| pubmed-article:18302784 | rdf:type | pubmed:Citation | lld:pubmed |
| pubmed-article:18302784 | lifeskim:mentions | umls-concept:C0026175 | lld:lifeskim |
| pubmed-article:18302784 | lifeskim:mentions | umls-concept:C0686817 | lld:lifeskim |
| pubmed-article:18302784 | lifeskim:mentions | umls-concept:C0017337 | lld:lifeskim |
| pubmed-article:18302784 | lifeskim:mentions | umls-concept:C0079429 | lld:lifeskim |
| pubmed-article:18302784 | lifeskim:mentions | umls-concept:C0036849 | lld:lifeskim |
| pubmed-article:18302784 | lifeskim:mentions | umls-concept:C0002045 | lld:lifeskim |
| pubmed-article:18302784 | lifeskim:mentions | umls-concept:C0449774 | lld:lifeskim |
| pubmed-article:18302784 | pubmed:dateCreated | 2008-4-3 | lld:pubmed |
| pubmed-article:18302784 | pubmed:abstractText | Mining gene patterns that are common to multiple genomes is an important biological problem, which can lead us to novel biological insights. When family classification of genes is available, this problem is similar to the pattern mining problem in the data mining community. However, when family classification information is not available, mining gene patterns is a challenging problem. There are several well developed algorithms for predicting gene patterns in a pair of genomes, such as FISH and DAGchainer. These algorithms use the optimization problem formulation which is solved using the dynamic programming technique. Unfortunately, extending these algorithms to multiple genome cases is not trivial due to the rapid increase in time and space complexity. | lld:pubmed |
| pubmed-article:18302784 | pubmed:commentsCorrections | http://linkedlifedata.com/r... | lld:pubmed |
| pubmed-article:18302784 | pubmed:commentsCorrections | http://linkedlifedata.com/r... | lld:pubmed |
| pubmed-article:18302784 | pubmed:commentsCorrections | http://linkedlifedata.com/r... | lld:pubmed |
| pubmed-article:18302784 | pubmed:commentsCorrections | http://linkedlifedata.com/r... | lld:pubmed |
| pubmed-article:18302784 | pubmed:commentsCorrections | http://linkedlifedata.com/r... | lld:pubmed |
| pubmed-article:18302784 | pubmed:commentsCorrections | http://linkedlifedata.com/r... | lld:pubmed |
| pubmed-article:18302784 | pubmed:commentsCorrections | http://linkedlifedata.com/r... | lld:pubmed |
| pubmed-article:18302784 | pubmed:commentsCorrections | http://linkedlifedata.com/r... | lld:pubmed |
| pubmed-article:18302784 | pubmed:commentsCorrections | http://linkedlifedata.com/r... | lld:pubmed |
| pubmed-article:18302784 | pubmed:language | eng | lld:pubmed |
| pubmed-article:18302784 | pubmed:journal | http://linkedlifedata.com/r... | lld:pubmed |
| pubmed-article:18302784 | pubmed:citationSubset | IM | lld:pubmed |
| pubmed-article:18302784 | pubmed:status | MEDLINE | lld:pubmed |
| pubmed-article:18302784 | pubmed:issn | 1471-2105 | lld:pubmed |
| pubmed-article:18302784 | pubmed:author | pubmed-author:YimS KSK | lld:pubmed |
| pubmed-article:18302784 | pubmed:author | pubmed-author:YangJiongJ | lld:pubmed |
| pubmed-article:18302784 | pubmed:author | pubmed-author:SuWeiW | lld:pubmed |
| pubmed-article:18302784 | pubmed:author | pubmed-author:PRAGJ JJJ | lld:pubmed |
| pubmed-article:18302784 | pubmed:author | pubmed-author:ChoiKwangminK | lld:pubmed |
| pubmed-article:18302784 | pubmed:issnType | Electronic | lld:pubmed |
| pubmed-article:18302784 | pubmed:volume | 9 | lld:pubmed |
| pubmed-article:18302784 | pubmed:owner | NLM | lld:pubmed |
| pubmed-article:18302784 | pubmed:authorsComplete | Y | lld:pubmed |
| pubmed-article:18302784 | pubmed:pagination | 124 | lld:pubmed |
| pubmed-article:18302784 | pubmed:dateRevised | 2009-11-18 | lld:pubmed |
| pubmed-article:18302784 | pubmed:meshHeading | pubmed-meshheading:18302784... | lld:pubmed |
| pubmed-article:18302784 | pubmed:meshHeading | pubmed-meshheading:18302784... | lld:pubmed |
| pubmed-article:18302784 | pubmed:meshHeading | pubmed-meshheading:18302784... | lld:pubmed |
| pubmed-article:18302784 | pubmed:meshHeading | pubmed-meshheading:18302784... | lld:pubmed |
| pubmed-article:18302784 | pubmed:meshHeading | pubmed-meshheading:18302784... | lld:pubmed |
| pubmed-article:18302784 | pubmed:meshHeading | pubmed-meshheading:18302784... | lld:pubmed |
| pubmed-article:18302784 | pubmed:meshHeading | pubmed-meshheading:18302784... | lld:pubmed |
| pubmed-article:18302784 | pubmed:meshHeading | pubmed-meshheading:18302784... | lld:pubmed |
| pubmed-article:18302784 | pubmed:meshHeading | pubmed-meshheading:18302784... | lld:pubmed |
| pubmed-article:18302784 | pubmed:meshHeading | pubmed-meshheading:18302784... | lld:pubmed |
| pubmed-article:18302784 | pubmed:year | 2008 | lld:pubmed |
| pubmed-article:18302784 | pubmed:articleTitle | A gene pattern mining algorithm using interchangeable gene sets for prokaryotes. | lld:pubmed |
| pubmed-article:18302784 | pubmed:affiliation | EECS, Case Western Reserve University, Cleveland, OH 44106 USA. meng.hu@case.edu | lld:pubmed |
| pubmed-article:18302784 | pubmed:publicationType | Journal Article | lld:pubmed |
| pubmed-article:18302784 | pubmed:publicationType | Research Support, U.S. Gov't, Non-P.H.S. | lld:pubmed |
| pubmed-article:18302784 | pubmed:publicationType | Research Support, Non-U.S. Gov't | lld:pubmed |
| http://linkedlifedata.com/r... | pubmed:referesTo | pubmed-article:18302784 | lld:pubmed |
