For the past decade, scientists have been worried about the so-called replication crisis. Enter the Preclinical Reproducibility and Robustness channel. The website launched the first week in February with the goal of publishing the results of replication studies. The journal wants to keep scientists accountable for their work.
Elemental Machines, which develops smart laboratory technology, launched a new suite of tools that that measure environmental variables such as temperature and humidity—both of which are not traditionally accounted for in scientific experiments. By “debugging” the lab environment, the company believes it can improve experimental reproducibility, therefore reducing the time and cost of marketing new drugs and therapies. Elemental Machines recently raised $2.5 million in seed capital to support the development of the new suite of tools, which is called the EM Suite.
Elemental Machines, a venture based in Boston and San Francisco, has come out of stealth mode. The startup says it's raised $2.5 million in seed from investors including Founders Fund’s FF Angel, PayPal co-founder Max Levchin and Project 11 Ventures. And now it’s ready to change the way our world does science, providing the infrastructure that will ensure experiment reproducibility for researchers.
Fernando Chirigati and Remi Rampin's poster "Enhancing Scholarly Communication with ReproZip" was recently accepted at FORCE2016, a conference from FORCE11 a community of scholars, librarians, archivists, publishers and research funders that has arisen organically to help facilitate the change toward improved knowledge creation and sharing.
Researchers at Sweden's Karolinska Institute and Royal Institute of Technology have developed a new data analysis workflow for shotgun mass spec that could help improve the technique's quantitative reproducibility. Detailed in a paper published this month in Molecular & Cellular Proteomics, the approach uses a new quality scoring system that allows for more reliable recovery of missing data points across multiple mass spec runs.
A video demonstrating noWorkflow, a non-intrusive tool that allows researchers to capture a variety of provenance information and utilize the analyses it supports, including graph-based visualization, differencing over provenance trails, and inference queries.