[HTML][HTML] Building a knowledge graph to enable precision medicine
Developing personalized diagnostic strategies and targeted treatments requires a deep
understanding of disease biology and the ability to dissect the relationship between …
understanding of disease biology and the ability to dissect the relationship between …
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 …
[HTML][HTML] Drug-disease association prediction using heterogeneous networks for computational drug repositioning
Y Kim, YS Jung, JH Park, SJ Kim, YR Cho - Biomolecules, 2022 - mdpi.com
Drug repositioning, which involves the identification of new therapeutic indications for
approved drugs, considerably reduces the time and cost of developing new drugs. Recent …
approved drugs, considerably reduces the time and cost of developing new drugs. Recent …
DeepLncLoc: a deep learning framework for long non-coding RNA subcellular localization prediction based on subsequence embedding
Long non-coding RNAs (lncRNAs) are a class of RNA molecules with more than 200
nucleotides. A growing amount of evidence reveals that subcellular localization of lncRNAs …
nucleotides. A growing amount of evidence reveals that subcellular localization of lncRNAs …
[HTML][HTML] Drug repositioning with GraphSAGE and clustering constraints based on drug and disease networks
The understanding of therapeutic properties is important in drug repositioning and drug
discovery. However, chemical or clinical trials are expensive and inefficient to characterize …
discovery. However, chemical or clinical trials are expensive and inefficient to characterize …
[HTML][HTML] An explainable framework for drug repositioning from disease information network
Exploring efficient and high-accuracy computational drug repositioning methods has
become a popular and attractive topic in drug development. This technology can …
become a popular and attractive topic in drug development. This technology can …
[HTML][HTML] DTI-HeNE: a novel method for drug-target interaction prediction based on heterogeneous network embedding
Y Yue, S He - BMC bioinformatics, 2021 - Springer
Background Prediction of the drug-target interaction (DTI) is a critical step in the drug
repurposing process, which can effectively reduce the following workload for experimental …
repurposing process, which can effectively reduce the following workload for experimental …
Review of natural language processing in pharmacology
D Trajanov, V Trajkovski, M Dimitrieva, J Dobreva… - Pharmacological …, 2023 - ASPET
Natural language processing (NLP) is an area of artificial intelligence that applies
information technologies to process the human language, understand it to a certain degree …
information technologies to process the human language, understand it to a certain degree …
[HTML][HTML] Gene based message passing for drug repurposing
The medicinal effect of a drug acts through a series of genes, and the pathological
mechanism of a disease is also related to genes with certain biological functions. However …
mechanism of a disease is also related to genes with certain biological functions. However …
Netpro2vec: a graph embedding framework for biomedical applications
The ever-increasing importance of structured data in different applications, especially in the
biomedical field, has driven the need for reducing its complexity through projections into a …
biomedical field, has driven the need for reducing its complexity through projections into a …