Spatiotemporal constrained RNA–protein heterogeneous network for protein complex identification
Z Li, S Wang, H Cui, X Liu, Y Zhang - Briefings in Bioinformatics, 2024 - academic.oup.com
The identification of protein complexes from protein interaction networks is crucial in the
understanding of protein function, cellular processes and disease mechanisms. Existing …
understanding of protein function, cellular processes and disease mechanisms. Existing …
Temporal Protein Complex Identification Based on Dynamic Heterogeneous Protein Information Network Representation Learning
Z Li, Y Zhang, P Zhou - IEEE/ACM Transactions on …, 2024 - ieeexplore.ieee.org
Protein complexes, as the fundamental units of cellular function and regulation, play a
crucial role in understanding the normal physiological functions of cells. Existing methods for …
crucial role in understanding the normal physiological functions of cells. Existing methods for …
Heterogeneous PPI network representation learning for protein complex identification
Protein complexes are critical units for studying a cell system. How to accurately identify
protein complexes has always been the focus of research. Most of the existing methods are …
protein complexes has always been the focus of research. Most of the existing methods are …
Protein Complex Identification Based on Heterogeneous Protein Information Network
Protein complexes are the foundation of all cellular activities, and accurately identifying them
is crucial for studying cellular systems. The efficient discovery of protein complexes is a …
is crucial for studying cellular systems. The efficient discovery of protein complexes is a …
PCGAN: a generative approach for protein complex identification from protein interaction networks
Motivation Protein complexes are groups of polypeptide chains linked by non-covalent
protein–protein interactions, which play important roles in biological systems and perform …
protein–protein interactions, which play important roles in biological systems and perform …
[HTML][HTML] An ensemble learning framework for detecting protein complexes from PPI networks
R Wang, H Ma, C Wang - Frontiers in Genetics, 2022 - frontiersin.org
Detecting protein complexes is one of the keys to understanding cellular organization and
processes principles. With high-throughput experiments and computing science …
processes principles. With high-throughput experiments and computing science …
COMNA: Core-attachment based protein complex detection via multiple network alignment
Y Chen, Y Zhu, M Zhong, J Liu - 2021 IEEE International …, 2021 - ieeexplore.ieee.org
Protein complexes are important functional units for performing biological functions and
revealing cellular organization principles, and its detection is a fundamental problem in …
revealing cellular organization principles, and its detection is a fundamental problem in …
DPCMNE: detecting protein complexes from protein-protein interaction networks via multi-level network embedding
Biological functions of a cell are typically carried out through protein complexes. The
detection of protein complexes is therefore of great significance for understanding the …
detection of protein complexes is therefore of great significance for understanding the …
[HTML][HTML] Identifying protein complexes with clear module structure using pairwise constraints in protein interaction networks
The protein-protein interaction (PPI) networks can be regarded as powerful platforms to
elucidate the principle and mechanism of cellular organization. Uncovering protein …
elucidate the principle and mechanism of cellular organization. Uncovering protein …
Constructing a PPI Network Based on Deep Transfer Learning for Protein Complex Detection
X Yuan, H Deng, J Hu - IEEJ Transactions on Electrical and …, 2022 - Wiley Online Library
In the detection of protein complexes, the completeness of a protein–protein interaction (PPI)
network is crucial. Complete PPI networks, however, are not available for most species …
network is crucial. Complete PPI networks, however, are not available for most species …