Title |
Automated ensemble assembly and validation of microbial genomes
|
---|---|
Published in |
BMC Bioinformatics, May 2014
|
DOI | 10.1186/1471-2105-15-126 |
Pubmed ID | |
Authors |
Sergey Koren, Todd J Treangen, Christopher M Hill, Mihai Pop, Adam M Phillippy |
Abstract |
The continued democratization of DNA sequencing has sparked a new wave of development of genome assembly and assembly validation methods. As individual research labs, rather than centralized centers, begin to sequence the majority of new genomes, it is important to establish best practices for genome assembly. However, recent evaluations such as GAGE and the Assemblathon have concluded that there is no single best approach to genome assembly. Instead, it is preferable to generate multiple assemblies and validate them to determine which is most useful for the desired analysis; this is a labor-intensive process that is often impossible or unfeasible. |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 10 | 45% |
United Kingdom | 2 | 9% |
Thailand | 1 | 5% |
Sweden | 1 | 5% |
China | 1 | 5% |
Norway | 1 | 5% |
Germany | 1 | 5% |
Unknown | 5 | 23% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Scientists | 14 | 64% |
Members of the public | 8 | 36% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 11 | 5% |
Brazil | 4 | 2% |
Norway | 1 | <1% |
Netherlands | 1 | <1% |
Australia | 1 | <1% |
Sweden | 1 | <1% |
Germany | 1 | <1% |
Czechia | 1 | <1% |
United Kingdom | 1 | <1% |
Other | 6 | 3% |
Unknown | 200 | 88% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 72 | 32% |
Student > Ph. D. Student | 40 | 18% |
Student > Bachelor | 23 | 10% |
Student > Master | 22 | 10% |
Professor > Associate Professor | 13 | 6% |
Other | 35 | 15% |
Unknown | 23 | 10% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 115 | 50% |
Biochemistry, Genetics and Molecular Biology | 26 | 11% |
Computer Science | 20 | 9% |
Immunology and Microbiology | 9 | 4% |
Engineering | 7 | 3% |
Other | 26 | 11% |
Unknown | 25 | 11% |