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 …

Identify RNA-associated subcellular localizations based on multi-label learning using Chou's 5-steps rule

H Wang, Y Ding, J Tang, Q Zou, F Guo - BMC genomics, 2021 - Springer
Background Biological functions of biomolecules rely on the cellular compartments where
they are located in cells. Importantly, RNAs are assigned in specific locations of a cell …

Multi-scale deep learning for the imbalanced multi-label protein subcellular localization prediction based on immunohistochemistry images

F Wang, L Wei - Bioinformatics, 2022 - academic.oup.com
Motivation The development of microscopic imaging techniques enables us to study protein
subcellular locations from the tissue level down to the cell level, contributing to the rapid …

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 …

Protein subcellular localization based on deep image features and criterion learning strategy

R Su, L He, T Liu, X Liu, L Wei - Briefings in Bioinformatics, 2021 - academic.oup.com
The spatial distribution of proteome at subcellular levels provides clues for protein functions,
thus is important to human biology and medicine. Imaging-based methods are one of the …

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 …

[图书][B] Dealing with imbalanced and weakly labelled data in machine learning using fuzzy and rough set methods

S Vluymans - 2019 - Springer
This book is based on my Ph. D. dissertation completed at Ghent University (Belgium) and
the University of Granada (Spain) in June 2018. It focuses on classification. The goal is to …

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 …