AIMC Journal:
bioRxiv

Showing 1131 to 1140 of 4938 articles

DyMoTree decodes early cell state transitions and drivers from single-cell transcriptomes using a tree-structured neural network

bioRxiv Jun 11, 2026
Inferring early cell fate from single-cell RNA-sequencing data is essential for identifying cellular origins and fate plasticity in development and disease. However, existing methods often fail to exploit tree-structured lineage trajectories, limitin...
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DLDN-Bench: A Benchmark Framework for Deep Learning de Novo Peptide Sequencing in Proteomics

bioRxiv Jun 11, 2026
De novo peptide sequencing is an essential approach for analyzing mass spectrometry data because it enables the identification of novel peptides without relying on protein sequence databases. Recent advances in deep learning have substantially improv...
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Controlling metal-carbonate phase, form, and function through de novo protein design

bioRxiv Jun 11, 2026
Biomineralization enables living systems to construct hybrid materials by controlling the location, orientation, and polymorph of inorganic crystals with proteins and other biomolecules. Despite decades of study, the molecular principles underlying t...
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Learning using switching synaptic plasticity rules

bioRxiv Jun 11, 2026
Hebbian-like learning has been repeatedly confirmed experimentally, yet computational models usually require non-local signals, such as backpropagating errors, to solve complex cognitive tasks. Recent cortical electron microscopy data suggests a mode...
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Single-allele chromatin folding is organized by recurrent motifs that are reweighted across cell types and states

bioRxiv Jun 11, 2026
Chromatin folding exhibits extensive cell-to-cell variability, yet whether this variability is dominated by continuously varying conformations or by recurrent organizational patterns remains unclear. Here, we combined high-resolution chromatin tracin...
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HoloCell: A Generative Foundation Model for Holistic Cellular Modeling

bioRxiv Jun 11, 2026
Single-cell multi-omics technologies have recently advanced to enable the profiling of epigenomic, transcriptomic, and proteomic layers within individual cells, offering new opportunities to characterize cellular states as integrated biological syste...
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Covariate-aware genomic prediction of blood metabolite profiles using multi-task neural networks

bioRxiv Jun 11, 2026
Circulating metabolites capture clinically relevant physiological variation and contribute to disease aetiology yet are mostly studied as biomarkers rather than prediction targets. Although genome-wide association studies have identified genetic dete...
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TifBERT: a self-supervised foundation model for normalization-robust bulk RNA-seq representation learning

bioRxiv Jun 11, 2026
Bulk RNA sequencing remains central to translational genomics, yet foundation-model development has largely focused on single-cell data. Existing transformer approaches for bulk RNA-seq often rely on expression discretization, numerical reconstructio...
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TMO: ASYMMETRIC CROSS-MODAL ATTENTION FOR LEARNINGCELL-STATE-DEPENDENT REGULATORY LAGS FROM SINGLE-CELL MULTIOMIC DATA

bioRxiv Jun 11, 2026
Abstract Background: Single-cell multi-omics technologies simultaneously measure chromatin accessibility (ATAC) and gene expression (RNA), providing a unique window into the temporal ordering of regulatory events during differentiation. However, most...
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Functional Continuum of GABAergic Synaptic Dynamics Reflects Genetic Identities

bioRxiv Jun 10, 2026
The language of the brain is articulated by temporal patterns of neuronal activity, which individual synapses interpret through distinct forms of synaptic dynamics. While glutamatergic synapses have been proposed to use a handful of functionally dist...
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