AIMC Journal:
bioRxiv

Showing 841 to 850 of 4938 articles

Conclusions Drawn From Neural Network to Brain Alignment Depend Strongly on the Chosen Similarity Measure

bioRxiv Jul 8, 2026
Deep neural networks are widely used to model biological perception and behavior, making the similarities and differences between artificial and biological systems consequential. If a principle (e.g. self-supervised learning) produces a model resembl...
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Label-Free Live Cell Type Prediction by Integrating Raman Spectroscopy and Machine Learning

bioRxiv Jul 8, 2026
Coherent Raman spectroscopy enables label-free biochemical fingerprinting of live cells with subcellular resolution. We previously developed a machine learning framework capable of classifying glioma FFPE tissues using Raman spectral signatures. To a...
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Graph-based modeling of multiparametric MRI deciphers molecular states of high-grade glioma invasion with prognostic implications

bioRxiv Jul 8, 2026
AbstractThe infiltrative, non-enhancing margin of IDH wildtype high grade glioma (IDHwt HGG) harbors distinct molecular programs that drive invasion and therapeutic resistance, yet remains largely unevaluable by conventional tissue sampling approache...
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Residual Multi-Modal Learning for Pan-Breast-Cancer Drug Response Prediction

bioRxiv Jul 8, 2026
Predicting drug sensitivity across diverse cancer cell lines remains a fundamental challenge in precision oncology, particularly for data-scarce cell lines where per-cell-line models overfit and lookup-table approaches cannot generalise to unseen bio...
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PINPOINT: Protease INhibitor PredictiOn at the plant-pathogen INTerface using protein language models and structural modeling

bioRxiv Jul 8, 2026
Cysteine and serine proteases act as an immune hub in the plant apoplast to provide robust extracellular immunity during microbial colonisation. Microbial pathogens counteract these immune proteases by inhibiting their activity using small secreted p...
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Graph neural network modeling of receptor interaction kinetics from single-molecule imaging data

bioRxiv Jul 8, 2026
Single-molecule (SM) imaging (SMI)-based approaches have the powerful ability to capture receptor interactions, which are necessary for cell signaling, in their native live-cell environment. Yet, due to substoichiometric labeling, SMI generally provi...
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Deep dynamical models of single-cell multiomic velocities predict loss-of-function and rescue perturbations in B cells

bioRxiv Jul 8, 2026
We present DynaVelo, a generative neural ordinary differential equation model that learns the joint dynamics of gene expression and transcription factor (TF) motif activities in evolving cell systems using single-cell multiome with joint gene express...
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Metabolomic signatures support the diagnostics of peritoneal endometriosis using generalised linear models.

bioRxiv Jul 7, 2026
Endometriosis, a common inflammatory gynecological disorder affecting up to 10% of women worldwide, is characterized by the presence of endometrium-like tissue outside the uterus. Current diagnostic methods, such as ultrasound and MRI, effectively de...
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VESTA: Machine Learning-Enabled Estimation of ViscoElastic Ratios from On-Axis Spatio-Temporal ARFI Features

bioRxiv Jul 7, 2026
Viscoelastic characterization of tissue has significant diagnostic value in oncology, as tumor progression alters both elasticity and viscosity in ways that neither property alone can fully capture. Existing acoustic radiation force (ARF)-based metho...
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ThermoFusion: A Multimodal Deep Learning Framework for Generalizable Prediction of Enzyme Thermostability

bioRxiv Jul 7, 2026
Protein thermostability is a critical property for both industrial and biomedical enzyme applications, yet experimental evaluation of mutation-induced stability changes remains laborious and costly. Here, we present ThermoFusion, a hybrid deep learni...
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