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GigaBlog
Data driven blogging from the GigaScience editors
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It’s December, the festive season and the end of  year are approaching fast –  and it’s time for our traditional look back on the past 12 months at GigaScience Press . Once more, we are pleased with the view in the rear mirror.  In its 11th year, GigaScience again published exceptional “big data” science (read on for examples). And GigaScience’s

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This end-of-the-year festive summary is different from previous ones:  For the first time, we can look back at a full publication year of our new baby, GigaByte journal. The older sibling GigaScience will also get the attention it deserves, before celebrating its 10th birthday in 2022. Let’s first have a look at how the new family member is doing.

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This is the last blog post of 2019 and it is time again to look back at some of the amazing research published in GigaScience over the past year. Besides handling manuscripts, reviews and data, the editors and curators also attended conferences near and far, they contributed to policy discussions and prepared the launch of a new journal, GigaByte. More about all these activities below.

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GigaScience recently published an article all about a Genotype Investigator for Genome-Wide Analyses, alternatively known as Gigwa. But what is this and how can it help? Guilhem Sempere explains more in a guest post. Exploring the structure of genomes and analyzing their evolution is essential to understanding the adaptation of organisms to biotic and abiotic environments.

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Today, GigaScience launched a project providing an alternative way to give authors credit for their work, contributing more to collaboration, transparency and better data. Amye Kenall tells us more about what this is and how it works. There is a clear need for better transparency and credit around authorship. In the current system researchers are evaluated by publications and the Impact Factor of journals in which they appear.

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Editors: Mark Wass (University of Kent, UK), Iddo Friedberg (Miami University, Oxford, Ohio, USA), Predrag Radivojac (Indiana University, Bloomington, Indiana, USA) Last July, GigaScience and the organisers of the Automated Function Prediction special interest group at ISMB announced an upcoming series on Automated Function Prediction.

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Regular reader of this blog will be aware of our efforts to promote data citation using digital object identifiers (DOIs), and this week, alongside Rebecca Lawrence from F1000 Research and Kevin Ashley from the Digital Curation Centre, our Editor in Chief Laurie Goodman has a correspondence in Nature strongly making this case.

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The precipitous drop in the price of next generation sequencing coupled with its increasing sensitivity has opened up whole new areas of research, one of the most interesting in recent years being the advent of single-cell sequencing. Combining advances in flow-sorting of cells, whole genome amplification and the latest sequencing technologies is now allowing researchers to study tumor evolution on a single-cell level.