Artificial intelligence to deep learning: machine intelligence approach for drug discovery

R Gupta, D Srivastava, M Sahu, S Tiwari, RK Ambasta… - Molecular …, 2021 - Springer
Drug designing and development is an important area of research for pharmaceutical
companies and chemical scientists. However, low efficacy, off-target delivery, time …

[HTML][HTML] Review of drug repositioning approaches and resources

H Xue, J Li, H Xie, Y Wang - International journal of biological …, 2018 - ncbi.nlm.nih.gov
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 …

Building a knowledge graph to enable precision medicine

P Chandak, K Huang, M Zitnik - Scientific Data, 2023 - nature.com
Developing personalized diagnostic strategies and targeted treatments requires a deep
understanding of disease biology and the ability to dissect the relationship between …

Machine learning for synergistic network pharmacology: a comprehensive overview

F Noor, M Asif, UA Ashfaq, M Qasim… - Briefings in …, 2023 - academic.oup.com
Network pharmacology is an emerging area of systematic drug research that attempts to
understand drug actions and interactions with multiple targets. Network pharmacology has …

A review on drug repurposing applicable to COVID-19

S Dotolo, A Marabotti, A Facchiano… - Briefings in …, 2021 - academic.oup.com
Drug repurposing involves the identification of new applications for existing drugs at a lower
cost and in a shorter time. There are different computational drug-repurposing strategies and …

Drug repositioning based on comprehensive similarity measures and bi-random walk algorithm

H Luo, J Wang, M Li, J Luo, X Peng, FX Wu… - …, 2016 - academic.oup.com
Motivation: Drug repositioning, which aims to identify new indications for existing drugs,
offers a promising alternative to reduce the total time and cost of traditional drug …

Detection-based prioritisation: Framework of multi-laboratory characteristics for asymptomatic COVID-19 carriers based on integrated Entropy–TOPSIS methods

AS Albahri, RA Hamid, OS Albahri… - Artificial intelligence in …, 2021 - Elsevier
Context and background Corona virus (COVID) has rapidly gained a foothold and caused a
global pandemic. Particularists try their best to tackle this global crisis. New challenges …

Predicting drug-disease associations by using similarity constrained matrix factorization

W Zhang, X Yue, W Lin, W Wu, R Liu, F Huang, F Liu - BMC bioinformatics, 2018 - Springer
Background Drug-disease associations provide important information for the drug discovery.
Wet experiments that identify drug-disease associations are time-consuming and expensive …

Biomedical data and computational models for drug repositioning: a comprehensive review

H Luo, M Li, M Yang, FX Wu, Y Li… - Briefings in …, 2021 - academic.oup.com
Drug repositioning can drastically decrease the cost and duration taken by traditional drug
research and development while avoiding the occurrence of unforeseen adverse events …

In silico methods for drug repurposing and pharmacology

RA Hodos, BA Kidd, K Shameer… - … Systems Biology and …, 2016 - Wiley Online Library
Data in the biological, chemical, and clinical domains are accumulating at ever‐increasing
rates and have the potential to accelerate and inform drug development in new ways …