pubmed-article:19261718 | rdf:type | pubmed:Citation | lld:pubmed |
pubmed-article:19261718 | lifeskim:mentions | umls-concept:C0040811 | lld:lifeskim |
pubmed-article:19261718 | lifeskim:mentions | umls-concept:C1969622 | lld:lifeskim |
pubmed-article:19261718 | lifeskim:mentions | umls-concept:C0806909 | lld:lifeskim |
pubmed-article:19261718 | lifeskim:mentions | umls-concept:C0301630 | lld:lifeskim |
pubmed-article:19261718 | lifeskim:mentions | umls-concept:C0150098 | lld:lifeskim |
pubmed-article:19261718 | lifeskim:mentions | umls-concept:C1711238 | lld:lifeskim |
pubmed-article:19261718 | lifeskim:mentions | umls-concept:C1533716 | lld:lifeskim |
pubmed-article:19261718 | lifeskim:mentions | umls-concept:C0205460 | lld:lifeskim |
pubmed-article:19261718 | lifeskim:mentions | umls-concept:C0439534 | lld:lifeskim |
pubmed-article:19261718 | pubmed:issue | 9 | lld:pubmed |
pubmed-article:19261718 | pubmed:dateCreated | 2009-4-24 | lld:pubmed |
pubmed-article:19261718 | pubmed:abstractText | The study of complex biological relationships is aided by large and high-dimensional data sets whose analysis often involves dimension reduction to highlight representative or informative directions of variation. In principle, information theory provides a general framework for quantifying complex statistical relationships for dimension reduction. Unfortunately, direct estimation of high-dimensional information theoretic quantities, such as entropy and mutual information (MI), is often unreliable given the relatively small sample sizes available for biological problems. Here, we develop and evaluate a hierarchy of approximations for high-dimensional information theoretic statistics from associated low-order terms, which can be more reliably estimated from limited samples. Due to a relationship between this metric and the minimum spanning tree over a graph representation of the system, we refer to these approximations as MIST (Maximum Information Spanning Trees). | lld:pubmed |
pubmed-article:19261718 | pubmed:grant | http://linkedlifedata.com/r... | lld:pubmed |
pubmed-article:19261718 | pubmed:grant | http://linkedlifedata.com/r... | lld:pubmed |
pubmed-article:19261718 | pubmed:grant | http://linkedlifedata.com/r... | lld:pubmed |
pubmed-article:19261718 | pubmed:grant | http://linkedlifedata.com/r... | lld:pubmed |
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pubmed-article:19261718 | pubmed:commentsCorrections | http://linkedlifedata.com/r... | lld:pubmed |
pubmed-article:19261718 | pubmed:commentsCorrections | http://linkedlifedata.com/r... | lld:pubmed |
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pubmed-article:19261718 | pubmed:commentsCorrections | http://linkedlifedata.com/r... | lld:pubmed |
pubmed-article:19261718 | pubmed:commentsCorrections | http://linkedlifedata.com/r... | lld:pubmed |
pubmed-article:19261718 | pubmed:commentsCorrections | http://linkedlifedata.com/r... | lld:pubmed |
pubmed-article:19261718 | pubmed:commentsCorrections | http://linkedlifedata.com/r... | lld:pubmed |
pubmed-article:19261718 | pubmed:commentsCorrections | http://linkedlifedata.com/r... | lld:pubmed |
pubmed-article:19261718 | pubmed:language | eng | lld:pubmed |
pubmed-article:19261718 | pubmed:journal | http://linkedlifedata.com/r... | lld:pubmed |
pubmed-article:19261718 | pubmed:citationSubset | IM | lld:pubmed |
pubmed-article:19261718 | pubmed:status | MEDLINE | lld:pubmed |
pubmed-article:19261718 | pubmed:month | May | lld:pubmed |
pubmed-article:19261718 | pubmed:issn | 1367-4811 | lld:pubmed |
pubmed-article:19261718 | pubmed:author | pubmed-author:TidorBruceB | lld:pubmed |
pubmed-article:19261718 | pubmed:author | pubmed-author:KingBracken... | lld:pubmed |
pubmed-article:19261718 | pubmed:issnType | Electronic | lld:pubmed |
pubmed-article:19261718 | pubmed:day | 1 | lld:pubmed |
pubmed-article:19261718 | pubmed:volume | 25 | lld:pubmed |
pubmed-article:19261718 | pubmed:owner | NLM | lld:pubmed |
pubmed-article:19261718 | pubmed:authorsComplete | Y | lld:pubmed |
pubmed-article:19261718 | pubmed:pagination | 1165-72 | lld:pubmed |
pubmed-article:19261718 | pubmed:dateRevised | 2011-4-11 | lld:pubmed |
pubmed-article:19261718 | pubmed:meshHeading | pubmed-meshheading:19261718... | lld:pubmed |
pubmed-article:19261718 | pubmed:meshHeading | pubmed-meshheading:19261718... | lld:pubmed |
pubmed-article:19261718 | pubmed:meshHeading | pubmed-meshheading:19261718... | lld:pubmed |
pubmed-article:19261718 | pubmed:meshHeading | pubmed-meshheading:19261718... | lld:pubmed |
pubmed-article:19261718 | pubmed:meshHeading | pubmed-meshheading:19261718... | lld:pubmed |
pubmed-article:19261718 | pubmed:meshHeading | pubmed-meshheading:19261718... | lld:pubmed |
pubmed-article:19261718 | pubmed:year | 2009 | lld:pubmed |
pubmed-article:19261718 | pubmed:articleTitle | MIST: Maximum Information Spanning Trees for dimension reduction of biological data sets. | lld:pubmed |
pubmed-article:19261718 | pubmed:affiliation | Computer Science and Artificial Intelligence Laboratory, Department of Biological Engineering, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, MA 02139, USA. | lld:pubmed |
pubmed-article:19261718 | pubmed:publicationType | Journal Article | lld:pubmed |
pubmed-article:19261718 | pubmed:publicationType | Research Support, Non-U.S. Gov't | lld:pubmed |
pubmed-article:19261718 | pubmed:publicationType | Research Support, N.I.H., Extramural | lld:pubmed |