AIMC Journal:
bioRxiv

Showing 51 to 60 of 4935 articles

Desktop iDMS: A stand-alone application of intelligent differential mobility spectrometry (iDMS), a neural net-work that predicts optimal separation and compensa-tion voltages for field asymmetric differential ion mobil-ity spectrometry

bioRxiv Oct 7, 2026
Summary: Mass spectrometry resolution of glycosphingolipids requires advanced separation methods. The virtual-ly identical structures of glycolipid epimers cannot be discriminated by routine multiple reaction monitoring-high-performance liquid chroma...
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Protein Language Model-Conditioned Graph Neural Networks for Multitask GPCR Ligand Activity Prediction

bioRxiv Oct 7, 2026
Predicting ligand activity across G protein-coupled receptors (GPCRs) requires models that capture both molecular structure and receptor-specific information while remaining robust to chemical and target-domain shift. We developed a multimodal graph ...
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Causal event structure shapes convergent reactivation signatures in human cortex and language model

bioRxiv Oct 7, 2026
Humans adapt to changing environments by understanding the latent causal structure of events, and modern large language models (LLMs) increasingly exhibit analogous abilities. However, elucidating how causal knowledge is represented and integrated in...
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AntiCapt: Fine-Tuned Nucleotide Language Models for Predicting and Designing Anticancer Aptamers

bioRxiv Oct 7, 2026
Over the past decade, aptamers have emerged as promising therapeutics, with cancer therapeutics as a major research area. Existing computational methods, however, either predict aptamer-target pairs or design aptamers against a specific target. In th...
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BettaAI: a machine-learning object detection model for the quantification of aggressive displays in the Siamese fighting fish Betta splendens

bioRxiv Oct 6, 2026
The Siamese fighting fish (Betta splendens) is well-known for its high levels of aggression and complex, stereotyped displays, making it an ideal model for testing deep learning-based tools for high-throughput, unbiased quantification of aggressive b...
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Predicted structure of the complete CPLANE complex reveals novel interactors and mechanisms of Jbts17 during ciliogenesis

bioRxiv Oct 6, 2026
Cilia are highly conserved organelles that use hundreds of unique proteins to drive extracellular motility and serve as signaling hubs for eukaryotic cells. The Ciliogenesis and Planar Polarity Effector (CPLANE) protein complex controls basal body do...
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Intrinsic dimensionality of deep learning representations reveals cell death-associated heterogeneity in Parkinsons disease iPSC-derived neurons

bioRxiv Oct 6, 2026
As AI is increasingly used to stratify heterogeneous Parkinsons disease, it is essential to determine whether learned representations preserve disease-relevant variation within diagnostic or genetic groups. In iPSC-derived neurons from three familial...
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GRASP: Graph Representation Learning with Assay Supervision for Molecular Properties

bioRxiv Oct 6, 2026
Molecular structures are abundant, while experimental bioactivity is sparse and distributed across assays. We introduce GRASP, a 93.5M-parameter graph Transformer that learns from these sources in sequence. GRASP first learns molecular structure thro...
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Mechanistic classification of the AAA superfamily with protein language models

bioRxiv Oct 6, 2026
The ATPases Associated with various cellular Activites (AAA) are a class of proteins with diverse structure-function relationships whereby conserved 3-dimensional architecture is employed in varied mechanistic contexts. While cryo-electron microscopy...
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Machine Learning Identification of Functional Trait Syndromes Associated with Responsiveness to Arbuscular Mycorrhizal Fungi

bioRxiv Oct 6, 2026
Arbuscular mycorrhizal fungi (AMF) are widespread plant symbionts that enhance nutrient acquisition, growth, and stress tolerance, yet plant responsiveness to AMF varies substantially and remains difficult to predict. We developed Trait2Myco, a Rando...
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