bioRxiv

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Uncertainty-aware genomic deep learning with knowledge distillation

bioRxiv Jan 1, 2025
Deep neural networks (DNNs) have advanced predictive modeling for regulatory genomics, but challenges remain in ensuring the reliability of their predictions and understanding the key factors behind their decision making. Here we introduce DEGU (Dist...
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Automated detection of macropods in Tasmania using drone surveys and convolutional neural networks (CNNs)

bioRxiv Jan 1, 2025
Manual annotation of drone imagery is labour-intensive and prone to observer bias, particularly when applied to large datasets across varied environments. To address this, a deep-learning pipeline was developed and evaluated for identifying macropods...
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Data-driven identification of functional networks in artificial and biological neural networks

bioRxiv Jan 1, 2025
Understanding how the brain represents information is a central challenge in neuroscience and a practical bottleneck for brain-computer interfaces. Existing analytical tools cannot identify neural representations directly from neural activity data. W...
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Infarctsize-AI: an efficient infarct size image analysis tool for small rodent myocardial infarction studies

bioRxiv Jan 1, 2025
Myocardial infarct size (IS) is the gold standard end-point in shorth-term studies on cardioprotection. However, IS quantification in rodent models with standard Evans Blue and 2,3,5-triphenyltetrazolium chloride (TTC) staining is time-consuming and ...
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DeepPathway: Predicting Pathway Expression from Histopathology Images

bioRxiv Jan 1, 2025
Spatial transcriptomics (ST) technologies provide spatially resolved gene expression along with image data, allowing the integrative analysis of complex tissue microenvironments. Despite their potential, the widespread adoption of ST remains limited ...
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Alignment of Artificial Neural Networks with Human Eye Movement Patterns in Facial Expression Recognition

bioRxiv Jan 1, 2025
Artificial neural networks (ANNs) have become powerful tools for modeling human perception and hehavior, yet it remains unclear if they resemble the sequential eye movement strategies humans employ during visual processing. Human studies demonstrate ...
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DTCFinder: a bench-to-bits toolkit for label-free, whole-spectrum analysis of disseminated and circulating tumor cells in liquid biopsies

bioRxiv Jan 1, 2025
Disseminated (DTCs) and circulating tumor cells (CTCs) are rare but pivotal in understanding cancer metastasis and advancing liquid biopsy-based diagnostics. Traditional detection approaches, hindered by their dependency on epithelial markers or morp...
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Bento: Benchmarking Classical and AI Docking on Drug Design–Relevant Data

bioRxiv Jan 1, 2025
Recent advances in artificial intelligence have introduced deep learning and co-folding approaches for predicting protein-ligand complexes, raising the question of their applicability and how they compare with classical docking methods. In this work,...
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Morphology-Aware Profiling of Highly Multiplexed Tissue Images using Variational Autoencoders

bioRxiv Jan 1, 2025
Spatial proteomics (highly multiplexed tissue imaging) provides unprecedented insight into the types, states, and spatial organization of cells within preserved tissue environments. To enable single-cell analysis, high-plex images are typically segme...
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Multi-modal, multi-species, and multi-task latent-space model for decoding level of consciousness

bioRxiv Jan 1, 2025
Assessing the degree and characteristics of consciousness is central to caring for patients with Disorders of Consciousness (DoC), yet current standard of care is a bedside questionnaire. Using a laminar neural probe we introduce a self-supervised, m...
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