GigaScience aims to revolutionize data dissemination, organization, understanding, and use. An online open-access open-data journal, we publish 'big-data' studies from the entire spectrum of life and biomedical sciences. To achieve our goals, the journal has a novel publication format: one that links standard manuscript publication with an extensive database that hosts all associated data and provides data analysis tools and cloud-computing resources.
Our scope covers not just 'omic' type data and the fields of high-throughput biology currently serviced by large public repositories, but also the growing range of more difficult-to-access data, such as imaging, neuroscience, ecology, cohort data, systems biology and other new types of large-scale sharable data.
With nearly 250 genetic diseases analogous to human disorders cats offer powerful natural models of diseases. Here we present genome assembly and annotation of two domestic and one wild cat greatly improving upon previous low-coverage versions
Elephant species as a whole are dwindling. Here we present sequence data of two Asian elephants that will compliment behavioural, genetic and evolutionary studies of these extraordinary mammals
Here we present a high coverage genome of the Australian Parakeet, the most widely studied parrot species in neuroscience and behavior, that includes data from multiple sequencing technologies and optical maps
This Data Note collects together 3000 rice genomes from 89 countries, providing a foundation for advancing rice breeding technology to help feed a growing world population
Presented here are 4 micro-computed tomography imaging scans of freshly fixed and museum earthworm specimens, allowing computer-based interactive exploration of their morphology and anatomy
No Publication Fees Until 2015
There are currently no article processing charges (APCs) for articles published in GigaScience due to generous support from BGI.
A savings of £1250 (based on 2014 prices)
GigaDB: The GigaScience Database
- Supporting data for the paper: "An integrated catalog of reference genes in the human gut microbiome".
GigaScience hosts all the relevant data and tools from articles published in the journal in its affiliated database, GigaDB. Supporting the open-data movement, data in GigaDB is released under a public domain CC0 waiver. For information on how to submit data with your manuscript, see the instructions for authors. All datasets hosted in GigaDB are assigned a DOI that allows data citation. GigaDB is tracked by the Thomson Reuters Data Citation Index. GigaDB can also provide hosting and DOIs for Software and Workflows integrated into our GigaGalaxy server, as this provides a clear and easy way for researchers to find and use methodology and tools from articles, making work more reproducible and easier to build on.
Data generated in the course of research are just as valuable to academic discourse as papers, and GigaDB provides a direct link between articles and their data by allowing data to be cited to assign due credit and allow its impact and use to be tracked. Submission of data to GigaDB complements but does not serve as a replacement for community approved public repositories, and, thus, supporting data and source code should also be made publicly available in a suitable public repository. See our paper for more information.
BGI was founded in Beijing in 1999 with the mission of supporting scientific and technological development, building strong research teams, and promoting international partnerships. Now the worlds largest genomics organization, in 2007, BGI relocated to Shenzhen as the first citizen-managed, non-profit research institution in China. To further its goals of making scientific information broadly accessible, BGI, in collaboration with BioMed Central, is now contributing to scientific communication by publishing the open-access international research journal GigaScience and hosting its integrated database GigaDB.
- 22 August 2014
- Ain’t No Party like a Bring Your Own Data Party!
- 31 July 2014
- Continuing the push beyond static documents. ISMB, and more on our “What Bioinformaticians need to know about digital publishing beyond the PDF2” workshop
- 22 July 2014
- Guest posting: Optical Mapping allows comprehensiveness and scalability that modern sequencing cannot provide
Automated Function Prediction: sifting through the biological data labelled as unknown function
Edited by: Dr Mark Wass, Dr Iddo Friedberg, Prof Predrag Radivojac
Published: 23 April 2014