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Literature DB >> 22965029

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Abstract

Mesh：

Year: 2012 PMID： 22965029 DOI： 10.1038/nbt.2335

Source DB: PubMed Journal: Nat Biotechnol ISSN： 1087-0156 Impact factor: 54.908

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3 in total

1. Drug development: Raise standards for preclinical cancer research.

Authors: C Glenn Begley; Lee M Ellis
Journal: Nature Date: 2012-03-28 Impact factor: 49.962

2. Erroneous analyses of interactions in neuroscience: a problem of significance.

Authors: Sander Nieuwenhuis; Birte U Forstmann; Eric-Jan Wagenmakers
Journal: Nat Neurosci Date: 2011-08-26 Impact factor: 24.884

3. Believe it or not: how much can we rely on published data on potential drug targets?

Authors: Florian Prinz; Thomas Schlange; Khusru Asadullah
Journal: Nat Rev Drug Discov Date: 2011-08-31 Impact factor: 84.694

3 in total

11 in total

1. Increasing disparities between resource inputs and outcomes, as measured by certain health deliverables, in biomedical research.

Authors: Anthony Bowen; Arturo Casadevall
Journal: Proc Natl Acad Sci U S A Date: 2015-08-17 Impact factor: 11.205

2. Receptive to replication.

Authors:
Journal: Nat Biotechnol Date: 2013-11 Impact factor: 54.908

3. A necessary supplement.

Authors:
Journal: Nat Methods Date: 2012-11 Impact factor: 28.547

4. Assessing the validity and reproducibility of genome-scale predictions.

Authors: Lauren A Sugden; Michael R Tackett; Yiannis A Savva; William A Thompson; Charles E Lawrence
Journal: Bioinformatics Date: 2013-09-17 Impact factor: 6.937

5. The international MAQC Society launches to enhance reproducibility of high-throughput technologies.

Authors: Leming Shi; Rebecca Kusko; Russell D Wolfinger; Benjamin Haibe-Kains; Matthias Fischer; Susanna-Assunta Sansone; Christopher E Mason; Cesare Furlanello; Wendell D Jones; Baitang Ning; Weida Tong
Journal: Nat Biotechnol Date: 2017-12-08 Impact factor: 54.908

Further confirmation needed.

1. Drug development: Raise standards for preclinical cancer research.

2. Erroneous analyses of interactions in neuroscience: a problem of significance.

3. Believe it or not: how much can we rely on published data on potential drug targets?

1. Increasing disparities between resource inputs and outcomes, as measured by certain health deliverables, in biomedical research.

2. Receptive to replication.

3. A necessary supplement.

4. Assessing the validity and reproducibility of genome-scale predictions.

5. The international MAQC Society launches to enhance reproducibility of high-throughput technologies.

6. ITK: enabling reproducible research and open science.

7. The Researchers' View of Scientific Rigor-Survey on the Conduct and Reporting of In Vivo Research.

8. Reproducibility of biomedical research - The importance of editorial vigilance.

9. Biosafety data as confidential business information.

10. Overflow in science and its implications for trust.