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[HTML][HTML] Networks beyond pairwise interactions: Structure and dynamics
The complexity of many biological, social and technological systems stems from the richness
of the interactions among their units. Over the past decades, a variety of complex systems …
of the interactions among their units. Over the past decades, a variety of complex systems …
Superhypergraph neural networks and plithogenic graph neural networks: Theoretical foundations
T Fujita - arxiv preprint arxiv:2412.01176, 2024 - arxiv.org
Hypergraphs extend traditional graphs by allowing edges to connect multiple nodes, while
superhypergraphs further generalize this concept to represent even more complex …
superhypergraphs further generalize this concept to represent even more complex …
Review on predicting pairwise relationships between human microbes, drugs and diseases: from biological data to computational models
L Wang, Y Tan, X Yang, L Kuang… - Briefings in …, 2022 - academic.oup.com
In recent years, with the rapid development of techniques in bioinformatics and life science,
a considerable quantity of biomedical data has been accumulated, based on which …
a considerable quantity of biomedical data has been accumulated, based on which …
Generalized matrix factorization based on weighted hypergraph learning for microbe-drug association prediction
Y Ma, Q Liu - Computers in Biology and Medicine, 2022 - Elsevier
The complex and diverse microbial communities are closely related to human health, and
the research of microbial communities plays an increasingly critical role in drug …
the research of microbial communities plays an increasingly critical role in drug …
Microbes and complex diseases: from experimental results to computational models
Studies have shown that the number of microbes in humans is almost 10 times that of cells.
These microbes have been proven to play an important role in a variety of physiological …
These microbes have been proven to play an important role in a variety of physiological …
Predicting potential microbe-disease associations with graph attention autoencoder, positive-unlabeled learning, and deep neural network
Background Microbes have dense linkages with human diseases. Balanced
microorganisms protect human body against physiological disorders while unbalanced ones …
microorganisms protect human body against physiological disorders while unbalanced ones …
Exploring complex and heterogeneous correlations on hypergraph for the prediction of drug-target interactions
The continuous emergence of drug-target interaction data provides an opportunity to
construct a biological network for systematically discovering unknown interactions. However …
construct a biological network for systematically discovering unknown interactions. However …
A survey on predicting microbe-disease associations: biological data and computational methods
Various microbes have proved to be closely related to the pathogenesis of human diseases.
While many computational methods for predicting human microbe-disease associations …
While many computational methods for predicting human microbe-disease associations …
GMMAD: a comprehensive database of human gut microbial metabolite associations with diseases
CY Wang, X Kuang, QQ Wang, GQ Zhang, ZS Cheng… - BMC genomics, 2023 - Springer
Background The natural products, metabolites, of gut microbes are crucial effect factors on
diseases. Comprehensive identification and annotation of relationships among disease …
diseases. Comprehensive identification and annotation of relationships among disease …
Predicting microbe‐disease association based on heterogeneous network and global graph feature learning
Numerous microbes inhabit human body, making a vast difference in human health. Hence,
discovering associations between microbes and diseases is beneficial to disease …
discovering associations between microbes and diseases is beneficial to disease …