Graph representation learning in bioinformatics: trends, methods and applications

Leveraging graph-based hierarchical medical entity embedding for healthcare applications

(2021) Tong Wu et al.   Scientific Reports

Multi-view Multichannel Attention Graph Convolutional Network for miRNA–disease association prediction

(2021) Xinru Tang et al.   BRIEFINGS IN BIOINFORMATICS

Identification of disease treatment mechanisms through the multiscale interactome

(2021) Camilo Ruiz et al.   Nature Communications

Masked graph modeling for molecule generation

(2021) Omar Mahmood et al.   Nature Communications

Multiview Consensus Graph Learning for lncRNA–Disease Association Prediction

(2020) Haojiang Tan et al.   Frontiers in Genetics

A graph regularized generalized matrix factorization model for predicting links in biomedical bipartite networks

(2020) Zi-Chao Zhang et al.   BIOINFORMATICS

Identifying drug–target interactions based on graph convolutional network and deep neural network

(2020) Tianyi Zhao et al.   BRIEFINGS IN BIOINFORMATICS

Attentional multi-level representation encoding based on convolutional and variance autoencoders for lncRNA–disease association prediction

(2020) Nan Sheng et al.   BRIEFINGS IN BIOINFORMATICS

AGCN: Attention-based Graph Convolutional Networks for Drug-Drug Interaction Extraction

(2020) Chanhee Park et al.   EXPERT SYSTEMS WITH APPLICATIONS

GCNCDA: A new method for predicting circRNA-disease associations based on Graph Convolutional Network Algorithm

(2020) Lei Wang et al.   PLoS Computational Biology

Deep multiplex graph infomax: Attentive multiplex network embedding using global information

(2020) Chanyoung Park et al.   KNOWLEDGE-BASED SYSTEMS

Variational graph auto-encoders for miRNA-disease association prediction

(2020) Yulian Ding et al.   METHODS

Denoising Protein–Protein interaction network via variational graph auto-encoder for protein complex detection

(2020) Heng Yao et al.   Journal of Bioinformatics and Computational Biology

Graph2GO: a multi-modal attributed network embedding method for inferring protein functions

(2020) Kunjie Fan et al.   GigaScience

Learning Representations to Predict Intermolecular Interactions on Large-Scale Heterogeneous Molecular Association Network

(2020) Hai-Cheng Yi et al.   iScience

Generative adversarial networks

(2020) Ian Goodfellow et al.   COMMUNICATIONS OF THE ACM

A Comprehensive Survey on Graph Neural Networks

(2020) Zonghan Wu et al.   IEEE Transactions on Neural Networks and Learning Systems

An end-to-end heterogeneous graph representation learning-based framework for drug–target interaction prediction

(2020) Jiajie Peng et al.   BRIEFINGS IN BIOINFORMATICS

Disease Prediction via Graph Neural Networks

(2020) Zhenchao Sun et al.   IEEE Journal of Biomedical and Health Informatics

Deep Learning on Graphs: A Survey

(2020) Ziwei Zhang et al.   IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING

Learning Representation of Molecules in Association Network for Predicting Intermolecular Associations

(2020) Hai-Cheng Yi et al.   IEEE-ACM Transactions on Computational Biology and Bioinformatics

To Embed or Not: Network Embedding as a Paradigm in Computational Biology

(2019) Walter Nelson et al.   Frontiers in Genetics

Molecule Property Prediction Based on Spatial Graph Embedding

(2019) Xiaofeng Wang et al.   Journal of Chemical Information and Modeling

AHNG: Representation learning on attributed heterogeneous network

(2019) Mengyue Liu et al.   Information Fusion

Neural inductive matrix completion with graph convolutional networks for miRNA-disease association prediction

(2019) Jin Li et al.   BIOINFORMATICS

Evaluation of knowledge graph embedding approaches for drug-drug interaction prediction in realistic settings

(2019) Remzi Celebi et al.   BMC BIOINFORMATICS

Drug–target prediction utilizing heterogeneous bio-linked network embeddings

(2019) Nansu Zong et al.   BRIEFINGS IN BIOINFORMATICS

Deciphering interaction fingerprints from protein molecular surfaces using geometric deep learning

(2019) P. Gainza et al.   NATURE METHODS

Learning Graph Embedding With Adversarial Training Methods

(2019) Shirui Pan et al.   IEEE Transactions on Cybernetics

Predicting drug-disease associations by using similarity constrained matrix factorization

(2018) Wen Zhang et al.   BMC BIOINFORMATICS

A Comprehensive Survey of Graph Embedding: Problems, Techniques and Applications

(2018) HongYun Cai et al.   IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING

A Survey on Network Embedding

(2018) Peng Cui et al.   IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING

Attributed Social Network Embedding

(2018) Lizi Liao et al.   IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING

Heterogeneous Information Network Embedding for Recommendation

(2018) Chuan Shi et al.   IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING

Graph embedding techniques, applications, and performance: A survey

(2018) Palash Goyal et al.   KNOWLEDGE-BASED SYSTEMS

Protein function prediction as a graph-transduction game

(2018) Sebastiano Vascon et al.   PATTERN RECOGNITION LETTERS

Bipartite graphs in systems biology and medicine: a survey of methods and applications

(2018) Georgios A Pavlopoulos et al.   GigaScience

Predicting adverse drug reactions of combined medication from heterogeneous pharmacologic databases

(2018) Yi Zheng et al.   BMC BIOINFORMATICS

Knowledge Graph Embedding: A Survey of Approaches and Applications

(2017) Quan Wang et al.   IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING

Inferring MicroRNA-Disease Associations by Random Walk on a Heterogeneous Network with Multiple Data Sources

(2017) Yuansheng Liu et al.   IEEE-ACM Transactions on Computational Biology and Bioinformatics

Network embedding-based representation learning for single cell RNA-seq data

(2017) Xiangyu Li et al.   NUCLEIC ACIDS RESEARCH

Learning a Health Knowledge Graph from Electronic Medical Records

(2017) Maya Rotmensch et al.   Scientific Reports

Deep learning for computational biology

(2016) Christof Angermueller et al.   Molecular Systems Biology

Machine Learning in Genomic Medicine: A Review of Computational Problems and Data Sets

(2016) Michael K. K. Leung et al.   PROCEEDINGS OF THE IEEE

A Review of Relational Machine Learning for Knowledge Graphs

(2016) Maximilian Nickel et al.   PROCEEDINGS OF THE IEEE

Disease Ontology 2015 update: an expanded and updated database of human diseases for linking biomedical knowledge through disease data

(2014) Warren A. Kibbe et al.   NUCLEIC ACIDS RESEARCH

Disease gene identification by random walk on multigraphs merging heterogeneous genomic and phenotype data

(2012) Yongjin Li et al.   BMC GENOMICS

Drug repositioning through incomplete bi-cliques in an integrated drug–target–disease network

(2012) Simone Daminelli et al.   Integrative Biology

Prediction of Drug-Target Interactions and Drug Repositioning via Network-Based Inference

(2012) Feixiong Cheng et al.   PLoS Computational Biology

A ceRNA Hypothesis: The Rosetta Stone of a Hidden RNA Language?

(2011) Leonardo Salmena et al.   CELL

Using manifold embedding for assessing and predicting protein interactions from high-throughput experimental data

(2010) Z.-H. You et al.   BIOINFORMATICS

Network medicine: a network-based approach to human disease

(2010) Albert-László Barabási et al.   NATURE REVIEWS GENETICS

Molecular networks as sensors and drivers of common human diseases

(2009) Eric E. Schadt   NATURE

Network visualization and analysis of gene expression data using BioLayout Express3D

(2009) Athanasios Theocharidis et al.   Nature Protocols

The Graph Neural Network Model

(2008) F. Scarselli et al.   IEEE TRANSACTIONS ON NEURAL NETWORKS

An empirical framework for binary interactome mapping

(2008) Kavitha Venkatesan et al.   NATURE METHODS

Comparative Toxicogenomics Database: a knowledgebase and discovery tool for chemical-gene-disease networks

(2008) A. P. Davis et al.   NUCLEIC ACIDS RESEARCH