English
Related papers

Related papers: Computational Approaches for Predicting Drug-Disea…

200 papers

Repurposing existing drugs to treat new diseases is a cost-effective alternative to de novo drug development, but there are millions of potential drug-disease combinations to be considered with only a small fraction being viable. In silico…

Quantitative Methods · Quantitative Biology 2025-10-24 Austin Polanco , M. E. J. Newman

Drug repositioning (DR) refers to identification of novel indications for the approved drugs. The requirement of huge investment of time as well as money and risk of failure in clinical trials have led to surge in interest in drug…

Computation and Language · Computer Science 2017-05-23 Sahil Manchanda , Ashish Anand

Drug promiscuity and polypharmacology are much discussed topics in pharmaceutical research. Drug repositioning applies established drugs to new disease indications with increasing success. As polypharmacology, defined a drug's ability to…

Distributed, Parallel, and Cluster Computing · Computer Science 2019-05-16 Antonios Makris

Drug development is a very costly and lengthy process, while repositioned or repurposed drugs could be brought into clinical practice within a shorter time-frame and at a much reduced cost. The past decade has observed a massive growth in…

Genomics · Quantitative Biology 2019-11-14 Alexandria Lau , Hon-Cheong So

Computational methods in drug repositioning can help to conserve resources. In particular, methods based on biological networks are showing promise. Considering only the network topology and knowledge on drug target genes is not sufficient…

Molecular Networks · Quantitative Biology 2025-04-02 Atte Aalto , La Mi , Diego A. Blanco-Mora , Jorge Goncalves

Development of new medications is a very lengthy and costly process. Finding novel indications for existing drugs, or drug repositioning, can serve as a useful strategy to shorten the development cycle. In this study, we present an approach…

Genomics · Quantitative Biology 2017-12-13 Kai Zhao , Hon-Cheong So

The COVID-19 crisis called for rapid reaction from all the fields of biomedical research. Traditional drug development involves time consuming pipelines that conflict with the urgence of identifying effective therapies during a health and…

Genomics · Quantitative Biology 2020-05-06 Francesco Napolitano , Gennaro Gambardella , Diego Carrella , Xin Gao , Diego di Bernardo

Background: Identifying new indications for approved drugs is a complex and time-consuming process that requires extensive knowledge of pharmacology, clinical data, and advanced computational methods. Recently, deep learning (DL) methods…

Machine Learning · Computer Science 2025-11-13 Shuting Jin , Yi Jiang , Yimin Liu , Tengfei Ma , Dongsheng Cao , Leyi Wei , Xiangrong Liu , Xiangxiang Zeng

Drug development is an expensive and time-consuming process where thousands of chemical compounds are being tested in order to find those possessing drug-like properties while being safe and effective. One of key parts of the early drug…

Quantitative Methods · Quantitative Biology 2022-02-15 Josip Mesarić

A pharmacological effect of a drug on cells, organs and systems refers to the specific biochemical interaction produced by a drug substance, which is called its mechanism of action. Drug repositioning (or drug repurposing) is a fundamental…

Machine Learning · Computer Science 2020-05-19 Dehua Chen , Amir Jalilifard , Adriano Veloso , Nivio Ziviani

Complex or co-existing diseases are commonly treated using drug combinations, which can lead to higher risk of adverse side effects. The detection of polypharmacy side effects is usually done in Phase IV clinical trials, but there are still…

Machine Learning · Statistics 2019-05-03 Andreea Deac , Yu-Hsiang Huang , Petar Veličković , Pietro Liò , Jian Tang

The extraction of biomedical data has significant academic and practical value in contemporary biomedical sciences. In recent years, drug repositioning, a cost-effective strategy for drug development by discovering new indications for…

Machine Learning · Computer Science 2025-01-20 Enqiang Zhu , Xiang Li , Chanjuan Liu , Nikhil R. Pal

Computational drug repositioning technology is an effective tool to accelerate drug development. Although this technique has been widely used and successful in recent decades, many existing models still suffer from multiple drawbacks such…

Machine Learning · Computer Science 2022-06-01 Xinxing Yang , Genke Yang , Jian Chu

Drug repurposing has attracted increasing attention from both the pharmaceutical industry and the research community. Many existing computational drug repurposing methods rely on preclinical data (e.g., chemical structures, drug targets),…

Quantitative Methods · Quantitative Biology 2020-07-28 Qianlong Wen , Ruoqi Liu , Ping Zhang

Drug discovery remains a slow and expensive process that involves many steps, from detecting the target structure to obtaining approval from the Food and Drug Administration (FDA), and is often riddled with safety concerns. Accurate…

Quantitative Methods · Quantitative Biology 2025-08-22 Ali Vefghi , Zahed Rahmati , Mohammad Akbari

Recently, a number of drug-therapy, disease, drug, and drug-target networks have been introduced. Here we suggest novel methods for network-based prediction of novel drug targets and for improvement of drug efficiency by analysing the…

Molecular Networks · Quantitative Biology 2008-07-31 Zoltan Spiro , Istvan A. Kovacs , Peter Csermely

Drug repositioning, that is finding new uses for existing drugs to treat more patients. Cumulative studies demonstrate that the mature miRNAs as well as their precursors can be targeted by small molecular drugs. At the same time, human…

Genomics · Quantitative Biology 2017-08-07 Liang Yu , Jin Zhao , Lin Gao

Drug repurposing is an effective strategy to identify new uses for existing drugs, providing the quickest possible transition from bench to bedside. Existing methods for drug repurposing that mainly focus on pre-clinical information may…

Applications · Statistics 2021-04-14 Ruoqi Liu , Lai Wei , Ping Zhang

Background: The problem of predicting whether a drug combination of arbitrary orders is likely to induce adverse drug reactions is considered in this manuscript. Methods: Novel kernels over drug combinations of arbitrary orders are…

Machine Learning · Computer Science 2019-02-26 Wen-Hao Chiang , Li Shen , Lang Li , Xia Ning

Identification and verification of molecular properties such as side effects is one of the most important and time-consuming steps in the process of molecule synthesis. For example, failure to identify side effects before submission to…

Quantitative Methods · Quantitative Biology 2024-04-12 Collin Beaudoin , Koustubh Phalak , Swaroop Ghosh
‹ Prev 1 2 3 10 Next ›