Reproducing palaeontological results depends on unrestricted access to fossils described in the literature, allowing others to re-examine or reinterpret them. Museums have policies and protocols for keeping materials in the public trust, but accessibility to privately owned fossil collections can be a problem.
There’s been a lot of discussion across many scientific fields about the "reproducibility crisis" in the past few years. Hundreds of psychologists attempted to redo 100 studies as part of the Reproducibility Project in Psychology, and claimed that fewer than half of the replication attempts succeeded. In Biomedicine, a study from the biotech firm Amgen tried to re-create results of 53 "landmark" preclinical cancer studies, and only got the same results for six of them. Amid a growing concern about research reliability, funders including the National Institutes of Health (NIH) have called for a greater effort to make research reproducible through transparent reporting of the methods researchers use to conduct their investigations.
The ongoing dialogue has included the role of improperly validated research reagents, such as antibodies, with blame falling at the feet of reagent vendors, researchers, and journals. This article will highlight how the lack of consistent research on antibody validation has contributed to the reproducibility crisis and the role of vendors from Cell Signaling Technology’s (CST) perspective in making research more robust and reproducible.
The lack of reproducibility of preclinical experimentation has implications for sustaining trust in and ensuring the viability and funding of the academic research enterprise. Here I identify problematic behaviors and practices and suggest solutions to enhance reproducibility in translational research.
Numerous variables can torpedo attempts to replicate cell experiments, from the batch of serum to the shape of growth plates. But there are ways to ensure reliability.
Many scientists worry over the reproducibility of wet-lab experiments, but data scientist Victoria Stodden's focus is on how to validate computational research: analyses that can involve thousands of lines of code and complex data sets. Beginning this month, Stodden — who works at the University of Illinois at Urbana-Champaign — becomes one of three ‘reproducibility editors’ appointed to look over code and data sets submitted by authors to the Applications and Case Studies (ACS) section of the Journal of the American Statistical Association (JASA). Other journals including Nature have established guidelines for accommodating data requests after publication, but they rarely consider the availability of code and data during the review of a manuscript. JASA ACS will now insist that — with a few exceptions for privacy — authors submit this information as a condition of publication.