.... The initial goal was to repeat 193 experiments from 53 high-impact papers published between 2010 and 2012, but the obstacles we encountered at every phase of the research lifecycle meant that we were only able to repeat 50 experiments from 23 papers. In the Liu Lab, we hope we could understand more about what affects scientific reproducibility and rebuild the public confidence over science and research!!

Make science more reliable by placing the burden of replicability on the community, not on individual laboratories. I found this article particularly interesting: https://www.nature.com/articles/d41586-021-02486-7#ref-CR1

Share your thoughts. Feel free to add GIFs, videos, #hashtags and more to your posts and comments. Get started by commenting below. Nature conducted a survey in 2016 with 1,576 researchers, and 52% of participants agreed on the existence of a “reproducibility crisis”. Disappointing results were gained from replication efforts on selected high-profile papers in cancer biology. Nevertheless, the scientific community discovered a few key factors that influence reproducibility, including inappropriate study design, improper statistics, lack of data sharing and data transparency, undocumented subtle protocol details, different or mislabeled reagents, and poorly reproducible measurement methods. In 2019, the PI’s lab led a cross-lab study reporting the multi-omic heterogeneity in HeLa cells, which was published in Nature Biotechnology. This study and many others indicate that the complexity inherent in biological systems further challenges the reproducibility of life science research. We hope to make use of the Online Forum feature in our Lab Webpage to engage more scientists and visitors to continue the discussion of key elements that influence research reproducibility. All visitors to the Forum can sign in with their email or Google and Facebook accounts and share their opinions, knowledge, research stories, and video links about the topic of research producibility – especially in the field of quantitative proteomics.

We'd love to get to know you better. Take a moment to say hi to the community in the comments.

We want everyone to get the most out of this community, so we ask that you please read and follow these guidelines: Respect each other Keep posts relevant to the forum topic No spamming