Title |
A comprehensive evaluation of multicategory classification methods for microbiomic data
|
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Published in |
Microbiome, April 2013
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DOI | 10.1186/2049-2618-1-11 |
Pubmed ID | |
Authors |
Alexander Statnikov, Mikael Henaff, Varun Narendra, Kranti Konganti, Zhiguo Li, Liying Yang, Zhiheng Pei, Martin J Blaser, Constantin F Aliferis, Alexander V Alekseyenko |
Abstract |
Recent advances in next-generation DNA sequencing enable rapid high-throughput quantitation of microbial community composition in human samples, opening up a new field of microbiomics. One of the promises of this field is linking abundances of microbial taxa to phenotypic and physiological states, which can inform development of new diagnostic, personalized medicine, and forensic modalities. Prior research has demonstrated the feasibility of applying machine learning methods to perform body site and subject classification with microbiomic data. However, it is currently unknown which classifiers perform best among the many available alternatives for classification with microbiomic data. |
X Demographics
Geographical breakdown
Country | Count | As % |
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United Kingdom | 3 | 33% |
India | 1 | 11% |
United States | 1 | 11% |
Unknown | 4 | 44% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 6 | 67% |
Science communicators (journalists, bloggers, editors) | 2 | 22% |
Scientists | 1 | 11% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 11 | 5% |
Sweden | 2 | <1% |
Germany | 1 | <1% |
Canada | 1 | <1% |
Ukraine | 1 | <1% |
Unknown | 219 | 93% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 61 | 26% |
Researcher | 51 | 22% |
Student > Master | 32 | 14% |
Student > Bachelor | 14 | 6% |
Other | 11 | 5% |
Other | 35 | 15% |
Unknown | 31 | 13% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 66 | 28% |
Biochemistry, Genetics and Molecular Biology | 36 | 15% |
Computer Science | 35 | 15% |
Medicine and Dentistry | 15 | 6% |
Immunology and Microbiology | 8 | 3% |
Other | 35 | 15% |
Unknown | 40 | 17% |