AIMC Topic: Organelles

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OrgaMeas: A pipeline that integrates all the processes of organelle image analysis.

Biochimica et biophysica acta. Molecular cell research Apr 21, 2025
Although image analysis has emerged as a key technology in the study of organelle dynamics, the commonly used image-processing methods, such as threshold-based segmentation and manual setting of regions of interests (ROIs), are error-prone and labori...
Deep Learning Image Processing, Computer-Assisted Organelles Humans Software
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Deep learning-based segmentation of subcellular organelles in high-resolution phase-contrast images.

Cell structure and function Jul 31, 2024
Although quantitative analysis of biological images demands precise extraction of specific organelles or cells, it remains challenging in broad-field grayscale images, where traditional thresholding methods have been hampered due to complex image fea...
Microscopy, Phase-Contrast Organelles Humans Image Processing, Computer-Assisted Deep Learning HeLa Cells
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Automated segmentation of cell organelles in volume electron microscopy using deep learning.

Microscopy research and technique Mar 19, 2024
Recent advances in computing power triggered the use of artificial intelligence in image analysis in life sciences. To train these algorithms, a large enough set of certified labeled data is required. The trained neural network is then capable of pro...
Humans Deep Learning Imaging, Three-Dimensional Neural Networks, Computer Algorithms Organelles Volume Electron Microscopy Microscopy, Electron Saccharomyces cerevisiae Image Processing, Computer-Assisted HeLa Cells
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Deep learning, 3D ultrastructural analysis reveals quantitative differences in platelet and organelle packing in COVID-19/SARSCoV2 patient-derived platelets.

Platelets Nov 7, 2023
Platelets contribute to COVID-19 clinical manifestations, of which microclotting in the pulmonary vasculature has been a prominent symptom. To investigate the potential diagnostic contributions of overall platelet morphology and their α-granules and ...
Organelles RNA, Viral Blood Platelets SARS-CoV-2 Deep Learning Humans COVID-19
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Genetically encoded multimeric tags for subcellular protein localization in cryo-EM.

Nature methods Nov 6, 2023
Cryo-electron tomography (cryo-ET) allows for label-free high-resolution imaging of macromolecular assemblies in their native cellular context. However, the localization of macromolecules of interest in tomographic volumes can be challenging. Here we...
Electron Microscope Tomography Cryoelectron Microscopy Organelles Humans Neural Networks, Computer Ligands
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Self-supervised deep learning encodes high-resolution features of protein subcellular localization.

Nature methods Jul 25, 2022
Explaining the diversity and complexity of protein localization is essential to fully understand cellular architecture. Here we present cytoself, a deep-learning approach for fully self-supervised protein localization profiling and clustering. Cytose...
Proteins Protein Transport Organelles Deep Learning Cluster Analysis
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Screening membraneless organelle participants with machine-learning models that integrate multimodal features.

Proceedings of the National Academy of Sciences of the United States of America Jun 10, 2022
Protein self-assembly is one of the formation mechanisms of biomolecular condensates. However, most phase-separating systems (PS) demand multiple partners in biological conditions. In this study, we divided PS proteins into two groups according to th...
Proteome Proteins Humans Phosphorylation Organelles Internet Use Machine Learning Biomolecular Condensates
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Prediction of liquid-liquid phase separating proteins using machine learning.

BMC bioinformatics Feb 15, 2022
BACKGROUND: The liquid-liquid phase separation (LLPS) of biomolecules in cell underpins the formation of membraneless organelles, which are the condensates of protein, nucleic acid, or both, and play critical roles in cellular function. Dysregulation...
Humans Proteins Machine Learning Organelles
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Image-guided MALDI mass spectrometry for high-throughput single-organelle characterization.

Nature methods Sep 30, 2021
Peptidergic dense-core vesicles are involved in packaging and releasing neuropeptides and peptide hormones-critical processes underlying brain, endocrine and exocrine function. Yet, the heterogeneity within these organelles, even for morphologically ...
Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization High-Throughput Screening Assays Organelles Machine Learning Aplysia Animals
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Prediction of Sequential Organelles Localization under Imbalance using A Balanced Deep U-Net.

Scientific reports Feb 14, 2020
Assessing the structure and function of organelles in living organisms of the primitive unicellular red algae Cyanidioschyzon merolae on three-dimensional sequential images demands a reliable automated technique in the class imbalance among various c...
Microscopy, Electron, Scanning Mitosis Organelles Neural Networks, Computer Imaging, Three-Dimensional Rhodophyta Algorithms Image Processing, Computer-Assisted
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