Tag Archives: reproducible research
Open Access Week 2021: GigaScience’s 10 Examples of Open
Scott Edmunds - October 29, 2021
For Open Access Week 2021 we look back over 10 of our favourite GigaScience papers providing examples of barriers we’ve tried to break for more open science.
GigaByte and River Valley Technologies push the boundaries of Executable Research Articles using Stencila and Code Ocean
Scott Edmunds - February 25, 2021
Today GigaByte publishes its first Executable Research Article (ERA), using technology from Stencila and Code Ocean to showcase interactive and executable versions of the figures.
Reproducible Classification. Q&A on ShinyLearner & the CODECHECK certificate, pt. 2
Scott Edmunds - April 8, 2020
This week we showcased a new way of peer reviewing software, testing code in an independent manner and providing a CODECHECK “certificate of reproducible computation” when the results in the paper can be reproduced. We’ve written a post on the CODECHECK process featuring a Q&A with CODECHECK founder Stephen Eglan, and here we’ll provide a follow […]
Certified Reproducibility. Q&A on ShinyLearner & the CODECHECK certificate, pt. 1
Scott Edmunds - April 7, 2020
Out today in GigaScience is ShinyLearner, a new tool to make it easier to perform benchmark comparisons of classification algorithms. This tool stands out by making this process super systematic and reproducible, and despite needing to interface with many different libraries and languages it uses software containers (and a CodeOcean demo) so end users don’t […]
GigaBlog meets Gigantum: Guest Post from Tyler Whitehouse, Dean Kleissas and Dav Clark
Nicole Nogoy - June 20, 2019
At GigaScience as our focus is on reproducibility rather than subjective impact, it can be challenging at times to judge this in our papers. Targeting the “bleeding edge” of data-driven research, more and more of our papers utilise technologies, such as Jupyter notebooks, Virtual Machines, and Containers such as Docker. Working these tools in to […]
Meet the GigaScience ICG Prize Winner, Pt. 2: Lisa Johnson Q&A
Scott Edmunds - December 14, 2018
Yesterday we published the winning paper of the second GigaScience prize, with additional detail and coverage in GigaBlog describing why we and the judging panel found it so novel. This was an impressively case study in reproducibility, reassembling & reannotating around 700 microbial eukaryotic transcriptomes to demonstrate this approach can aid in revealing new biologically relevant […]
Reprocessing the Microbial Genomic Goldmine: Winner of the ICG13 Prize
Scott Edmunds - December 13, 2018
Out today is the winner of our ICG13 Prize, presenting work that can aid in revealing new biologically relevant findings and missed genes from previously generated transcriptome assemblies. Teaching old data new tricks, and maximising every last nugget of information from previously funded research. Here we present some insight into why the reviewers and judges […]
CUDDELing up to metabolomics in Hong Kong
Peter Li - January 22, 2018
As mentioned in our Happy New Year blog post, one of the highlights in 2017 was a second GigaScience hackathon workshop which we held in November last year in our Hong Kong BGI office. Funding for this workshop came from a project we have called CUDDEL which was awarded a grant by the BBSRC from their China […]
Research Parasites Wanted. Q&A with Casey Greene & Brian Byrd
Scott Edmunds - September 14, 2017
As a journal focussed on open science we are big promoters of research parasites (and research on parasites), and try to feeds them with open data and tools. It is therefore appropriate this is the second year GigaScience has supported and sponsored the Research Parasite awards. In one of our Q&As, organisers Casey Greene and […]
Data Intensive Software Publishing & Sailing The Code Ocean. Q&A With Ruibang Luo.
Scott Edmunds - June 27, 2017
GigaScience is always trying to push the boundaries of how we disseminate reproducible research, and to adapt to the challenges of dealing with experiments become more data-intensive. We now showcase a new reproducible research platform we’ve been testing called Code Ocean, and have a Q&A with our Author Ruibang Luo on his experiences using it. […]