| Title |
Bioinformatics for Whole-Genome Shotgun Sequencing of Microbial Communities
|
|---|---|
| Published in |
PLoS Computational Biology, July 2005
|
| DOI | 10.1371/journal.pcbi.0010024 |
| Pubmed ID | |
| Authors |
Kevin Chen, Lior Pachter |
| Abstract |
The application of whole-genome shotgun sequencing to microbial communities represents a major development in metagenomics, the study of uncultured microbes via the tools of modern genomic analysis. In the past year, whole-genome shotgun sequencing projects of prokaryotic communities from an acid mine biofilm, the Sargasso Sea, Minnesota farm soil, three deep-sea whale falls, and deep-sea sediments have been reported, adding to previously published work on viral communities from marine and fecal samples. The interpretation of this new kind of data poses a wide variety of exciting and difficult bioinformatics problems. The aim of this review is to introduce the bioinformatics community to this emerging field by surveying existing techniques and promising new approaches for several of the most interesting of these computational problems. |
X Demographics
The data shown below were collected from the profiles of 12 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 3 | 25% |
| Germany | 1 | 8% |
| Switzerland | 1 | 8% |
| Norway | 1 | 8% |
| Sweden | 1 | 8% |
| Unknown | 5 | 42% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 7 | 58% |
| Members of the public | 5 | 42% |
Mendeley readers
The data shown below were compiled from readership statistics for 860 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 31 | 4% |
| Brazil | 10 | 1% |
| United Kingdom | 7 | <1% |
| Germany | 6 | <1% |
| India | 5 | <1% |
| France | 3 | <1% |
| Italy | 3 | <1% |
| Spain | 3 | <1% |
| Chile | 3 | <1% |
| Other | 31 | 4% |
| Unknown | 758 | 88% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 185 | 22% |
| Researcher | 137 | 16% |
| Student > Master | 125 | 15% |
| Student > Bachelor | 92 | 11% |
| Professor > Associate Professor | 52 | 6% |
| Other | 148 | 17% |
| Unknown | 121 | 14% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 402 | 47% |
| Biochemistry, Genetics and Molecular Biology | 116 | 13% |
| Computer Science | 49 | 6% |
| Environmental Science | 35 | 4% |
| Immunology and Microbiology | 28 | 3% |
| Other | 93 | 11% |
| Unknown | 137 | 16% |