☆ 4.5 Article

Implementing link prediction in protein networks via feature fusion models based on graph neural networks

COMPUTATIONAL BIOLOGY AND CHEMISTRY (2024)

相关参考文献

注意：仅列出部分参考文献，下载原文获取全部文献信息。

Article Computer Science, Information Systems

Fusing Higher and Lower-order Biological Information for Drug Repositioning via Graph Representation Learning

Bo-Wei Zhao et al.

IEEE Transactions on Emerging Topics in Computing (2023)

添加到收藏夹

Article Biochemical Research Methods

PPISB: A Novel Network-Based Algorithm of Predicting Protein-Protein Interactions With Mixed Membership Stochastic Blockmodel

Xiaojuan Wang et al.

Summary: This paper proposes an efficient network-based prediction algorithm called PPISB, which uses a mixed membership stochastic blockmodel to capture the latent community structures of proteins in a PPI network. PPISB optimizes the membership distributions of proteins and computes the similarity between proteins to determine their interaction. Experimental results show that PPISB performs well in predicting PPIs based on various evaluation metrics.

IEEE-ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS (2023)

添加到收藏夹

Article Biochemical Research Methods

Efficient link prediction in the protein-protein interaction network using topological information in a generative adversarial network machine learning model

Oliver M. Balogh et al.

Summary: The authors developed a software tool for link prediction in protein-protein interaction networks using machine learning. They utilized a modified breadth-first search algorithm for data processing and a conditional generative adversarial network model with Wasserstein distance-based loss improved with gradient penalty to predict potential unknown edge connections.

BMC BIOINFORMATICS (2022)

添加到收藏夹

Article Engineering, Multidisciplinary

Perturbation of the Normalized Laplacian Matrix for the Prediction of Missing Links in Real Networks

Roya Aliakbarisani et al.

Summary: This paper presents a link prediction method called Laplacian Perturbation Method (LPM) based on perturbation theory, which significantly improves prediction accuracy and outperforms other methods.

IEEE TRANSACTIONS ON NETWORK SCIENCE AND ENGINEERING (2022)

添加到收藏夹

Article Physics, Multidisciplinary

Deep Link-Prediction Based on the Local Structure of Bipartite Networks

Hehe Lv et al.

Summary: This paper proposes a deep link-prediction (DLP) method based on the local structure of bipartite networks. The method extracts and learns the representation of the local structure using a graph neural network, achieving significant improvement in link prediction. The effectiveness of the local structure in link prediction is confirmed through experimental analysis.

ENTROPY (2022)

添加到收藏夹

Article Biochemical Research Methods

Incorporating higher order network structures to improve miRNA-disease association prediction based on functional modularity

Yizhou He et al.

Summary: The study introduces a novel prediction model called HiSCMDA, which incorporates higher order network structures to improve the prediction performance of miRNA-disease associations. Experimental results demonstrate that HiSCMDA achieves the best performance across all datasets and evaluation metrics.

BRIEFINGS IN BIOINFORMATICS (2022)

添加到收藏夹

Article Biology

A novel link prediction algorithm for protein-protein interaction networks by attributed graph embedding

Elahe Nasiri et al.

Summary: Predicting interactions in protein networks is crucial for biological processes, and computational methods have been used, including the popular Deepwalk algorithm, to predict protein interactions. This study focuses on link prediction in attributed networks by modifying Deepwalk with feature selection for more accurate prediction of protein-protein interactions. Results show that this approach outperforms other methods and improves prediction accuracy.

COMPUTERS IN BIOLOGY AND MEDICINE (2021)

添加到收藏夹

Article Biochemical Research Methods

A Deep Learning Framework for Gene Ontology Annotations With Sequence- and Network-Based Information

Fuhao Zhang et al.

Summary: Understanding protein functions is crucial in biology and medicine, but many proteins lack functional annotations. DeepGOA utilizes protein sequences and PPI networks to predict protein functions, combining word embeddings, deep learning, and neural network algorithms. Experimental results demonstrate its superior performance compared to other methods.

IEEE-ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS (2021)

添加到收藏夹

Article Computer Science, Artificial Intelligence

Hierarchical Attention Link Prediction Neural Network

Zhitao Wang et al.

Summary: The proposed HalpNet model utilizes a hierarchical attention mechanism to comprehensively explore neighborhood information and achieve effective link prediction, demonstrating significant superiority over existing approaches on various benchmark datasets.

KNOWLEDGE-BASED SYSTEMS (2021)

添加到收藏夹

Article Computer Science, Artificial Intelligence

Nonnegative matrix factorization for link prediction in directed complex networks using PageRank and asymmetric link clustering information

Guangfu Chen et al.

EXPERT SYSTEMS WITH APPLICATIONS (2020)

添加到收藏夹

Article Multidisciplinary Sciences

Graph embedding-based novel protein interaction prediction via higher-order graph convolutional network

Ze Xiao et al.

PLOS ONE (2020)

添加到收藏夹

Article Multidisciplinary Sciences

SkipGNN: predicting molecular interactions with skip-graph networks

Kexin Huang et al.

SCIENTIFIC REPORTS (2020)

添加到收藏夹

Article Mathematics, Interdisciplinary Applications

GLEE: Geometric Laplacian Eigenmap Embedding

Leo Torres et al.

JOURNAL OF COMPLEX NETWORKS (2020)

添加到收藏夹

Article Computer Science, Artificial Intelligence

An Ensemble Approach to Link Prediction

Liang Duan et al.

IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING (2017)

添加到收藏夹

Article Computer Science, Information Systems

Link prediction in multi-relational networks based on relational similarity

Caiyan Dai et al.

INFORMATION SCIENCES (2017)

添加到收藏夹

Article Biochemical Research Methods

Toward a comprehensive atlas of the physical interactome of Saccharomyces cerevisiae

Sean R. Collins et al.

MOLECULAR & CELLULAR PROTEOMICS (2007)

添加到收藏夹

Article Multidisciplinary Sciences

Global landscape of protein complexes in the yeast Saccharomyces cerevisiae

NJ Krogan et al.

NATURE (2006)

添加到收藏夹

© Peeref 2019-2024. All rights reserved.