Genomes OnLine Database (GOLD) v.8: overview and updates

By Supratim Mukherjee, Dimitrios Stamatis, J. Bertsch, Galina Ovchinnikova, J. C. Sundaramurthi, Janey Lee, Mahathi Kandimalla, I. Chen, Nikos Kyrpides, T. Reddy. 2020

174 citations recorded by the source corpus.

The Genomes OnLine Database (GOLD) (https://gold.jgi.doe.gov/) is a manually curated, daily updated collection of genome projects and their metadata accumulated from around the world. The current version of the database includes over 1.17 million entries organized broadly into Studies (45 770), Organisms (387 382) or Biosamples (101 207), Sequencing Projects (355 364) and Analysis Projects (283 481). These four levels contain over 600 metadata fields, which includes 76 controlled vocabulary (CV) tables containing 3873 terms. GOLD provides an interactive web user interface for browsing and searching by a wide range of project and metadata fields. Users can enter details about their own projects in GOLD, which acts as a gatekeeper to ensure that metadata is accurately documented before submitting sequence information to the Integrated Microbial Genomes (IMG) system for analysis. In order to maintain a reference dataset for use by members of the scientific community, GOLD also imports projects from public repositories such as GenBank and SRA. The current status of the database, along with recent updates and improvements are described in this manuscript.

Subfields: Ecology, Molecular Biology

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In Ecology

1. Dmitry Meleshko
2. Anton I. Korobeynikov
3. Jillian F. Banfield
4. Rayan Chikhi
5. Robert C. Edgar
6. Patrick D. Schloss
7. Kazutaka Katoh
8. Toni Gabaldón

In Molecular Biology

1. Dmitry Meleshko
2. Jillian F. Banfield
3. Anton I. Korobeynikov
4. Alexander Rives
5. Tom Sercu
6. Brian L. Hie
7. Robert Verkuil
8. Rayan Chikhi

Citations in the corpus

• Evolutionary-scale prediction of atomic level protein structure with a language model (2022, background): “[26] Supratim Mukherjee, Dimitri Stamatis, Jon Bertsch, Galina Ovchinnikova, Jagadish Chandrabose Sundaramurthi, Janey Lee, Mahathi Kandimalla, I.”
• Petabase-scale sequence alignment catalyses viral discovery (2020, background): “Discordant libraries—ones in which a CoV is identified and the viral expected host 30 does not match the sequencing library source taxa—were rare, accounting for only 0.92% of cases (Supplementary Table 1f).”