[HTML][HTML] Review of drug repositioning approaches and resources
Drug discovery is a time-consuming, high-investment, and high-risk process in traditional
drug development. Drug repositioning has become a popular strategy in recent years …
drug development. Drug repositioning has become a popular strategy in recent years …
Exploring the new horizons of drug repurposing: A vital tool for turning hard work into smart work
Drug discovery and development are long and financially taxing processes. On an average
it takes 12–15 years and costs 1.2 billion USD for successful drug discovery and approval …
it takes 12–15 years and costs 1.2 billion USD for successful drug discovery and approval …
Deep mining heterogeneous networks of biomedical linked data to predict novel drug–target associations
Motivation A heterogeneous network topology possessing abundant interactions between
biomedical entities has yet to be utilized in similarity-based methods for predicting drug …
biomedical entities has yet to be utilized in similarity-based methods for predicting drug …
Comparing methods for drug–gene interaction prediction on the biomedical literature knowledge graph: performance versus explainability
F Aisopos, G Paliouras - BMC bioinformatics, 2023 - Springer
This paper applies different link prediction methods on a knowledge graph generated from
biomedical literature, with the aim to compare their ability to identify unknown drug-gene …
biomedical literature, with the aim to compare their ability to identify unknown drug-gene …
Extracting microRNA-gene relations from biomedical literature using distant supervision
Many biomedical relation extraction approaches are based on supervised machine learning,
requiring an annotated corpus. Distant supervision aims at training a classifier by combining …
requiring an annotated corpus. Distant supervision aims at training a classifier by combining …
Large-scale prediction of drug-target interaction: a data-centric review
The prediction of drug-target interactions (DTIs) is of extraordinary significance to modern
drug discovery in terms of suggesting new drug candidates and repositioning old drugs …
drug discovery in terms of suggesting new drug candidates and repositioning old drugs …
The role of drug profiles as similarity metrics: applications to repurposing, adverse effects detection and drug–drug interactions
S Vilar, G Hripcsak - Briefings in Bioinformatics, 2017 - academic.oup.com
Explosion of the availability of big data sources along with the development in computational
methods provides a useful framework to study drugs' actions, such as interactions with …
methods provides a useful framework to study drugs' actions, such as interactions with …
Transforming heterogeneous data into knowledge for personalized treatments—a use case
Big data has exponentially grown in the last decade; it is expected to grow at a faster rate in
the next years as a result of the advances in the technologies for data generation and …
the next years as a result of the advances in the technologies for data generation and …
MULDER: querying the linked data web by bridging RDF molecule templates
The increasing number of RDF data sources that allow for querying Linked Data via Web
services form the basis for federated SPARQL query processing. Federated SPARQL query …
services form the basis for federated SPARQL query processing. Federated SPARQL query …
Knowledge graph enhanced community detection and characterization
Recent studies show that by combining network topology and node attributes, we can better
understand community structures in complex networks. However, existing algorithms do not …
understand community structures in complex networks. However, existing algorithms do not …