bioRxiv

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A hardwired neural circuit for temporal difference learning

bioRxiv Jan 1, 2025
The neurotransmitter dopamine plays a major role in learning by acting as a teaching signal to update the brain’s predictions about rewards. A leading theory proposes that this process is analogous to a reinforcement learning algorithm called tempora...
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Single-sequence deep learning delivers crystal-quality models of covalent K-Ras G12 hotspot complexes

bioRxiv Jan 1, 2025
Structure-based design of covalent drugs has achieved tremendous success by understanding and leveraging the three-dimensional interactions between small-molecule drug candidates and their protein targets. However, this approach traditionally relies ...
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Pre-Training for Large-Scale Functional Connectome Fingerprinting Supports Generalization and Transfer Learning in Functional Neuroimaging

bioRxiv Jan 1, 2025
Functional MRI currently supports a limited application space stemming from modest dataset sizes, large interindividual variability and heterogeneity among scanning protocols. These constraints have made it difficult for fMRI researchers to take adva...
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A mean-field model of neural networks with PV and SOM interneurons reveals connectivity-based mechanisms of gamma oscillations

bioRxiv Jan 1, 2025
Classic theoretical models of cortical oscillations are based on the interactions between two populations of excitatory and inhibitory neurons. Nevertheless, experimental studies and network simulations suggest that interneuron subclasses such as par...
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Decoding RNA–RNA Interactions: The Role of Low-Complexity Repeats and a Deep Learning Framework for Sequence-Based Prediction

bioRxiv Jan 1, 2025
RNA–RNA interactions (RRIs) are fundamental to gene regulation and RNA processing, yet their molecular determinants remain unclear. In this work, we analyze several large-scale RRI datasets and identify low-complexity repeats (LCRs), including simple...
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Attcatvgg-Net: an Explainable Multioutput Deep Learning Framework for Cataract Stage Classification and Visual Acuity Regression using Multicolor Fundus Images

bioRxiv Jan 1, 2025
The purpose of this study is to develop and evaluate an attention-guided deep learning model using the multicolor imaging module of Spectralis Optical Coherence Tomography (OCT) imaging for automated cataract severity classification and Visual Acuity...
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Machine learning–assisted selection of informative loci for strain-level phylogenetics of Neisseria gonorrhoeae

bioRxiv Jan 1, 2025
Epidemiological surveillance of Neisseria gonorrhoeae is hindered by the limitations of existing molecular typing methods, such as NG-MAST and MLST, which either suffer from excessive variability or insufficient resolution. In this study, we propose ...
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Transformer Networks Enable Robust Generalization of Source Localization for EEG Measurements

bioRxiv Jan 1, 2025
An electroencephalogram (EEG) is an electrical measurement of brain activity using electrodes placed on the scalp surface. After EEG measurements are collected, numerical methods and algorithms can be employed to analyze these measurements and attemp...
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AGAPE (computAtional G-quadruplex Affinitiy PrEdiction): The first Artificial Intelligence workflow for G-quadruplex binding affinity prediction

bioRxiv Jan 1, 2025
AGAPE (computational G-quadruplex Affinity Prediction) is a novel machine learning (ML)-based tool designed to predict the binding and stabilizing potential of small molecules targeting G-quadruplexes (G4s). G4s, prevalent in telomeres and oncogene p...
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HXMS: a standardized file format for HX/MS data

bioRxiv Jan 1, 2025
Hydrogen-deuterium exchange/mass spectrometry (HX/MS) is a rapidly expanding technique used to investigate protein conformational ensembles. The growing popularity and utility of HX/MS has driven the development of diverse instrumentation and softwar...
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