Since the very start of GigaScience we’ve been strong proponents of Data Citation, helping promote and practice the procedure of affording data the same importance in the scholarly record as citations of other research objects such as publications (see examples of this in GigaBlog and BMC Res Notes ). These efforts by the wider community culminated

GigaScience has always had a focus on reproducibility rather than subjective impact, and it can be challenging for our reviewers to judge this, especially now that more and more tools are being created – bringing data science to the masses.  This also means more efficiency and ease is required especially when multiple collaborators and contributors on a specific project are involved.

GigaScience Press and River Valley Technologies, with the help of Stencila, launch their first interactive “ Executable Research Article ” from their new scientific journal, GigaByte.

The SAMtools suite of tools for manipulating sequencing data one of the most ubiquitous tools in bioinformatics, as the “glue” holding together much of bioinformatics we see it used in pretty much every genomics pipeline we are submitted.

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 need to worry about this complexity.

Sheer Heart Attack Diagnosis is key to beginning treatment for preventing coronary heart disease, the most common cause of heart attacks. One useful tool in the fight against this leading killer is magnetic resonance imaging, which allows the direct examination of blood flow to the myocardium of the heart.