bioRxiv

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đť’ź-BLUP: a differentiable genomic BLUP model with learnable variance and marker weights

bioRxiv Jan 1, 2025
Genomic best linear unbiased prediction (GBLUP) is widely used for genomic selection in livestock and crop breeding. There is growing interest in connecting machine learning with genomic breeding value prediction. Although the BLUP formula is itself ...
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Top-down feedback matters: Functional impact of brainlike connectivity motifs on audiovisual integration

bioRxiv Jan 1, 2025
Artificial neural networks (ANNs) are an important tool for studying neural computation, but many features of the brain are not captured by standard ANN architectures. One notable missing feature in most ANN models is top-down feedback, i.e. projecti...
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Diffusion Models vs. DCGANs for Class-Imbalanced Lung Cancer CT Classification: A Comparative Study

bioRxiv Jan 1, 2025
Effective lung cancer detection from CT scans remains critically challenged by class imbalance where benign and normal cases are underrepresented, leading to biased machine learning models with reduced sensitivity for minority classes and potentially...
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Explainable Machine Learning for Preoperative Relapse Prediction in Molecularly Stratified Endometrial Cancer: A Single-Center Finnish Cohort Study

bioRxiv Jan 1, 2025
Relapse risk in endometrial carcinoma (EC) is strongly influenced by molecular subtype, yet current WHO/ESGO classifications rely on postoperative data, limiting their utility for preoperative decision-making. We developed and compared interpretable ...
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Graph attention with structural features improves the generalizability of identifying functional sequences at a protein interface

bioRxiv Jan 1, 2025
Accurate prediction of the set of sequences compatible with a protein-protein interface is an unsolved problem in biology. While supervised sequence-based models trained directly on experimental data can predict variant effects, they often fail to ge...
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Deep Learning links TP53 genotype to expression-defined transcriptional program in Acute Myeloid Leukemia

bioRxiv Jan 1, 2025
Acute myeloid leukemia (AML) is a hematological cancer characterized by genetic diversity and poor clinical outcomes. Among various genetic mutations in AML, TP53 mutations have relatively low prevalence and present very dismal survival rates. While ...
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Unsupervised visual learning is revealed for task-irrelevant natural scenes due to reduced attentional suppression effects in visual areas

bioRxiv Jan 1, 2025
Unsupervised learning—learning through repeated exposure without instruction or reward—is central to both machine learning and human cognition, including language acquisition and statistical learning. However, its role in visual perceptual learning (...
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Statistically valid explainable black-box machine learning: applications in sex classification across species using brain imaging

bioRxiv Jan 1, 2025
Sex classification using neuroimaging data has the potential to revolutionize personalized diagnostics by revealing subtle structural brain differences that underlie sex-specific disease risks. Despite the promise of machine learning, traditional met...
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Dissecting sequence determinants of DNA methylation and in silico perturbation

bioRxiv Jan 1, 2025
DNA methylation shapes cellular identity and genome function, yet the sequence logic that governs its establishment remains largely unresolved. Here we present MethylAI, a cross-species–pretrained and human-specialized deep learning framework that pr...
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Deep Learning-Augmented Stimulated Raman Imaging for Cell-Type-Specific Metabolic Profiling in Live Neuronal Co-Cultures

bioRxiv Jan 1, 2025
Neuronal metabolism is fundamental to brain functions and diseases, yet its spatial and temporal dynamics and interactions remain poorly understood. Here, we introduce a tandem deep-learning approach integrated with bioorthogonal chemical imaging usi...
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