Editor in Chief
Laurie Goodman, PhD
拉斯维加5357ccScott Edmunds, PhD
拉斯维加5357ccNicole Nogoy, PhD
Hans Zauner, PhD
About the journal
GigaScience 拉斯维加5357ccis an open access, open data, open peer-review journal focusing on ‘big data’ research from the life and biomedical sciences.
GigaScience拉斯维加5357cc has been selected as the 2018 Prose Awards Winner for "Innovation in Journal Publishing."
Supporting data for "Chromosome-level genome assembly of the female western mosquitofish (Gambusia affinis)"
Supporting data for "A haplotype-resolved, de novo genome assembly for the wood tiger moth (Arctia plantaginis) through trio binning"
Supporting data for "Hi-C chromosome conformation capture sequencing of avian genomes using the BGISEQ-500 platform"
Supporting data for "Long-read only assembly of Drechmeria coniospora genomes reveals widespread chromosome plasticity and illustrates the limitations of current nanopore methods."
Discover a variety of collection pages presenting different thematic series from GigaScience.
- Data-Driven Multicellular Systems Biology
- GigaScience Prize Track Series
- Functional Metagenomics (Meta-Func) Series
- Plant phenomics: Data integration and analyses
- Brainhack: Open tools for Brain Science
- Metabolomics: approaches, applications, and integration
- Data intensive ecology
- Optical mapping: new applications, advances and challenges
- fMRI: advances and challenges in big data analysis
- Galaxy Series: Data Intensive and Reproducible Research
- The Genomic Standards Consortium and beyond: best practice in genomics research
ShinyLearner, a new tool to make it easier to perform benchmark comparisons of classification algorithms, showcases a way new of peer reviewing software: the certificate. This tackles one of the main challenges of computational research by supporting people checking and reviewing code with tools to evaluate computer programs. These independently time-stamped runs are awarded a “certificate of reproducible computation” and increased availability, discovery and reproducibility of these crucial artifacts. Alongside the open peer reviews that GigaScience provides as standard, the resulting can be displayed alongside the published paper.
Classification algorithms are a key tool in machine learning, and benchmarking is crucial to decide which algorithm is best for a particular application. ShinyLearner拉斯维加5357cc provides a tool that requires no coding to perform this type of analysis, and stands out by making this process systematic and reproducible so users don’t need to worry about its complexity. Read more in the and to become a CODECHECKER.
拉斯维加5357ccGigaScience has a key focus on the transparency, reproducibility and reusability of data driven research. Check out the additional integrated resources that help enable this.
- integrated database for research objects supporting GigaScience papers
- data driven blogging from the GigaScience editors and guests
- Galaxy workflow server hosting data analyses from GigaScience papers
- GitHub repository for code associated with GigaScience papers
- associated article videos and author and editor presentations
- downloadable, citable and forkable protocols from GigaScience papers
- browse transparent, signed and citable peer-Editable Content Block with Images from GigaScience papers
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拉斯维加5357ccGigaScience is now a member of the NPRC, an alliance of neuroscience journals that share manuscript reviews with other NPRC members at the author's request. The NPRC system facilitates fast-track review and publication of neuroscience research, and reduces the burden on peer reviewers.