Data-Driven Prediction of Drug Effects and Interactions-Reference-Cited by-同舟云学术

Data-Driven Prediction of Drug Effects and Interactions

Published:2012-03-14 Issue:125 Volume:4 Page:
ISSN:1946-6234
Container-title:Science Translational Medicine
language:en
Short-container-title:Sci. Transl. Med.

Author:

Tatonetti Nicholas P.¹²,Ye Patrick P.²,Daneshjou Roxana³,Altman Russ B.²³

Affiliation:

1. Biomedical Informatics Training Program, Stanford University, Stanford, CA 94305, USA.

2. Departments of Bioengineering and Genetics, Stanford University, Stanford, CA 94305, USA.

3. Department of Medicine, Stanford University, Stanford, CA 94305, USA.

Abstract

Two new databases—one of drug effects and a second of drug-drug interaction side effects—permit identification of drug targets, prediction of drug indications, and discovery of drug class interactions.

Publisher

American Association for the Advancement of Science (AAAS)

Subject

General Medicine

Reference34 articles.

1. Incidence of Adverse Drug Events and Potential Adverse Drug Events

2. Adverse Drug Events in Hospitalized PatientsExcess Length of Stay, Extra Costs, and Attributable Mortality

3. Pharmacovigilance in the 21st Century: New Systematic Tools for an Old Problem

4. Quantitative signal detection using spontaneous ADR reporting

5. Use of Screening Algorithms and Computer Systems to Efficiently Signal Higher-Than-Expected Combinations of Drugs and Events in the US FDA??s Spontaneous Reports Database

Cited by 628 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Transformer-based medication recommendation with a multiple graph augmentation strategy;Expert Systems with Applications;2024-12

2. A study on improving drug–drug interactions prediction using convolutional neural networks;Applied Soft Computing;2024-11

3. Role of AI in Advancing Pharmacology;Advances in Medical Technologies and Clinical Practice;2024-09-27

4. Polypharmacy side effect prediction based on semi-implicit graph variational auto-encoder;Journal of Bioinformatics and Computational Biology;2024-09-12

5. Network medicine and systems pharmacology approaches to predicting adverse drug effects;British Journal of Pharmacology;2024-09-11