bioRxiv

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Cross-chemical and cross-species toxicity prediction: benchmarking and a novel 3D-structure-based deep learning model

bioRxiv Jan 1, 2025
Prediction of a compound’s toxicity is a key step toward realizing animal-free testing of chemical compounds. Recent advances have yielded significant progress in computational toxicity prediction, including machine learning methods that utilize chem...
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A semantotopic map in human hippocampus

bioRxiv Jan 1, 2025
The hippocampus plays a central role in encoding abstract conceptual and semantic information. However, little is known about the topography of that encoding. We leveraged the rare opportunity to examine neural responses densely along a small portion...
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Refined Myocardium Segmentation from CT Using a Hybrid-Fusion Transformer

bioRxiv Jan 1, 2025
Accurate segmentation of the left ventricle (LV) in cardiac CT images is crucial for assessing ventricular function and diagnosing cardiovascular diseases. Creating a sufficiently large training set with accurate manual labels of LV can be cumbersome...
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A deep learning model captures position-specific effects of plant regulatory sequences and suggests genes under complex regulation

bioRxiv Jan 1, 2025
Deep neural networks can be trained to predict gene expression directly from genomic sequence, thereby implicitly learning regulatory sequence patterns from scratch, minimizing the bias imposed by prior assumptions. A challenging, yet promising prosp...
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In search for the invisible: motor inhibition in monkey premotor cortex and its RNN replicas

bioRxiv Jan 1, 2025
Controlling actions in dynamically changing environments requires flexible and efficient motor control. A fundamental challenge in neuroscience is to uncover how cortical circuits generate, adjust, and sometimes suppress planned movements. To address...
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Oyster: a neural network for modelling genomic sequences that enables exact position-specific k-mer contributions

bioRxiv Jan 1, 2025
Genomic functions arise from nucleotide sequences and their overlapping k-mers – subsequences whose contributions depend on their composition, position and associations. Understanding these contributions requires computing a k-mer contribution functi...
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A Deep Learning Framework for Quantifying Dynamic Self-Organization in Myxococcus xanthus

bioRxiv Jan 1, 2025
Under starvation, Myxococcus xanthus bacteria initiate a multicellular developmental program in which cells move to form fruiting bodies and differentiate into distinct cell types. Many genes affecting this process have been identified, and it is ass...
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Machine Learning Analysis of Cilia-Driven Particle Transport Distinguishes Primary Ciliary Dyskinesia Cilia from Normal Cilia

bioRxiv Jan 1, 2025
Primary ciliary dyskinesia (PCD) is a genetic condition that results in dysmotile cilia and abnormal mucociliary clearance. Despite advances in understanding the pathogenesis of PCD, diagnosis continues to be challenging. Here we used feature-based m...
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CUSP: Complex Spike Sorting from Multi-electrode Array Recordings with U-net Sequence-to-Sequence Prediction

bioRxiv Jan 1, 2025
Complex spikes (CSs) in cerebellar Purkinje cells convey unique signals complementary to Simple spike (SS) action potentials, but are infrequent and variable in waveform. Their variability and low spike counts, combined with recording artifacts such ...
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Deep Learning Enables Automated Segmentation and Quantification of Ultrastructure from Transmission Electron Microscopy Images

bioRxiv Jan 1, 2025
The widths of kidney glomerular basement membrane (GBM) and podocyte foot processes (FP) are essential ultrastructural markers for assessing kidney function and diagnosing glomerular disease. FP widening reflects podocyte injury, whereas GBM thickeni...
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