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GigaBlog
Data driven blogging from the GigaScience editors
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Published

A lot has already been written about last months Assemblathon2 paper in GigaScience (see the growing list of articles here), but for the box-set completists interested in squeezing every last bit of insight into the project and how it was put together, there was a lot of additional material left over from the recent Biome Q&A with Keith Bradnam that we thought it could be useful to post in a (hopefully final) blog posting.

Published

Open Science flourishes at BOSC and ISMB It’s been a busy couple of weeks for GigaScience , with our 1st birthday, publication of a special anniversary print issue sponsored by Aspera, and publication of the (unusually reviewed) Assemblathon2 paper. These all spanned and were coordinated with the ISMB meeting in Berlin, the yearly gathering of the computational biology community.

Published

Biggest ever contest to put genome assemblers through their paces If you haven’t caught it yet, the largest systematic assessment the process of genome assembly carried out to date has been published this week in GigaScience . The second Assemblathon competition saw 21 teams submit 43 entries based on data from three different unassembled parrot, cichlid fish, and boa constrictor genomes sequenced using three different

Published

The speed of data Last week was the Bio-IT World Asia meeting in Singapore, and while we didn’t attend this year (see last years conference report in Genome Biology ), our editorial board member Tin-Lap Lee presented on the GigaGalaxy server that we have been collaborating with him on (see slides). Also timed for the meeting, Aspera made a press release on our recent adoption of their suite of software products to

Published

The 2013 Galaxy Community Conference (GCC2013) and GigaScience are today announcing a call for papers for a special thematic focused series on studies utilizing large-scale datasets and workflows. Galaxy is an open, web-based platform for data intensive biomedical research allowing their growing community of users to reproduce and share analyses.

Published

With advances in sequencing technologies leading to a so-called “data deluge”, the amount of data supporting a biological study is becoming increasingly unwieldy and difficult to make available. These issues have led to a lack of transparency in analyses of sequencing data, resulting in an ever-increasing reproducibility gap.