bioRxiv

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Medical Abbreviation Disambiguation with Large Language Models: Zero- and Few-Shot Evaluation on the MeDAL Dataset

bioRxiv Jan 1, 2025
Abbreviation disambiguation is a critical challenge in processing clinical and biomedical texts, where ambiguous short forms frequently obscure meaning. In this study, we assess the zero-shot performance of large language models (LLMs) on the task of...
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Unified Protein-Small Molecule Graph Neural Networks for Binding Site Prediction

bioRxiv Jan 1, 2025
Predicting small molecule binding sites on proteins remains a key challenge in structure-based drug discovery. While AlphaFold3 has transformed protein structure prediction, accurate identification of functional sites such as ligand binding pockets r...
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Rapid and Interpretable Protein Contact Map Prediction Using a Pattern-Matching Strategy

bioRxiv Jan 1, 2025
Protein sequence determines the structure, function, and dynamics of a protein. In recent years, enormous progress has been made in translating sequence information into structural information using machine learning approaches. However, because of th...
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Voltage-dependent reversal potentials in spiking recurrent neural networks enhance energy efficiency and task performance

bioRxiv Jan 1, 2025
Spiking recurrent neural networks (SRNNs) rival gated RNNs on various tasks, yet they still lack several hallmarks of biological neural networks. We introduce a biologically grounded SRNN that implements Dale’s law with voltage-dependent AMPA and GAB...
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Aging diminishes interlaminar functional connectivity in the mouse cortical V1 and CA1 hippocampal regions

bioRxiv Jan 1, 2025
Aging disrupts brain network integration and is a significant risk factor for cognitive decline and neurological diseases, yet the circuit-level mechanisms underlying these changes remain unclear. Most previous studies have utilized cross-sectional o...
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Ultraconserved elements and machine learning classifiers enable robust phylogenetics and taxonomy in model and non-model nematodes

bioRxiv Jan 1, 2025
Nematodes are among the most diverse animals, yet only around 28,000 of an estimated one million species have been morphologically described. Their small size, morphological simplicity, and cryptic diversity complicate phylogenetic analyses. Traditio...
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Fine-tuning sequence to function deep learning models on large-scale proteomic data improves the accuracy of variant effect prediction

bioRxiv Jan 1, 2025
Fine-tuning sequence to function models has shown promise for variant effect prediction, but accuracy and generalization to unseen genes and unseen individuals remains a standing challenge. We fine-tuned Borzoi on 54,219 individuals and 2,923 circula...
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ET-Pfam: Ensemble transfer learning for protein family prediction

bioRxiv Jan 1, 2025
Due to the rapid growth of sequence generation, which has surpassed the expert curators ability to manually review and annotate them, the computational annotation of proteins remains a significant challenge in bioinformatics nowadays. The Pfam databa...
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Inferring spatial single-cell-level interactions through interpreting cell state and niche correlations learned by self-supervised graph transformer

bioRxiv Jan 1, 2025
Cell-cell interactions (CCI), driven by distance-dependent signaling, are important for tissue development and organ function. While imaging-based spatial transcriptomics offers unprecedented opportunities to unravel CCI at single-cell resolution, cu...
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Postprocessing-Enhanced Machine Learning for Reliable Real-Time Sleep Staging in Closed-Loop Neuromodulation

bioRxiv Jan 1, 2025
Real-time sleep stage classification is important for closed-loop neuromodulation at certain stages during sleep, yet current models often yield noisy and unstable outputs that risk false triggers. These fluctuations, especially near stage boundaries...
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