Hansheng Xue
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View article: Personalised Drug Identifier for Cancer Treatment with Transformers using Auxiliary Information
Personalised Drug Identifier for Cancer Treatment with Transformers using Auxiliary Information Open
Cancer remains a global challenge due to its growing clinical and economic burden. Its uniquely personal manifestation, which makes treatment difficult, has fuelled the quest for personalized treatment strategies. Thus, genomic profiling i…
View article: Modeling User Intent Beyond Trigger: Incorporating Uncertainty for Trigger-Induced Recommendation
Modeling User Intent Beyond Trigger: Incorporating Uncertainty for Trigger-Induced Recommendation Open
To cater to users' desire for an immersive browsing experience, numerous e-commerce platforms provide various recommendation scenarios, with a focus on Trigger-Induced Recommendation (TIR) tasks. However, the majority of current TIR method…
View article: Solving genomic puzzles: computational methods for metagenomic binning
Solving genomic puzzles: computational methods for metagenomic binning Open
Metagenomics involves the study of genetic material obtained directly from communities of microorganisms living in natural environments. The field of metagenomics has provided valuable insights into the structure, diversity and ecology of …
View article: Personalised Drug Identifier for Cancer Treatment with Transformers using Auxiliary Information
Personalised Drug Identifier for Cancer Treatment with Transformers using Auxiliary Information Open
Cancer remains a global challenge due to its growing clinical and economic burden. Its uniquely personal manifestation, which makes treatment difficult, has fuelled the quest for personalized treatment strategies. Thus, genomic profiling i…
View article: Graph Coloring via Neural Networks for Haplotype Assembly and Viral Quasispecies Reconstruction
Graph Coloring via Neural Networks for Haplotype Assembly and Viral Quasispecies Reconstruction Open
Understanding genetic variation, e.g., through mutations, in organisms is crucial to unravel their effects on the environment and human health. A fundamental characterization can be obtained by solving the haplotype assembly problem, which…
View article: RepBin: Constraint-Based Graph Representation Learning for Metagenomic Binning
RepBin: Constraint-Based Graph Representation Learning for Metagenomic Binning Open
Mixed communities of organisms are found in many environments -- from the human gut to marine ecosystems -- and can have profound impact on human health and the environment. Metagenomics studies the genomic material of such communities thr…
View article: RepBin: Constraint-based Graph Representation Learning for Metagenomic Binning
RepBin: Constraint-based Graph Representation Learning for Metagenomic Binning Open
Mixed communities of organisms are found in many environments (from the human gut to marine ecosystems) and can have profound impact on human health and the environment. Metagenomics studies the genomic material of such communities through…
View article: Multiplex Bipartite Network Embedding using Dual Hypergraph Convolutional Networks
Multiplex Bipartite Network Embedding using Dual Hypergraph Convolutional Networks Open
A bipartite network is a graph structure where nodes are from two distinct domains and only inter-domain interactions exist as edges. A large number of network embedding methods exist to learn vectorial node representations from general gr…
View article: Multiplex Bipartite Network Embedding using Dual Hypergraph Convolutional Networks
Multiplex Bipartite Network Embedding using Dual Hypergraph Convolutional Networks Open
A bipartite network is a graph structure where nodes are from two distinct domains and only inter-domain interactions exist as edges. A large number of network embedding methods exist to learn vectorial node representations from general gr…
View article: Predicting the Disease Genes of Multiple Sclerosis Based on Network Representation Learning
Predicting the Disease Genes of Multiple Sclerosis Based on Network Representation Learning Open
Multiple sclerosis (MS) is an autoimmune disease for which it is difficult to find exact disease-related genes. Effectively identifying disease-related genes would contribute to improving the treatment and diagnosis of multiple sclerosis. …
View article: Modeling Dynamic Heterogeneous Network for Link Prediction using Hierarchical Attention with Temporal RNN
Modeling Dynamic Heterogeneous Network for Link Prediction using Hierarchical Attention with Temporal RNN Open
Network embedding aims to learn low-dimensional representations of nodes while capturing structure information of networks. It has achieved great success on many tasks of network analysis such as link prediction and node classification. Mo…
View article: TS-GOEA: a web tool for tissue-specific gene set enrichment analysis based on gene ontology
TS-GOEA: a web tool for tissue-specific gene set enrichment analysis based on gene ontology Open
View article: Towards Gene Function Prediction via Multi-Networks Representation Learning
Towards Gene Function Prediction via Multi-Networks Representation Learning Open
Multi-networks integration methods have achieved prominent performance on many network-based tasks, but these approaches often incur information loss problem. In this paper, we propose a novel multi-networks representation learning method …
View article: Predicting disease-related phenotypes using an integrated phenotype similarity measurement based on HPO
Predicting disease-related phenotypes using an integrated phenotype similarity measurement based on HPO Open
View article: Integrating multi-network topology for gene function prediction using deep neural networks
Integrating multi-network topology for gene function prediction using deep neural networks Open
Motivation The emerging of abundant biological networks, which benefit from the development of advanced high-throughput techniques, contribute to describing and modeling complex internal interactions among biological entities such as genes…
View article: Deep Feature Learning of Multi-Network Topology for Node Classification
Deep Feature Learning of Multi-Network Topology for Node Classification Open
Networks are ubiquitous structure that describes complex relationships between different entities in the real world. As a critical component of prediction task over nodes in networks, learning the feature representation of nodes has become…
View article: An online tool for measuring and visualizing phenotype similarities using HPO
An online tool for measuring and visualizing phenotype similarities using HPO Open
View article: Additional file 4 of Predicting disease-related genes using integrated biomedical networks
Additional file 4 of Predicting disease-related genes using integrated biomedical networks Open
Diseases selected as the evaluation set. Additional file 4 is a table of diseases selected as the evaluation set. (PDF 708 kb)
View article: Predicting disease-related genes using integrated biomedical networks
Predicting disease-related genes using integrated biomedical networks Open