AIMC Journal:
bioRxiv

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NeuroCDS: Integrating Local and Global Neural Network Representations via Structural Constrained Viterbi Decoding for Robust CDS Annotation

bioRxiv May 2, 2026
Motivation: Robust annotation of Coding Sequences (CDS) is critical for downstream transcriptomics, yet heavily fragmented de novo RNA-Seq assemblies pose a severe challenge. Traditional computational tools rely on fixed, hand-crafted features that a...
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Single-cell foundation models reveal context-sensitive cancer programmes under subtype shift

bioRxiv May 1, 2026
Single-cell foundation models (scFMs) have shown promise as transferable representations of cellular state, but recent zero-shot evaluations suggest that they do not consistently outperform simpler baselines. We asked whether this apparent limitation...
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DIANNE: Segmentation-Free Localization of Histology Differential Attributes

bioRxiv May 1, 2026
Pathologist-guided distinctions within histology and spatial omic images provide insights into health and disease, with digital pathology leveraging artificial intelligence to automate such assessments. To train computational models, current digital ...
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Interpretable sequence-based machine learning consolidates candidate H3N2 hemagglutinin antigenic sites

bioRxiv May 1, 2026
Vaccine strain selection for seasonal influenza A(H3N2) depends on knowing which hemagglutinin (HA) substitutions are most likely to erode neutralizing antibody recognition, yet published antigenic site sets disagree substantially on which positions ...
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A dataset of simultaneous two-photon calcium imaging and auditory discrimination behavior

bioRxiv May 1, 2026
The emerging field of artificial intelligence for neuroscience relies heavily on high-quality, standardized datasets. Data linking high-dimensional neural population dynamics with complex behavior is crucial for advancing the field of brain-computer ...
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Deep learning cell type classification using nuclear DNA patterns

bioRxiv May 1, 2026
Multicellular organisms comprise various types of cells, which are characterized by gene expression through interactions between chromosomal DNA and nuclear proteins. Many cutting-edge methods have been developed to reveal the three-dimensional organ...
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Mitigating Family Effects in RNA Secondary-Structure Prediction with Latent-Space Continual Learning

bioRxiv May 1, 2026
Accurate RNA secondary-structure prediction remains difficult despite decades of thermodynamics-based algorithms and the advent of deep-learning architectures (convolutional networks, Transformers, diffusion models). In fact, the datasets that pair R...
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Artificial intelligence aided design of peptides with custom secondary structure motifs and reduced amino acid alphabets

bioRxiv May 1, 2026
Proteins are highly diverse functional polymers where the specific sequence of amino acids, selected from a standard genetically-encoded alphabet of twenty (C20), determines the structure and ultimately the function of the resulting folded protein. T...
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Tuned inhibitory control of neuronal firing thresholds explains predictive sensorimotor behavior

bioRxiv May 1, 2026
Prior expectations guide sensorimotor behavior when sensory information is uncertain, yet the cellular mechanisms underlying this integration remain elusive. Here, we investigate how priors in sensory motion direction shape neural population dynamics...
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Population geometry reveals directed coupling and transient bistability in spontaneous pituitary secretion

bioRxiv Apr 30, 2026
The pituitary gland operates as an organized signaling network in which endocrine cell populations coordinate hormone secretion, through homotypic and heterotypic interactions, yet the contribution of spontaneous intrinsic activity in shaping populat...
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