AIMC Journal:
bioRxiv

Showing 1881 to 1890 of 4956 articles

Representational magnitude as a geometric signature ofimage and word memorability

bioRxiv Apr 11, 2026
What makes some stimuli more memorable than others? Recent work has shown that image memorability is predicted by the magnitude of population responses in both monkey inferotemporal cortex and convolutional neural networks, suggesting that stimuli th...
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A structure-informed deep learning framework for modeling TCR-peptide-HLA interactions

bioRxiv Apr 11, 2026
The interaction between T cell receptors (TCRs), peptides, and human leukocyte antigens (HLAs) underlies antigen-specific T cell immunity. Despite substantial advances in peptide-HLA presentation prediction, accurate modeling of coupled TCR-peptide-H...
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Spatial Organellomics Maps Cell State Diversity and Metabolic Adaptation in Tissues

bioRxiv Apr 9, 2026
Cell state diversity drives tissue adaptability, repair, and disease resilience, but fully capturing this cellular complexity remains a challenge. Most current approaches rely on transcriptional profiling and often overlook functional insights embedd...
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Reduced spread of nodes in spatial network models improves topology associated with increased computational capabilities

bioRxiv Apr 5, 2026
Biological neural networks are characterized by short average path lengths, high clustering, and modular and hierarchical architectures. These complex network topologies strike a balance between local specialization and global synchronization via lon...
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CellBench-LS: Benchmark Evaluation of Single-cell Foundation Models for Low-supervision Scenarios

bioRxiv Apr 5, 2026
While single-cell foundation models (SCFMs) have shown promise across various downstream tasks, their generalization performance in label-scarce settings remains a critical bottleneck. The absence of systematic benchmarks for these low-resource scena...
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Interpretable Deep Learning-Based Multi-Omics Integrationfor Prognosis in Hepatocellular Carcinoma

bioRxiv Apr 5, 2026
Hepatocellular carcinoma (HCC) is a leading cause of cancer mortality worldwide, yet existing prognostic models incompletely capture its molecular heterogeneity. We developed an interpretable, attention-based multi-branch deep learning framework for ...
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OpenAc4C: A gateway to decode the landscape, regulation and pathogenesis of N4-acetylcytidine (ac4C) epitranscriptome

bioRxiv Apr 5, 2026
N4-acetylcytidine (ac4C) is an ancient and highly conserved chemical marker found in all domains of life. Recent advancements in sequencing techniques have enabled the functional analysis of ac4C occurrence by accurately capturing its locations and l...
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Fine scale structural information substantially improves multivariate regression model for mRNA in-vial degradation prediction

bioRxiv Apr 4, 2026
The success of COVID-19 mRNA vaccines has made the in-solution stability optimization of mRNAs a key objective. However, we still lack a complete understanding of sequence metrics that influence mRNA in-solution stability. RNA secondary structure pla...
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Eukaryote-to-eukaryote gene transfer pervades the genome evolution of Rhizaria

bioRxiv Apr 3, 2026
Lateral gene transfer (LGT) has contributed to the genetic makeup of various eukaryotic lineages, yet its prevalence and long-term significance remain poorly understood, particularly for transfers between eukaryotes. Here, we investigate LGT across 2...
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Deep representation learning for temporal inference in cancer omics: a systematic review

bioRxiv Mar 31, 2026
Deep learning methods, including deep representation learning (DRL) approaches such as variational autoencoders (VAEs), have been widely applied to cancer omics data to address the high dimensionality of these datasets. Despite remarkable advances, c...
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