bioRxiv

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MetaPaCS: A Novel Meta-Learning Framework for Pancreatic Cancer Subtype Identification

bioRxiv Jan 1, 2025
As the third leading cause of cancer related deaths in the United States, pancreatic cancer (PaC) is a highly heterogenous malignancy that can be divided into a multitude of potential subtypes, with the main 4 consisting of aberrantly differentiated ...
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AI-assisted modeling of attention quantifies engagement and predicts cognitive improvement in older adults

bioRxiv Jan 1, 2025
Cognitive training aims to prevent or slow cognitive decline in older adults, but outcomes vary widely. Engagement, describing how individuals allocate cognitive, affective, and physiological resources, is critical to training benefits, yet behaviora...
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Protein Compositional Ratio Representation (PCRR) Systematically Improves Human Disease Prediction

bioRxiv Jan 1, 2025
Plasma proteomics captures a functional snapshot of human physiology; yet, most machine learning models treat protein abundances as independent variables, ignoring the fact that biological systems and proteomic measurements are inherently composition...
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Encoding and Decoding of Brain Dynamic Functional Connectivity for ADHD Diagnosis

bioRxiv Jan 1, 2025
Recent studies have demonstrated strong associations between the changes in dynamic functional connectivity (FC) and both behavioral and cognitive functions. The sliding window technique is the most widely used method for evaluating dynamic FC; howev...
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Epigenetic profile drives accurate survival prediction in breast cancer via a multi-omics machine learning model

bioRxiv Jan 1, 2025
Accurate overall survival (OS) prediction is key for personalized treatment in breast cancer, but mutation burden alone is insufficient. To improve prognostic accuracy, we integrated genomic, transcriptomic, proteomic, epigenetic, and clinical featur...
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Towards Video-LLM Driven Workflow for Behavioral Segmentation and Scoring in Mice Performing a Skilled Water Reaching Task: An Evaluation of Recent LLM Models

bioRxiv Jan 1, 2025
Behavior scoring is labor-intensive and subjective, introducing variability in results. Large Language Models (LLMs) capable of video understanding offer a transformative solution to manual scoring, crucial for accelerating and standardizing neurosci...
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PocketX: Preference Alignment for Protein Pockets Design through Group Relative Policy Optimization

bioRxiv Jan 1, 2025
Designing protein pockets that target specific ligands is crucial for drug discovery and enzyme engineering. Although deep generative models show promise in proposing high-quality pockets, they are usually trained purely to match the data distributio...
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Population trajectory analysis reveals divergent state-space geometries across cortical excitatory cell types

bioRxiv Jan 1, 2025
Cortical population activity unfolds along structured trajectories in state space, reflecting underlying dynamics of the neural networks involved. However, how such geometry differs across neural cell types remains poorly understood. Using a large-sc...
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Explainable 3D CNNs link regional and network level disruption in early Parkinson’s MRIs to symptom progression

bioRxiv Jan 1, 2025
Parkinson’s Disease (PD) is a progressive neurodegenerative disorder affecting approximately 1% of the population over 65. Clinical diagnosis typically depends on tracking gradually developing motor symptoms as the disease progresses, underscoring th...
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Helix: a structure-aware deep learning model for accurate prediction of A-to-I RNA editing by endogenous ADARs

bioRxiv Jan 1, 2025
Adenosine deaminase acting on RNA (ADAR) converts adenosine to inosine within double-stranded RNA (dsRNA) and can be co-opted for therapeutic RNA editing by introducing dsRNA substrates in trans using programmable guide RNAs (gRNAs). However, ADAR’s ...
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