AIMC Journal:
bioRxiv

Showing 581 to 590 of 4935 articles

Explainable HGT-based framework for predicting human dark kinase protein-pathway associations by leveraging BERT-based embeddings and WGAN-GP

bioRxiv Aug 4, 2026
Discovery of pathway associations and druggability can leverage underutililized dark kinase genes for treating complex diseases (proven for cancer and neurodegeneration), boosted with computational methods. Herein, we employ BERT-based embeddings of ...
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Operationalising LLM-assisted screening of literature to support systematic reviews

bioRxiv Aug 3, 2026
Large language models (LLMs) can ease the work of screening titles and abstracts for systematic reviews, but obtaining reliable results requires researchers to make practical choices about which LLMs to use, how to combine their scores into a ranking...
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PG-LLM: Benchmarking General-Purpose Language Models for Protein Variant Ranking

bioRxiv Aug 3, 2026
eneral-purpose language models are being increasingly utilized in protein-design workflows, yet their ability to evaluate variant effects remains unclear. To answer this question, we introduce PG-LLM, a benchmark built on ProteinGym to evaluate gener...
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A data-driven approach to automate embolism detection in leaves

bioRxiv Aug 3, 2026
- Embolism, the formation of air bubbles in the plant water transport system, is a mechanistic driver of plant death. The Optical Vulnerability Technique (OVT) is an imaging method for non-invasive quantification of embolism (including P50, a common ...
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A sequence-to-function model to predict T7 transcription rates and redesign T7 expression systems with lowered production of immunogenic RNA byproducts

bioRxiv Aug 3, 2026
T7 RNA polymerase is widely used to produce RNA using a canonical T7 promoter; however, it will also bind to low-affinity sites to generate cryptic transcription and produce RNA byproducts, which reduce full-length mRNA purity and yield. When manufac...
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Genome-scale prediction of context-specific synthetic lethality beyond protein interaction networks

bioRxiv Aug 3, 2026
Identifying synthetic lethal (SL) interactions offers a principled framework for discovering disease-specific therapeutic targets. However, current machine learning approaches heavily rely on curated protein-protein interaction networks. Because thes...
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Interpretable Machine Learning Model of Receptor Dynamics Reveals AT1R Allostery and a Negative Allosteric Modulator

bioRxiv Aug 3, 2026
Allosteric modulation of G protein-coupled receptors (GPCRs) offers major advantages in receptor selectivity and signaling control; yet systematic approaches to identify allosteric modulators, define their binding sites, and map the underlying allost...
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Combining Machine Learning and Directed Evolution for Optimization of a Monooxygenase

bioRxiv Aug 3, 2026
L-3,4-dihydroxyphenylalanine (L-Dopa) is an important pharmaceutical for the treatment of Parkinson's disease and a precursor to numerous catechol-containing compounds. The flavin-dependent monooxygenase HpaBC is a promising biocatalyst for microbial...
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Explainable Generative AI Uncovers a Molecular Continuum in Medulloblastoma with Implications for Rare Cancer Subtyping and Treatment Equity

bioRxiv Aug 3, 2026
Medulloblastoma is a childhood brain tumor traditionally classified into four molecular subgroups. Recent evidence suggests that Groups 3 and 4 represent a biological continuum rather than distinct entities, a paradigm shift with significant implicat...
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The aging rhythm: spatio-temporal dynamics of resting alpha oscillations in young and older brains

bioRxiv Aug 3, 2026
Aging is associated with substantial alterations in brain oscillatory activity, particularly within the alpha band (8 -12 Hz). Yet, little is known about how aging affects the spatial propagation of alpha oscillations across cortical networks. In add...
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