bioRxiv

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Biomedical Hypothesis Explainability with Graph-Based Context Retrieval

bioRxiv Jan 1, 2025
We introduce an explainability method for biomedical hypothesis generation systems, built on top of the novel Hypothesis Generation Context Retriever framework. Our approach combines semantic graph-based retrieval and relevant data-restrictive traini...
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Biologically informed cortical models predict optogenetic perturbations

bioRxiv Jan 1, 2025
A recurrent neural network fitted to large electrophysiological datasets may help us understand the chain of cortical information transmission. In particular, successful network reconstruction methods should enable a model to predict the response to ...
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A study on edge devices for image classification of the Tasmanian devil (Sarcophilus harrisii) for vaccine delivery

bioRxiv Jan 1, 2025
A target-specific bait dispenser is required for oral bait vaccination of the endangered Tasmanian devil (Sarcophilus harrisii) against the deadly devil facial tumour disease. Development of a broadly extendible dispenser would be a beneficial ecolog...
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High-accuracy SNV calling for bacterial isolates using deep learning with AccuSNV

bioRxiv Jan 1, 2025
Accurate detection of mutations within bacterial species is critical for fundamental studies of microbial evolution, reconstructing transmission events, and identifying antimicrobial resistance mutations. While many tools have been developed to ident...
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Integration of In Vitro and In Silico Approaches Enables Prediction of Drug-Induced Liver Injury

bioRxiv Jan 1, 2025
Drug-induced liver injury (DILI) is a major cause of drug attrition and poses a significant threat to patient safety. However, current preclinical prediction methods, including heuristic screening rules, in vitro assays, machine learning models and a...
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Base-editing a single missense mutation in A20 enhances CAR-T cell efficacy

bioRxiv Jan 1, 2025
T cell exhaustion limits the efficacy of cancer immunotherapies. Here, we performed genome-wide loss-of-function screening in repetitively stimulated human T cells and identified the mulitfunctional ubiquitin-modifying protein A20/TNFAIP3 as a major ...
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Dynamic Meta-Networking Identifies Distinct Network Correlates of Positive and Negative Formal Thought Disorder in Schizophrenia

bioRxiv Jan 1, 2025
Formal thought disorder (FTD) is a core symptom of schizophrenia, yet the neural network mechanisms underlying this phenotype remain poorly understood. In this study, we applied a dynamic meta-networking framework, which captures temporally recurring...
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High-content live-cell time-lapse imaging predicts cells about to die via apoptosis

bioRxiv Jan 1, 2025
Cell death is a dynamic process that unfolds through time. Live-cell time-lapse imaging captures these dynamics in a way that’s impossible for static snapshots. High-content imaging (HCI), which has been developed for static microscopy, applied to ti...
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The Human Brain as a Dynamic Mixture of Expert Models in Video Understanding

bioRxiv Jan 1, 2025
The human brain is the most efficient and versatile system for processing dynamic visual input. By comparing representations from deep video models to brain activity, we can gain insights into mechanistic solutions for effective video processing, imp...
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A comprehensive functional landscape of α-tubulin TUBA1A variants illuminates microtubule biology and refines clinical classification

bioRxiv Jan 1, 2025
Missense variant interpretation in highly conserved, paralog-rich gene families remains a critical bottleneck for precision medicine. Here, we developed an integrated experimental-computational platform to systematically assess the functional impact ...
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