Bioimage-based protein subcellular location prediction: a comprehensive review

YY Xu, LX Yao, HB Shen - Frontiers of Computer Science, 2018 - Springer
Subcellular localization of proteins can provide key hints to infer their functions and
structures in cells. With the breakthrough of recent molecule imaging techniques, the usage …

Positive-unlabelled learning of glycosylation sites in the human proteome

F Li, Y Zhang, AW Purcell, GI Webb, KC Chou… - BMC …, 2019 - Springer
Background As an important type of post-translational modification (PTM), protein
glycosylation plays a crucial role in protein stability and protein function. The abundance …

Review of research on biomedical image processing based on pattern recognition

Y XU, H SHEN - 电子与信息学报, 2020 - jeit.ac.cn
Pattern recognition algorithms can discover valuable information from mass data of
biomedical images as guide for basic research and clinical application. In recent years, with …

Robust classification of cell cycle phase and biological feature extraction by image-based deep learning

Y Nagao, M Sakamoto, T Chinen… - Molecular biology of …, 2020 - Am Soc Cell Biol
Across the cell cycle, the subcellular organization undergoes major spatiotemporal changes
that could in principle contain biological features that could potentially represent cell cycle …

SIFLoc: a self-supervised pre-training method for enhancing the recognition of protein subcellular localization in immunofluorescence microscopic images

Y Tu, H Lei, HB Shen, Y Yang - Briefings in Bioinformatics, 2022 - academic.oup.com
With the rapid growth of high-resolution microscopy imaging data, revealing the subcellular
map of human proteins has become a central task in the spatial proteome. The cell atlas of …

Active semi-supervised learning for biological data classification

G Camargo, PH Bugatti, PTM Saito - PLoS One, 2020 - journals.plos.org
Due to datasets have continuously grown, efforts have been performed in the attempt to
solve the problem related to the large amount of unlabeled data in disproportion to the …

Learning protein subcellular localization multi-view patterns from heterogeneous data of imaging, sequence and networks

G Wang, MQ Xue, HB Shen, YY Xu - Briefings in Bioinformatics, 2022 - academic.oup.com
Location proteomics seeks to provide automated high-resolution descriptions of protein
location patterns within cells. Many efforts have been undertaken in location proteomics over …

Incorporating label correlations into deep neural networks to classify protein subcellular location patterns in immunohistochemistry images

JX Hu, Y Yang, YY Xu, HB Shen - Proteins: Structure, Function …, 2022 - Wiley Online Library
Abstract Analysis of protein subcellular localization is a critical part of proteomics. In recent
years, as both the number and quality of microscopic images are increasing rapidly, many …

GraphLoc: a graph neural network model for predicting protein subcellular localization from immunohistochemistry images

JX Hu, Y Yang, YY Xu, HB Shen - Bioinformatics, 2022 - academic.oup.com
Motivation Recognition of protein subcellular distribution patterns and identification of
location biomarker proteins in cancer tissues are important for understanding protein …

Segmentation, splitting, and classification of overlapping bacteria in microscope images for automatic bacterial vaginosis diagnosis

Y Song, L He, F Zhou, S Chen, D Ni… - IEEE journal of …, 2016 - ieeexplore.ieee.org
Quantitative analysis of bacterial morphotypes in the microscope images plays a vital role in
diagnosis of bacterial vaginosis (BV) based on the Nugent score criterion. However, there …