ARWAR: a network approach for predicting adverse drug reactions
Predicting novel drug side-effects, or Adverse Drug Reactions (ADRs), plays an important
role in the drug discovery process. Existing methods consider mainly the chemical and …
role in the drug discovery process. Existing methods consider mainly the chemical and …
EMDIP: an entropy measure to discover important proteins in PPI networks
Discovering important proteins in Protein–Protein Interaction (PPI) networks has attracted a
lot of attention in recent years. Most of the previous work applies different network centrality …
lot of attention in recent years. Most of the previous work applies different network centrality …
An integrated network of Arabidopsis growth regulators and its use for gene prioritization
Elucidating the molecular mechanisms that govern plant growth has been an important topic
in plant research and current advances in large-scale data generation call for computational …
in plant research and current advances in large-scale data generation call for computational …
Predicting genes involved in human cancer using network contextual information
Summary Protein-Protein Interaction (PPI) networks have been widely used for the task of
predicting proteins involved in cancer. Previous research has shown that functional …
predicting proteins involved in cancer. Previous research has shown that functional …
[PDF][PDF] Interaction-based feature selection for predicting cancer-related proteins in protein-protein interaction networks
The task of predicting in a protein-protein-interaction (PPI) network which proteins are
involved in certain diseases, such as cancer, has received a significant amount of attention …
involved in certain diseases, such as cancer, has received a significant amount of attention …
[PDF][PDF] An Introduction to Graph Mining
H Rahmani - 2011 - liacs.leidenuniv.nl
Definition: Node i is important if the shortest-path distance of some node v to node i is likely
to be relevant for v's classification Feature fi denotes the shortest-path distance to node i …
to be relevant for v's classification Feature fi denotes the shortest-path distance to node i …