bioRxiv

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CVAE-based Causal Representation Learning from Retinal Fundus Images for Age Related Macular Degeneration(AMD) Prediction

bioRxiv Jan 1, 2025
Regarding relatively poor prognosis and acute vision impairment, analyzing Age-Related Macular Degeneration, or AMD has been one of the most important tasks in retinal disease analysis. Especially, constructing methods to analyze and predict Wet AMD,...
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NiCLIP: Neuroimaging contrastive language-image pretraining model for predicting text from brain activation images

bioRxiv Jan 1, 2025
Predicting cognitive processes from brain activation maps has remained an open question within the neuroscience community for many years. Meta-analytic functional decoding methods aim to tackle this issue by providing a quantitative estimation of beh...
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Modeling Withdrawal States in Opioid-Dependent Mice with Machine Learning

bioRxiv Jan 1, 2025
Understanding opioid withdrawal behaviors in preclinical models is critical to improving therapeutic approaches for opioid use disorder (OUD). However, quantifying these withdrawal behaviors remains a difficult process for researchers, given the subt...
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Dynamic Graphs Analysis of EEG

bioRxiv Jan 1, 2025
In this study, we investigate the use of temporal dynamics in brain connectivity for the classification of electroencephalography (EEG) signals using dynamic Graph Neural Networks (GNNs). Our methods are applied to several large-scale EEG datasets fo...
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FIDDLE: a deep learning method for chemical formulas prediction from tandem mass spectra

bioRxiv Jan 1, 2025
Molecular identification through tandem mass spectrometry is fundamental in small molecule analysis, with formula identification serving as an initial step in the process. Current computational methods often struggle with accuracy, speed, and scalabi...
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Scaling Up Social Behavior Studies: Real-Time, Large-Scale and Prolonged Social Behavior Analysis with PrecisionTrack

bioRxiv Jan 1, 2025
Large-scale ethological behavioral studies can provide novel insights into the neuronal processes underlying complex and social behaviors, potentially opening new mental health research avenues. However, conducting such studies remains a tedious and ...
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MR-AIV reveals in vivo brain-wide fluid flow with physics-informed AI

bioRxiv Jan 1, 2025
The circulation of cerebrospinal and interstitial fluid plays a vital role in clearing metabolic waste from the brain, and its disruption has been linked to neurological disorders. However, directly measuring brain-wide fluid transport—especially in ...
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Protein Function Prediction via Contig-Aware Multi-Level Feature Integration

bioRxiv Jan 1, 2025
Proteins play a central role in biological processes, and accurately predicting their functions is crucial for biomedical research. While computational methods have advanced significantly, most approaches rely solely on sequence or structure, neglect...
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Improving polygenic risk prediction performance through integrating electronic health records by phenotype embedding

bioRxiv Jan 1, 2025
Large-scale biobanks provide comprehensive electronic health records (EHRs) that capture detailed clinical phenotypes, potentially enhancing disease risk prediction. However, traditional polygenic risk score (PRS) methods rely on simplified phenotype...
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Parabricks: GPU Accelerated Universal Pan-Instrument Genomics Analysis Software Suite

bioRxiv Jan 1, 2025
Next-generation sequencing (NGS) has transformed genomics, enabling breakthroughs in biotechnology, healthcare, and pharmaceuticals. However, exponential data growth-outpacing Moore’s Law-presents critical computational challenges for secondary analy...
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