bioRxiv

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MOAST: Mechanism of Action Similarity Tool

bioRxiv Jan 1, 2025
Determining the mechanism of action (MOA) for natural products remains a significant bottleneck in drug discovery, particularly for researchers with limited computational resources or small compound libraries. Traditional approaches require screening...
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Gene Specific Pathogenicity Predictor for Chromatin-Remodeling BAF Complex-Associated Neurodevelopmental Disorders

bioRxiv Jan 1, 2025
Advancements in whole genome sequencing have increased the number of variants of uncertain significance (VUS) identified in patient genomes. This has created a diagnostic bottleneck for genetic counselors tasked with sifting through these variants an...
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Effective sequence-to-expression prediction for membrane proteins using machine learning and computational protein design

bioRxiv Jan 1, 2025
The recombinant expression of integral membrane proteins is notoriously challenging. One way to address this challenge is via computational genotype-to-phenotype models that determine how particular sequence features correlate with protein expression...
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Museum collections and machine learning guide discovery of novel coronaviruses and paramyxoviruses

bioRxiv Jan 1, 2025
Natural history museum collections are valuable but underutilized resources for viral discovery, offering opportunities to test hypotheses about viral occurrence across space, time, and taxonomic groups. We developed machine learning models of bat ho...
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From Chewing to Chirping: The Misophonia Audiovisual Trigger Archive (MATA)

bioRxiv Jan 1, 2025
Misophonia is an emerging condition in which everyday sounds, such as chewing, sniffing, or tapping, evoke disproportionately intense emotional and physiological responses. Despite growing recognition of its clinical significance, progress in underst...
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Machine Learning-Guided Synthetic Microbial Communities Enable Functional and Sustainable Degradation of Persistent Environmental Pollutants

bioRxiv Jan 1, 2025
Persistent environmental pollutants demand the use of diverse microbial metabolic capabilities for effective degradation. While naturally occurring consortia or single strains often fall short in efficiency, synthetic microbial communities (SynComs) ...
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HRDPath: An Explainable Multi-Model Deep Learning Architecture for Predicting Homologous Recombination Deficiency from Histopathology Images

bioRxiv Jan 1, 2025
Homologous recombination deficiency (HRD) is a critical biomarker for guiding treatment decisions in high-grade serous tubo-ovarian carcinoma (HGSOC), a cancer with few reliable biomarkers. However, existing genomic-based tests for HRD are variable, ...
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Scalable and interpretable secretion system annotation with Sismis

bioRxiv Jan 1, 2025
Secretion systems play critical roles in bacterial growth, survival, and pathogenesis. Genes encoding secretion system components often co-occur together as gene clusters in bacterial (meta)genomes. However, existing tools for secretion system annota...
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ppIRIS: deep learning for proteome-wide prediction of bacterial protein-protein interactions

bioRxiv Jan 1, 2025
Protein–protein interactions (PPIs) are central to cellular processes and host–pathogen dynamics, yet bacterial interactomes remain poorly mapped, especially for extracellular effectors and cross-species interactions. Experimental approaches provide ...
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Query Augmented Generation (QAG) from the Genomic Data Commons for Accurate Variant Statistics

bioRxiv Jan 1, 2025
In precision oncology, researchers often use public knowledgebases to check somatic variant frequencies against their cohort data. Large language models (LLMs) can quickly answer questions on somatic variant frequencies, but often hallucinate and giv...
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