransferases (GTs) are a large family of enzymes that catalyze the formation of glycosidic linkages between chemically diverse donor and acceptor molecules to regulate diverse cellular processes across all domains of life. Despite their impor...
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Spatial Agent-Based Modeling and Interpretable Machine Learning Predict Combination Therapy Response in HER2-Heterogeneous Breast Cancer

bioRxiv Mar 17, 2026
HER2 heterogeneity and reversible phenotypic plasticity play a central role in breast cancer progression and therapeutic resistance, yet how their interaction shapes treatment response remains poorly understood. Experimental and clinical evidence ind...
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A network-based deep learning model integrating subclonal architecture for therapy response prediction in cancer

bioRxiv Mar 17, 2026
Predicting treatment response remains challenging in oncology, particularly given the growing diversity of therapeutic options. Despite efforts using gene expression signatures, or integrative multi-omics frameworks, robust and interpretable biomarke...
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A novel framework for expanding RNNs with biophysical detail to solve cognitive tasks

bioRxiv Mar 17, 2026
Recurrent neural networks (RNNs) have proven to be highly successful in emulating human-like cognitive functions such as working memory. In recent years, RNNs are evolving to incorporate more biophysical realism to produce more plausible predictions ...
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Single-Pass Discrete Diffusion Predicts High-Affinity Peptide Binders at >1,000 Sequences per Second across 150 Receptor Targets

bioRxiv Mar 17, 2026
De novo peptide design methods traditionally couple generation to 3D structure prediction, limiting throughput to seconds or hours per candidate. Here we present LigandForge, a discrete diffusion model that generates binding peptide sequences in a si...
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RNAElectra: An ELECTRA-Style RNA Foundation Model for RNA Regulatory Inference

bioRxiv Mar 17, 2026
RNA regulation governs gene expression through sequence-encoded mechanisms such as RNA structure formation, protein binding, chemical modification, and RNA-RNA targeting, with regulatory rules spanning both nucleotide-scale motifs and longer-range co...
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