Artificial intelligence in cancer target identification and drug discovery
Artificial intelligence is an advanced method to identify novel anticancer targets and discover
novel drugs from biology networks because the networks can effectively preserve and …
novel drugs from biology networks because the networks can effectively preserve and …
A survey on hypergraph representation learning
Hypergraphs have attracted increasing attention in recent years thanks to their flexibility in
naturally modeling a broad range of systems where high-order relationships exist among …
naturally modeling a broad range of systems where high-order relationships exist among …
A novel approach to large-scale dynamically weighted directed network representation
A d ynamically w eighted d irected n etwork (DWDN) is frequently encountered in various big
data-related applications like a terminal interaction pattern analysis system (TIPAS) …
data-related applications like a terminal interaction pattern analysis system (TIPAS) …
Link prediction techniques, applications, and performance: A survey
Link prediction finds missing links (in static networks) or predicts the likelihood of future links
(in dynamic networks). The latter definition is useful in network evolution (Wang et al., 2011; …
(in dynamic networks). The latter definition is useful in network evolution (Wang et al., 2011; …
Network representation learning: A survey
With the widespread use of information technologies, information networks are becoming
increasingly popular to capture complex relationships across various disciplines, such as …
increasingly popular to capture complex relationships across various disciplines, such as …
Foundations and modeling of dynamic networks using dynamic graph neural networks: A survey
Dynamic networks are used in a wide range of fields, including social network analysis,
recommender systems and epidemiology. Representing complex networks as structures …
recommender systems and epidemiology. Representing complex networks as structures …
Updated review of advances in microRNAs and complex diseases: taxonomy, trends and challenges of computational models
Since the problem proposed in late 2000s, microRNA–disease association (MDA)
predictions have been implemented based on the data fusion paradigm. Integrating diverse …
predictions have been implemented based on the data fusion paradigm. Integrating diverse …
Path extension similarity link prediction method based on matrix algebra in directed networks
F Guo, W Zhou, Q Lu, C Zhang - Computer Communications, 2022 - Elsevier
Traditional link prediction methods are generally only calculated for the neighbor information
of nodes, and the network path between nodes has not been fully utilized. Therefore, this …
of nodes, and the network path between nodes has not been fully utilized. Therefore, this …
A novel link prediction algorithm for protein-protein interaction networks by attributed graph embedding
The prediction of interactions in protein networks is very critical in various biological
processes. In recent years, scientists have focused on computational approaches to predict …
processes. In recent years, scientists have focused on computational approaches to predict …
Applications of link prediction in social networks: A review
Link prediction methods anticipate the likelihood of a future connection between two nodes
in a given network. The methods are essential in social networks to infer social interactions …
in a given network. The methods are essential in social networks to infer social interactions …