AIMC Topic: Subcellular Fractions
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Proteomics and Machine Learning-Based Approach to Decipher Subcellular Proteome of Mouse Heart.
Molecular & cellular proteomics : MCP
Mar 18, 2025
Protein compartmentalization to distinctive subcellular niches is critical for cardiac function and homeostasis. Here, we employed a rapid and robust workflow based on differential centrifugal-based fractionation with mass spectrometry-based proteomi...
Label-free multiplexed microtomography of endogenous subcellular dynamics using generalizable deep learning.
Nature cell biology
Dec 7, 2021
Simultaneous imaging of various facets of intact biological systems across multiple spatiotemporal scales is a long-standing goal in biology and medicine, for which progress is hindered by limits of conventional imaging modalities. Here we propose us...
Animals
Deep Learning
Cell Line, Tumor
Single-Cell Analysis
Humans
Lipid Droplets
Subcellular Fractions
Electron Microscope Tomography
COS Cells
HEK293 Cells
Cell Nucleus
Actins
Refractometry
Cell Nucleolus
Cell Membrane
Optical Imaging
Chlorocebus aethiops
HeLa Cells
3T3 Cells
Imaging, Three-Dimensional
Mice
Mitochondria
Convolutional Neural Network-Based Artificial Intelligence for Classification of Protein Localization Patterns.
Biomolecules
Feb 11, 2021
Identifying localization of proteins and their specific subpopulations associated with certain cellular compartments is crucial for understanding protein function and interactions with other macromolecules. Fluorescence microscopy is a powerful metho...
Use of Chou's 5-steps rule to predict the subcellular localization of gram-negative and gram-positive bacterial proteins by multi-label learning based on gene ontology annotation and profile alignment.
Journal of integrative bioinformatics
Jun 29, 2020
To date, many proteins generated by large-scale genome sequencing projects are still uncharacterized and subject to intensive investigations by both experimental and computational means. Knowledge of protein subcellular localization (SCL) is of key i...
Application of deep convolutional neural networks in classification of protein subcellular localization with microscopy images.
Genetic epidemiology
Jan 4, 2019
Single-cell microscopy image analysis has proved invaluable in protein subcellular localization for inferring gene/protein function. Fluorescent-tagged proteins across cellular compartments are tracked and imaged in response to genetic or environment...
Deep learning enables cross-modality super-resolution in fluorescence microscopy.
Nature methods
Dec 17, 2018
We present deep-learning-enabled super-resolution across different fluorescence microscopy modalities. This data-driven approach does not require numerical modeling of the imaging process or the estimation of a point-spread-function, and is based on ...
Deep learning is combined with massive-scale citizen science to improve large-scale image classification.
Nature biotechnology
Aug 20, 2018
Pattern recognition and classification of images are key challenges throughout the life sciences. We combined two approaches for large-scale classification of fluorescence microscopy images. First, using the publicly available data set from the Cell ...
Prediction of Apoptosis Protein's Subcellular Localization by Fusing Two Different Descriptors Based on Evolutionary Information.
Acta biotheoretica
Mar 12, 2018
The apoptosis protein has a central role in the development and the homeostasis of an organism. Obtaining information about the subcellular localization of apoptosis protein is very helpful to understand the apoptosis mechanism and the function of th...
Efficient computational model for classification of protein localization images using Extended Threshold Adjacency Statistics and Support Vector Machines.
Computer methods and programs in biomedicine
Feb 2, 2018
BACKGROUND AND OBJECTIVE: Discriminative and informative feature extraction is the core requirement for accurate and efficient classification of protein subcellular localization images so that drug development could be more effective. The objective o...
Machine learning to design integral membrane channelrhodopsins for efficient eukaryotic expression and plasma membrane localization.
PLoS computational biology
Oct 23, 2017
There is growing interest in studying and engineering integral membrane proteins (MPs) that play key roles in sensing and regulating cellular response to diverse external signals. A MP must be expressed, correctly inserted and folded in a lipid bilay...
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