Mixed outcomes for computational predictions-Reference-Cited by-同舟云学术

Mixed outcomes for computational predictions

Published:2017-01-19 Issue: Volume:6 Page:
ISSN:2050-084X
Container-title:eLife
language:en
Short-container-title:

Author:

Dang Chi Van¹

Affiliation:

1. Abramson Cancer Center, Abramson Family Cancer Research Institute, University of Pennsylvania, Philadelphia, United States

Abstract

Experimental efforts to validate the output of a computational model that predicts new uses for existing drugs highlights the inherently complex nature of cancer biology.

Publisher

eLife Sciences Publications, Ltd

Subject

General Immunology and Microbiology,General Biochemistry, Genetics and Molecular Biology,General Medicine,General Neuroscience

Link

https://cdn.elifesciences.org/articles/22661/elife-22661-v1.pdf

Reference7 articles.

1. 1,500 scientists lift the lid on reproducibility;Baker;Nature,2016

2. Drug development: Raise standards for preclinical cancer research;Begley;Nature,2012

3. An open investigation of the reproducibility of cancer biology research;Errington;eLife,2014

4. Registered Report: Discovery and preclinical validation of drug indications using compendia of public gene expression data;Kandela;eLife,2015

5. Replication Study: Discovery and preclinical validation of drug indications using compendia of public gene expression data;Kandela;eLife,2017

Cited by 4 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. Issues and challenges to reproducibility of cancer research: a commentary;Future Oncology;2022-04

2. Independent validation of induced overexpression efficiency across 242 experiments shows a success rate of 39%;Scientific Reports;2019-01-23

3. On the low reproducibility of cancer studies;National Science Review;2018-02-02

4. The challenges of replication;eLife;2017-01-19