bioRxiv

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Lab-in-the-loop therapeutic antibody design with deep learning

bioRxiv Jan 1, 2025
Therapeutic antibody design is a complex multi-property optimization problem with substantial promise for improvement with the application of machine-learning methods. Towards realizing that promise, we introduce “Lab-in-the-loop,” a new approach tha...
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Global gaps and priorities for shark and ray conservation: Integrating threat, function, and evolutionary distinctiveness

bioRxiv Jan 1, 2025
Elasmobranchs (sharks, rays, and skates) face unprecedented extinction risk, with over one-third of species threatened primarily by overfishing. While marine protected areas (MPAs) are essential tools to help safeguard marine ecosystems and the speci...
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SARS-CoV-2 Variant-Dependent Alterations in Nasopharyngeal Microbiota and Host Inflammatory Response

bioRxiv Jan 1, 2025
The SARS-CoV-2 pandemic saw multiple outbreaks occur over short periods. This was linked to the virus’s high infectivity and rapid mutation rate, which hindered the development of effective treatments and a comprehensive understanding of COVID-19 pat...
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Generative cerebral vasculature visualization using spatial transcriptomic data

bioRxiv Jan 1, 2025
The brain is sustained by an intricate vascular network that provides a continuous supply of nutrients and oxygen essential for its function. Understanding the structural variability and region-specific function of this neurovascular system is essent...
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Computational redesign of a thermostable T7 RNA polymerase

bioRxiv Jan 1, 2025
T7 RNA polymerase (T7 RNAP) is a foundational enzyme for biotechnology, but its utility for many potential applications is limited by low thermal stability of 43-44°C. While stabilized variants exist, the most stable commercial version has a propriet...
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Direct Training of Networks of Morris-Lecar Neurons with Backprop

bioRxiv Jan 1, 2025
Spiking Neural Networks (SNNs) have the potential to replicate the brain’s computational efficacy by explicitly incorporating action potentials or “spikes”, which is not a feature of most artificial neural networks. However, training SNNs is difficul...
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BehaveAI: a framework for rapidly detecting and classifying objects and behaviour from motion

bioRxiv Jan 1, 2025
Here we introduce BehaveAI, a biologically inspired video analysis framework that integrates static and motion information through a novel colour-from-motion encoding strategy. This method translates object movement – direction, speed, and accelerati...
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Inferring virtual cell environments using multi-agent reinforcement learning

bioRxiv Jan 1, 2025
Single cells interact continuously to form a cell environment that drives key biological processes. Cells and cell environments are highly dynamic across time and space, fundamentally governed by molecular mechanisms, such as gene expression. Recent ...
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Language may be all omics needs: Harmonizing multimodal data for omics understanding with CellHermes

bioRxiv Jan 1, 2025
Decoding cellular systems requires integrating diverse omics data, yet most models are trained from scratch on a single modality, restricting generalization. Here we present CellHermes, a biological language model that leverages pretrained large lang...
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Microbial Cell-Adaptive Segmentation in Quantitative Phase Imaging

bioRxiv Jan 1, 2025
Quantitative phase imaging (QPI) enables label-free microscopy with exceptional signal-to-background contrast and provides direct measurements of key biophysical parameters such as cell mass. Despite these advantages, QPI lacks a generalized, accurat...
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