Title |
De novo identification of viral pathogens from cell culture hologenomes
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Published in |
BMC Research Notes, January 2012
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DOI | 10.1186/1756-0500-5-11 |
Pubmed ID | |
Authors |
Ashok Patowary, Rajendra Kumar Chauhan, Meghna Singh, Shamsudheen KV, Vinita Periwal, Kushwaha KP, Gajanand N Sapkal, Vijay P Bondre, Milind M Gore, Sridhar Sivasubbu, Vinod Scaria |
Abstract |
Fast, specific identification and surveillance of pathogens is the cornerstone of any outbreak response system, especially in the case of emerging infectious diseases and viral epidemics. This process is generally tedious and time-consuming thus making it ineffective in traditional settings. The added complexity in these situations is the non-availability of pure isolates of pathogens as they are present as mixed genomes or hologenomes. Next-generation sequencing approaches offer an attractive solution in this scenario as it provides adequate depth of sequencing at fast and affordable costs, apart from making it possible to decipher complex interactions between genomes at a scale that was not possible before. The widespread application of next-generation sequencing in this field has been limited by the non-availability of an efficient computational pipeline to systematically analyze data to delineate pathogen genomes from mixed population of genomes or hologenomes. |
X Demographics
Geographical breakdown
Country | Count | As % |
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Unknown | 1 | 100% |
Demographic breakdown
Type | Count | As % |
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Members of the public | 1 | 100% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
United Kingdom | 2 | 5% |
Chile | 1 | 2% |
France | 1 | 2% |
New Zealand | 1 | 2% |
Denmark | 1 | 2% |
United States | 1 | 2% |
Unknown | 34 | 83% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 11 | 27% |
Researcher | 10 | 24% |
Student > Master | 4 | 10% |
Student > Bachelor | 3 | 7% |
Professor | 3 | 7% |
Other | 9 | 22% |
Unknown | 1 | 2% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 19 | 46% |
Biochemistry, Genetics and Molecular Biology | 7 | 17% |
Medicine and Dentistry | 5 | 12% |
Computer Science | 4 | 10% |
Engineering | 2 | 5% |
Other | 2 | 5% |
Unknown | 2 | 5% |