Switch to
| Predicate | Object |
|---|---|
| rdf:type | |
| lifeskim:mentions | |
| pubmed:issue |
3
|
| pubmed:dateCreated |
1996-12-4
|
| pubmed:abstractText |
'Profiles' of protein structures and sequence alignments can detect subtle homologies. Profile analysis has been put on firmer mathematical ground by the introduction of hidden Markov model (HMM) methods. During the past year, applications of these powerful new HMM-based profiles have begun to appear in the fields of protein-structure prediction and large-scale genome-sequence analysis.
|
| pubmed:grant | |
| pubmed:language |
eng
|
| pubmed:journal | |
| pubmed:citationSubset |
IM
|
| pubmed:status |
MEDLINE
|
| pubmed:month |
Jun
|
| pubmed:issn |
0959-440X
|
| pubmed:author | |
| pubmed:issnType |
Print
|
| pubmed:volume |
6
|
| pubmed:owner |
NLM
|
| pubmed:authorsComplete |
Y
|
| pubmed:pagination |
361-5
|
| pubmed:dateRevised |
2007-11-14
|
| pubmed:meshHeading | |
| pubmed:year |
1996
|
| pubmed:articleTitle |
Hidden Markov models.
|
| pubmed:affiliation |
Department of Genetics, Washington University School of Medicine, St. Louis, MO 63110, USA. eddy@genetics.wustl.edu
|
| pubmed:publicationType |
Journal Article,
Research Support, U.S. Gov't, P.H.S.,
Review,
Research Support, Non-U.S. Gov't
|