Metagenomics is a relatively recently established but rapidly expanding field that uses high-throughput next-generation sequencing technologies to characterize the microbial communities inhabiting different ecosystems (including oceans, lakes, soil, tundra, plants and body sites). Metagenomics brings with it a number of challenges, including the management, analysis, storage and sharing of data.
A functional gene database was developed to screen environmental metagenomic sequence datasets. FOAM provides a new functional ontology dedicated to classify gene functions relevant to environmental microorganisms based on Hidden Markov Models (HMMs).
Offers a collection of multiple sequence alignments and profiles hidden Markov models (HMMs). AntiFam can assist researchers to identify spurious open reading frames (ORFs) in protein annotation. It can be used to proceed quality control in metagenomic and genomic studies. This tool is composed of more than 20 families derived from Pfam as well as a small number of non-coding RNAs that were erroneously translated into protein sequences.
Supplies an access to several biological data resources and bioinformatics services. EBI is a platform that covers the entire range of biological sciences: raw DNA sequences to curated proteins, chemicals, structures, systems, pathways, ontologies and literature. Databases, tools, as well as web services are provided for sharing data, performing queries and analyzing results. Users can also deposit their data through a data submission page. All the resources are freely available without restriction, with few exceptions.
An open-submission data portal for processing, analyzing, sharing and disseminating metagenomic datasets. The system currently hosts over 200,000 datasets and is continuously updated. The volume of submissions has increased 4-fold over the past 24 months, now averaging 4 terabasepairs per month. In addition to several new features, we report changes to the analysis workflow and the technologies used to scale the pipeline up to the required throughput levels.
Enables discovery and access to microbial datasets consisting of project information, omics data and assemblies, metadata, and other associated files. Data in the iMicrobe Data Commons can be used in conjunction with iPlant bioinformatics tools, computational resources, and other federated datasets. Moreover, using data within the iPlant cyberinfrastructure fosters collaboration and data sharing among researchers towards broader community interaction.
Helps users to identify experimental variables associated with changes in microbial community structure. MicrobiomeDB was developed to empower researchers to leverage their experimental metadata to construct queries that interrogate microbiome datasets. The development of this online resource integrates an automated workflow for loading data from microbiome experiments. It also accepts microbial community census data in the form of a .biom file.
Includes all in-complete sequenced marine prokaryotic genomes regardless level of completeness. MarDB is a contextual and sequence part of MAR databases. This resource was built by compiling data from a number of publicly available sequence, taxonomy and literature databases in a semiautomatic fashion. There are three environmental metadata fields used for describing the sampling site of a microorganism in MarDB: environmental biome, feature and material which are controlled by a total of 95 terms.