Title |
Functional analysis of metagenomes and metatranscriptomes using SEED and KEGG
|
---|---|
Published in |
BMC Bioinformatics, February 2011
|
DOI | 10.1186/1471-2105-12-s1-s21 |
Pubmed ID | |
Authors |
Suparna Mitra, Paul Rupek, Daniel C Richter, Tim Urich, Jack A Gilbert, Folker Meyer, Andreas Wilke, Daniel H Huson |
Abstract |
Metagenomics is the study of microbial organisms using sequencing applied directly to environmental samples. Technological advances in next-generation sequencing methods are fueling a rapid increase in the number and scope of metagenome projects. While metagenomics provides information on the gene content, metatranscriptomics aims at understanding gene expression patterns in microbial communities. The initial computational analysis of a metagenome or metatranscriptome addresses three questions: (1) Who is out there? (2) What are they doing? and (3) How do different datasets compare? There is a need for new computational tools to answer these questions. In 2007, the program MEGAN (MEtaGenome ANalyzer) was released, as a standalone interactive tool for analyzing the taxonomic content of a single metagenome dataset. The program has subsequently been extended to support comparative analyses of multiple datasets. |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 17 | 3% |
Brazil | 8 | 2% |
Germany | 4 | <1% |
Canada | 4 | <1% |
France | 3 | <1% |
Mexico | 3 | <1% |
Belgium | 3 | <1% |
India | 3 | <1% |
Chile | 2 | <1% |
Other | 18 | 3% |
Unknown | 466 | 88% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 142 | 27% |
Researcher | 112 | 21% |
Student > Master | 71 | 13% |
Student > Bachelor | 36 | 7% |
Student > Doctoral Student | 28 | 5% |
Other | 82 | 15% |
Unknown | 60 | 11% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 311 | 59% |
Biochemistry, Genetics and Molecular Biology | 48 | 9% |
Environmental Science | 32 | 6% |
Computer Science | 21 | 4% |
Immunology and Microbiology | 12 | 2% |
Other | 36 | 7% |
Unknown | 71 | 13% |