AIMC Journal:
bioRxiv

Showing 1201 to 1210 of 4956 articles

CLASPP: A unified model for predicting post-translational modifications

bioRxiv Jun 7, 2026
Post-Translational Modifications (PTMs) are a fundamental mechanism for regulating cellular pathways and increasing the functional diversity of the proteome. Accurately predicting the PTM types that are likely to occur at a given site in the primary ...
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BacteReason: A Reasoning Model for Antimicrobial Resistance Prediction

bioRxiv Jun 7, 2026
The rapid global spread of antimicrobial resistance (AMR) has placed unprecedented pressure on clinical decision-making. Machine learning predictors of antibiotic susceptibility exist, but their lack of mechanistic grounding limits credibility. We pr...
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CREP: Cis-Regulatory Element Predictor Based on Fine-Tuned Enformer

bioRxiv Jun 7, 2026
A substantial fraction of disease-associated genetic variants reside in non-coding regions of the genome, where they act by perturbing cis-regulatory elements (CREs) such as enhancers, promoters, and insulators. While recent sequence-based deep learn...
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A Web-based software toolkit for accessible and best-practice machine learning analyses in biomedical research

bioRxiv Jun 7, 2026
Machine learning is increasingly central to biomedical research, but using machine learning well often requires substantial computational expertise and methodological care to produce high-quality results. To make machinelearning tools more accessible...
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Polynomial Trajectory Compression for Protein Language Model Embeddings

bioRxiv Jun 7, 2026
Protein language models (PLMs) generate rich, layer-wise embeddings that capture diverse biological information but are expensive in terms of storage and computation at scale. In this work, we propose a compact surrogate representation for PLM embedd...
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CytoGem-XAI:A Hypergraph Neural Network Framework for Genome-Scale Metabolic Modeling and Interpretable Analysis

bioRxiv Jun 7, 2026
Genome-scale metabolic models are essential for understanding cellular metabolism, yet existing deep learning approaches remain black boxes, and traditional flux balance analysis (FBA) cannot provide sample-specific predictions. To our knowledge, Cyt...
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Single-cell gene regulatory network reconstruction and key regulator identification using a dual-channel fusion graph convolutional network

bioRxiv Jun 7, 2026
Background and objective: Gene regulatory networks are formed by complex regulatory relationships between transcription factors and their target genes. A systematic understanding of these regulatory relationships is crucial for deciphering the molecu...
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Multi-level, multi-body atomic interaction graphs for machine learning-based prediction of protein-ligand binding energies

bioRxiv Jun 7, 2026
Accurate prediction of binding affinity is crucial for rational drug design and discovery. Traditional computational methods often rely on complex scoring functions that incorporate a multitude of physical and chemical descriptors, leading to high co...
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Quantifying Evidence for Competing Biomedical Hypotheses using Large Language Models and Bayesian Analysis

bioRxiv Jun 7, 2026
Science fundamentally depends on the generation and testing of hypotheses, many of them controversial. An explosion in scientific literature has made evaluating hypotheses even within a domain a problem of scale, and risks slowing an already extensiv...
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Epigenetic conditioning improves sequence-based modeling of gene regulation across cell types and alleles

bioRxiv Jun 7, 2026
Epigenetic state modulates gene regulation in a manner not always predictable from DNA sequence alone, yet current genomic deep learning models do not leverage epigenetic state as input. We present MethylSeqNet, a model that conditions pretrained seq...
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