bioRxiv

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Clair-Mosaic: A deep-learning method for long-read mosaic small variant calling

bioRxiv Jan 1, 2025
Mosaic variants, defined as postzygotic mutations occurring during an organism’s development from zygote to adult, play critical roles in developmental biology, aging, and diseases such as cancer and neurological disorders. However, their accurate de...
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Ultrahigh throughput screening to train generative protein models for engineering specificity into unspecific peroxygenases

bioRxiv Jan 1, 2025
Enzyme engineering is central to developing biocatalysts with improved activity and specificity, yet traditional approaches are often limited by the scale of experimental screening. Here we combine ultrahigh-throughput microfluidic droplet screening ...
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The Human-In-the-Loop Drug Design Framework with Equivariant Rectified Flow

bioRxiv Jan 1, 2025
Advancements in AI-based drug design often face obstacles due to incomplete datasets, hindering progress to clinical trials. Human experts bring invaluable expertise and nuanced contextual understanding to drug design. There are two main difficulties...
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Notebook-based alignment of human and agentic reasoning in single-cell biology

bioRxiv Jan 1, 2025
Agentic AI is increasingly deployed on complex problems, often using chain-of-thought prompting to ground predictions in stepwise reasoning. In biomedical research, assistive agents could make this reasoning accessible to human scientists: for exampl...
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CeDNe: A multi-scale computational framework for modeling structure-function relationships in the C. elegans nervous system

bioRxiv Jan 1, 2025
Understanding how neural circuits generate behavior requires integrating structural and functional data across scales. C. elegans with its complete connectome, genetically identifiable neurons, single-cell transcriptome, neuropeptide-receptor distrib...
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Uncovering biological patterns across studies through automated large-scale reanalyses of public transcriptomic data

bioRxiv Jan 1, 2025
Large amounts of transcriptomic data have been made available in public repositories. Systematic reanalyses of these data offer the potential to identifying conserved biological patterns or context-specific signatures. However, this is a labour inten...
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ARCLID: Accurate and Robust Characterization of Long Insertions and Deletions in Genome

bioRxiv Jan 1, 2025
Structural variants (SVs) play crucial roles in genome diversity and disease, yet their accurate detection remains challenging, particularly under low sequencing coverage and within complex genomic regions. We present ARCLID, a deep learning–based SV...
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Designing optimal perturbation inputs for system identification in neuroscience

bioRxiv Jan 1, 2025
Investigating the dynamics of neural networks, which are governed by connectivity between neurons, is a fundamental challenge in neuroscience. Because passive (spontaneous) activity provides only limited information for estimating connectivity, pertu...
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Assessing the feasibility of machine learning for ancient DNA age prediction: limitations and insights

bioRxiv Jan 1, 2025
We investigated the possibility of estimating the age of ancient biological samples directly from their DNA damage profiles using supervised machine learning. Traditional dating methods such as radiocarbon dating, dendrochronology rely on either mate...
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BiosInt: Biosensor-based smart design of pathway dynamic regulation for industrial biomanufacturing

bioRxiv Jan 1, 2025
Industrial-scale production of bio-based chemicals in the circular green bioeconomy still faces inefficiencies arising from scaling up challenges. Biosensor mediated control of metabolic pathways has been proposed as a strategy to improve the perform...
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