AIMC Journal:
bioRxiv

Showing 1601 to 1610 of 4956 articles

Susagi: A Microbiome World Model

bioRxiv May 11, 2026
Motivation: Accurately modelling how microbial communities assemble and change across hosts and environments is essential for analysis and intervention. Typical pipelines capture limited generalisable structure and often depend on fixed ecological un...
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The Second Brain: Diffusion Models for Realistic Human Microbiome Generation

bioRxiv May 11, 2026
The human microbiome is a critical determinant of health and disease, but microbiome machine learning is constrained by limited data availability, heterogeneous cohort coverage, and privacy risks from individually identifying microbial signatures. Sy...
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Enhanced processing of cartoons in infant visual cortex

bioRxiv May 11, 2026
Developing sensory systems may have heightened sensitivity to exaggerated features that emphasize diagnostic information, as shown by the benefits of infant-directed speech for language acquisition. Here, we examine this sensory exaggeration hypothes...
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Entropy Sorting Feature Selection: information-theoretic gene set identification improves single-cell RNA sequencing data interpretability

bioRxiv May 10, 2026
Single-cell RNA sequencing (scRNA-seq) has transformed our ability to resolve cellular heterogeneity, but extracting meaningful signals remains challenging due to technical noise and batch effects. Most methods for denoising scRNA-seq data have focus...
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Scale matters: Large language models with billions (rather than millions) of parameters better match neural representations of natural language

bioRxiv May 10, 2026
Recent research has used large language models (LLMs) to study the neural basis of naturalistic language processing in the human brain. LLMs have rapidly grown in complexity, leading to improved language processing capabilities. However, neuroscience...
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Integrative taxonomy using traits and genomic data for Species Delimitation with Deep learning

bioRxiv May 10, 2026
Recognizing species boundaries in complex speciation scenarios, including those involving gene flow and demographic fluctuations, remains a challenge, particularly given the diversity of existing species concepts. Promising recent approaches adopt an...
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LIME: a fully automated pipeline for high-throughput quantification of leaf lesions

bioRxiv May 10, 2026
Accurate quantification of leaf lesion severity is essential for plant disease research and phenotyping but is often limited by subjective visual scoring and time-intensive manual image analysis. We present LIME, a fully automated, open-source image ...
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Interpretable neural networks prioritize cancer driver genes from genome-wide dependency landscapes

bioRxiv May 10, 2026
Identifying cancer driver genes and their therapeutic impact remains a core challenge in computational cancer biology. We introduce xNNDriver and xAEDriver, two interpretable neural network frameworks that connect cancer mutations with genome-wide De...
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AI-enabled virtual immunopeptidomics links quantitative neoantigen presentation to immunogenicity

bioRxiv May 10, 2026
Effective anti-tumor T cell response depends on both neoantigen quality (non-selfness) and quantity (abundance). However, existing methods for neoantigen prioritization largely overlook peptide abundance because it is difficult to measure and model. ...
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Deep Computational Anatomy via Latent-Aligned Multiview Normalizing Flows

bioRxiv May 10, 2026
In modeling complex probability distributions, normalizing flows provide exact-likelihood, bijective mappings between empirical data and tractable latent spaces. Building on this foundation, latent-aligned multiview normalizing (LAMNr) flows leverage...
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