Title |
MAKER2: an annotation pipeline and genome-database management tool for second-generation genome projects
|
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Published in |
BMC Bioinformatics, December 2011
|
DOI | 10.1186/1471-2105-12-491 |
Pubmed ID | |
Authors |
Carson Holt, Mark Yandell |
Abstract |
Second-generation sequencing technologies are precipitating major shifts with regards to what kinds of genomes are being sequenced and how they are annotated. While the first generation of genome projects focused on well-studied model organisms, many of today's projects involve exotic organisms whose genomes are largely terra incognita. This complicates their annotation, because unlike first-generation projects, there are no pre-existing 'gold-standard' gene-models with which to train gene-finders. Improvements in genome assembly and the wide availability of mRNA-seq data are also creating opportunities to update and re-annotate previously published genome annotations. Today's genome projects are thus in need of new genome annotation tools that can meet the challenges and opportunities presented by second-generation sequencing technologies. |
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Geographical breakdown
Country | Count | As % |
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Canada | 3 | 19% |
United States | 2 | 13% |
Sweden | 1 | 6% |
Germany | 1 | 6% |
Norway | 1 | 6% |
Unknown | 8 | 50% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 10 | 63% |
Scientists | 5 | 31% |
Science communicators (journalists, bloggers, editors) | 1 | 6% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 19 | 2% |
United Kingdom | 7 | <1% |
Brazil | 7 | <1% |
Sweden | 5 | <1% |
Netherlands | 4 | <1% |
Germany | 4 | <1% |
Switzerland | 3 | <1% |
Norway | 3 | <1% |
Australia | 3 | <1% |
Other | 17 | 1% |
Unknown | 1075 | 94% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 282 | 25% |
Researcher | 213 | 19% |
Student > Master | 139 | 12% |
Student > Bachelor | 95 | 8% |
Other | 58 | 5% |
Other | 185 | 16% |
Unknown | 175 | 15% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 532 | 46% |
Biochemistry, Genetics and Molecular Biology | 261 | 23% |
Computer Science | 44 | 4% |
Engineering | 18 | 2% |
Immunology and Microbiology | 16 | 1% |
Other | 71 | 6% |
Unknown | 205 | 18% |