bioRxiv

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Novel Machine Learning-based Approach to Identify Viral Biomarkers of Human Respiratory Emissions from Oral and Nasal Metagenomes

bioRxiv Jan 1, 2025
Humans spend approximately 90% of their lives in built environments, making virus transmission indoors a key determinant of health. Environmental sampling of respiratory viral pathogens is often challenging because of frequent non-detect measurements...
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Integrative Transcriptomic and Machine Learning Approaches to decipher Mitochondrial Gene Regulation in severe Plasmodium vivax Malaria

bioRxiv Jan 1, 2025
Mitochondria in Plasmodium vivax are functionally vital despite possessing a highly reduced genome and differing substantially from the human organelle. Beyond their classical role in energy production, they dynamically coordinate processes like pyri...
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A theory for self-sustained balanced states in absence of strong external currents

bioRxiv Jan 1, 2025
Recurrent neural networks with balanced excitation and inhibition exhibit irregular asynchronous dynamics, which is fundamental for cortical computations. Classical balance mechanisms require strong external inputs to sustain finite firing rates, rai...
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GPT-4 accurately predicts human emotions and their neural correlates

bioRxiv Jan 1, 2025
Emotions are evoked by both internal and external events related to survival challenges. Recent advances in multimodal large language models ((M)LLMs), such as GPT-4, enable them to accurately analyze and describe complex visual scenes, raising the q...
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Large-scale experimental validation of phenotype-guided generative AI for de novo drug discovery

bioRxiv Jan 1, 2025
Generative AI is increasingly used to design drugs with desired physicochemical and biological properties. We have previously used the cGAN algorithm trained on cell painting data to generate molecules targeting 10 molecular cancer targets. Here, we ...
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Graph-Based Modeling of Alzheimer’s Protein Interactions via Spiking Neural, Hyperdimensional Encoding, and Scalable Ray-Based Learning

bioRxiv Jan 1, 2025
This study introduces a novel computational framework for predicting protein-protein interactions (PPIs) in Alzheimer’s disease by integrating biologically inspired and graph-based learning paradigms. The pipeline combines genetic algorithm-driven fe...
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NanTex enables computational multiplexing and phenotyping of organelles across super-resolution modalities

bioRxiv Jan 1, 2025
Super-resolution microscopy (SRM) enables nanoscale visualization of cellular organelles but remains constrained by spectral overlap, labeling requirements, and temporal offsets in multicolor imaging. We present NanTex, a deep learning framework that...
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Lung Adenocarcinoma Just Desserts: An Expanding Pie of Activating Oncogenes or a Layer Cake of Integrated Alterations

bioRxiv Jan 1, 2025
The molecular landscape of lung adenocarcinoma (LUAD) is often summarized as a “pie chart” of driver oncogenes, suggesting identification and targeting of oncogenic drivers is the best clinical approach. However, this model oversimplifies LUAD biolog...
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Inferring Dynamic Information from Protein Structures by Gaussian Integrals and Deep Learning

bioRxiv Jan 1, 2025
Protein conformational flexibility underlies a wide range of biological functions, yet experimentally probing dynamics at atomic resolution remains costly and low-throughput. Here, we present a deep learning framework that predicts protein flexibilit...
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An integrative machine learning approach identifies the centrality of ferroptosis, cuproptosis, and immune pathway crosstalk for breast cancer stratification and therapy guidance

bioRxiv Jan 1, 2025
Breast cancer (BRCA) is a leading cause of cancer-related mortality in women, characterized by marked heterogeneity in molecular subtypes, immune microenvironment, and therapeutic response. Current gene expression classifiers often lack mechanistic g...
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