Artificial intelligence in cancer target identification and drug discovery

Y You, X Lai, Y Pan, H Zheng, J Vera, S Liu… - … and Targeted Therapy, 2022 - nature.com
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 …

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 …

A learning-based method for drug-target interaction prediction based on feature representation learning and deep neural network

J Peng, J Li, X Shang - BMC bioinformatics, 2020 - Springer
Background Drug-target interaction prediction is of great significance for narrowing down the
scope of candidate medications, and thus is a vital step in drug discovery. Because of the …

Drug repurposing for Alzheimer's disease from 2012–2022—A 10-year literature review

ME Grabowska, A Huang, Z Wen, B Li… - Frontiers in …, 2023 - frontiersin.org
Background: Alzheimer's disease (AD) is a debilitating neurodegenerative condition with
few treatment options available. Drug repurposing studies have sought to identify existing …

Therapeutic drug repositioning with special emphasis on neurodegenerative diseases: Threats and issues

BB Kakoti, R Bezbaruah, N Ahmed - Frontiers in Pharmacology, 2022 - frontiersin.org
Drug repositioning or repurposing is the process of discovering leading-edge indications for
authorized or declined/abandoned molecules for use in different diseases. This approach …

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 …

SemaTyP: a knowledge graph based literature mining method for drug discovery

S Sang, Z Yang, L Wang, X Liu, H Lin, J Wang - BMC bioinformatics, 2018 - Springer
Background Drug discovery is the process through which potential new medicines are
identified. High-throughput screening and computer-aided drug discovery/design are the …

A paradigm shift in medicine: A comprehensive review of network-based approaches

F Conte, G Fiscon, V Licursi, D Bizzarri, T D'Antò… - … et Biophysica Acta (BBA …, 2020 - Elsevier
Network medicine is a rapidly evolving new field of medical research, which combines
principles and approaches of systems biology and network science, holding the promise to …

Drug repositioning through integration of prior knowledge and projections of drugs and diseases

P Xuan, Y Cao, T Zhang, X Wang, S Pan… - Bioinformatics, 2019 - academic.oup.com
Motivation Identifying and develo** novel therapeutic effects for existing drugs contributes
to reduction of drug development costs. Most of the previous methods focus on integration of …

Graph convolutional autoencoder and fully-connected autoencoder with attention mechanism based method for predicting drug-disease associations

P Xuan, L Gao, N Sheng, T Zhang… - IEEE Journal of …, 2020 - ieeexplore.ieee.org
Predicting novel uses for approved drugs helps in reducing the costs of drug development
and facilitates the development process. Most of previous methods focused on the multi …