ArticleBiomolecules2021
Convolutional Neural Network-Based Artificial Intelligence for Classification of Protein Localization Patterns.
Article in Biomolecules, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed.
- Transfer Learning Approach with Features Block Selection via Genetic Algorithm for High-Imbalance and Multi-Label Classification of HPA Confocal Microscopy Images.Bioengineering (Basel, Switzerland) · 2025Article
- Deciphering Membrane Proteins Through Deep Learning Models by Revealing Their Locale Within the Cell.Bioengineering (Basel, Switzerland) · 2024Article
- Bibliometric analysis of the application of deep learning in cancer from 2015 to 2023.Cancer imaging : the official publication of the International Cancer Imaging Society · 2024Article
- Molecular Mechanisms of Medicinal PlantCurrent pharmaceutical design · 2024Article
- Cueing effect of attention among nurses with different anxiety levels: an EEG study.Medical & biological engineering & computing · 2023Article
- Assessing Metabolic Markers in Glioblastoma Using Machine Learning: A Systematic Review.Metabolites · 2023Review
- Data augmentation with improved regularisation and sampling for imbalanced blood cell image classification.Scientific reports · 2022Article
- Entity relation extraction in the medical domain: based on data augmentation.Annals of translational medicine · 2022Article
- Extraction of entity relations from Chinese medical literature based on multi-scale CRNN.Annals of translational medicine · 2022Article
- Resource Management through Artificial Intelligence in Screening Programs-Key for the Successful Elimination of Hepatitis C.Diagnostics (Basel, Switzerland) · 2022Article
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
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 method to assess protein localizations, with increasing demand of automated high throughput analysis methods to supplement the technical advancements in high throughput imaging. Here, we study the applicability of deep neural network-based artificial intelligence in classification of protein localization in 13 cellular subcompartments. We use deep learning-based on convolutional neural network and fully convolutional network with similar architectures for the classification task, aiming at achieving accurate classification, but importantly, also comparison of the networks. Our results show that both types of convolutional neural networks perform well in protein localization classification tasks for major cellular organelles. Yet, in this study, the fully convolutional network outperforms the convolutional neural network in classification of images with multiple simultaneous protein localizations. We find that the fully convolutional network, using output visualizing the identified localizations, is a very useful tool for systematic protein localization assessment.
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Registered trials
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