bioRxiv

Showing 4511 to 4520 of 5021 articles

Evaluation of a structure-based method for ab initio gene detection using deep learning

bioRxiv Jan 1, 2025
In this work, a novel method for the detection of exons within genomic DNA sequences was implemented and evaluated. This is a structure-based approach, inspired by recent work from Sharma et al., by which nucleotide sequences are converted into physi...
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Design principles of neuromorphic computing using genetic circuits

bioRxiv Jan 1, 2025
Cells have evolved to sense a wide range of input combinations and integrate those signals through signaling pathways to produce context-specific responses, such as differentiation, cell-type specification, and patterning. To replicate this informati...
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Fitness Landscape for Antibodies 2: Benchmarking Reveals That Protein AI Models Cannot Yet Consistently Predict Developability Properties

bioRxiv Jan 1, 2025
A prominent application of machine learning in therapeutic antibody design is the development of models that can generate or screen antibody candidates with a high probability of success in manufacturing and clinical trials. These models must accurat...
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Deep learning to overcome human error and bias in electrode position extraction in tDCS-fMRI studies

bioRxiv Jan 1, 2025
Combining transcranial direct current stimulation (tDCS) with fMRI enables investigation of stimulation effects, while structural MRI verifies electrode positioning, critical for focal montages where minor misplacements reduce target current dose. Cu...
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PatchDNA: A Flexible and Biologically-Informed Alternative to Tokenization for DNA

bioRxiv Jan 1, 2025
DNA language models are emerging as powerful tools for representing genomic sequences, with recent progress driven by self-supervised learning. However, performance on downstream tasks is sensitive to tokenization strategies reflecting the complex en...
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Accurate Variant Classification in Tumour-Only Genomic Data Using Interpretable Tabular Models

bioRxiv Jan 1, 2025
Recent work has shown that machine learning can provide a reliable tool to classify somatic and rare germline variants in cancer studies where matched-normal samples are not available. Here, we present a workflow that combines an opensource pipeline ...
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Hierarchical Community Structure of the Adult Drosophila Connectome Reveals Conserved Circuit Archetypes

bioRxiv Jan 1, 2025
Biological neural networks can be meaningfully partitioned into sub-networks referred to as communities. Community structure is thought to support functional specialization, adaptability, and cost-efficient wiring. While many studies have focused on ...
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Curvature-based machine learning method for automated segmentation of dendritic spines

bioRxiv Jan 1, 2025
Recent advances in connectomics have been led by high-resolution reconstruction of large volumes of neural tissues using electron microscopy (EM), providing unprecedented insights into brain structure and function. Dendritic spines—dynamic protrusion...
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Prediction of Piconewton Receptor Tension Images using Deep Learning

bioRxiv Jan 1, 2025
Piconewton (pN) receptor forces govern many biological processes, but measuring these forces remains challenging. Molecular tension probes (MTPs) provide a sensitive means to measure pN cellular forces via fluorescence microscopy; however, MTPs are c...
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LoMuS: Low-Rank Adaptation with Multimodal Representations Improves Protein Stability Prediction

bioRxiv Jan 1, 2025
Protein folding stability is a key determinant for understanding protein dynamics, including molecular function, pathogenicity, and/or protein engineering. Yet, accurate prediction of protein stability changes remains a challenging problem due to the...
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