Total number of projects
Total number of libraries
44,895,778Combined length (amino acids): 5,713,099,081
MetagenomesOnline - The Curated Database for Environmental Metagenome Proteins
What is MetagenomesOnline?
MgOl is a manually annotated resource of predicted proteins identified in viral and microbial shotgun metagenomes. MgOl libraries are annotated with an abundance of sample metadata including sample provenance, geographical description, environmental parameters, sampling and preparation methodologies, and Environmental Ontology (ENVO) terms. Samples are further categorized using MgOl Sample Descriptors, easy to understand terms allowing samples to be easily grouped for comparison.
How can I use MgOl?
MgOl was initially designed as the environmental protein database that has underlied the VIROME metagenome annotation pipeline since 2009. Metagenome libraries submitted for analysis at VIROME are BLASTed against MgOl, with its graphical interface and links to various protein metadata enabling exploration of the results. This MgOl website is meant as a resource to obtain additional metadata regarding MgOl libraries and the proteins that compose them. Users can also perform use the website to perform small-scale homology searches against the database using the MgOl BLAST tool, or download all or part of the database, allowing this resource to be used for custom analysis on local hardware.
MGOL development supported through research grants from the Gordon and Betty Moore Foundation, the National Science Foundation, and the US. Department of Agriculture. Additional support from the Data Intensive Academic Grid/Institute for Genome Sciences, Delaware Biotechnology Institute, Delaware EPSCoR, Delaware INBRE, and the University of Delaware Center for Bioinformatics and Computational Biology.
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Meet the Team
We would love to hear your feedback, please contact us at: email@example.com
If you use MgOl, please list our URL (http://metagenomesonline.org) and cite:
Wommack, KE*, J Bhavsar*, SW Polson*, J Chen, M Dumas, S Srinivasiah, M Furman, S Jamindar, and DJ Nasko. 2012. VIROME: a standard operating procedure for analysis of viral metagenome sequences. Standards in Genomic Sciences 6:427-439 [PMC3558967]