Source:http://linkedlifedata.com/resource/pubmed/id/21042592
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| Predicate | Object |
|---|---|
| rdf:type | |
| lifeskim:mentions | |
| pubmed:issue |
10
|
| pubmed:dateCreated |
2010-11-2
|
| pubmed:abstractText |
With an estimated 38 million people worldwide currently infected with human immunodeficiency virus (HIV), and an additional 4.1 million people becoming infected each year, it is important to understand how this virus mutates and develops resistance in order to design successful therapies.
|
| pubmed:grant | |
| pubmed:language |
eng
|
| pubmed:journal | |
| pubmed:citationSubset |
IM
|
| pubmed:chemical | |
| pubmed:status |
MEDLINE
|
| pubmed:issn |
1932-6203
|
| pubmed:author | |
| pubmed:issnType |
Electronic
|
| pubmed:volume |
5
|
| pubmed:owner |
NLM
|
| pubmed:authorsComplete |
Y
|
| pubmed:pagination |
e13564
|
| pubmed:meshHeading | |
| pubmed:year |
2010
|
| pubmed:articleTitle |
Development of a low bias method for characterizing viral populations using next generation sequencing technology.
|
| pubmed:affiliation |
Department of Chemical Engineering and the Helen Wills Neuroscience Institute, University of California, Berkeley, California, United States of America.
|
| pubmed:publicationType |
Journal Article,
Research Support, Non-U.S. Gov't,
Research Support, N.I.H., Extramural,
Validation Studies
|