Reference point insensitive molecular data analysis
Author(s) -
Michael Altenbuchinger,
T Rehberg,
Helena U. Zacharias,
Frank Stämmler,
Katja Dettmer,
Daniela Weber,
Andreas Hiergeist,
André Gessner,
Ernst Holler,
Peter J. Oefner,
Rainer Spang
Publication year - 2016
Publication title -
bioinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.599
H-Index - 390
eISSN - 1367-4811
pISSN - 1367-4803
DOI - 10.1093/bioinformatics/btw598
Subject(s) - lasso (programming language) , computer science , measure (data warehouse) , regression , regression analysis , biomedicine , data mining , point (geometry) , algorithm , statistics , bioinformatics , mathematics , machine learning , biology , geometry , world wide web
In biomedicine, every molecular measurement is relative to a reference point, like a fixed aliquot of RNA extracted from a tissue, a defined number of blood cells, or a defined volume of biofluid. Reference points are often chosen for practical reasons. For example, we might want to assess the metabolome of a diseased organ but can only measure metabolites in blood or urine. In this case, the observable data only indirectly reflects the disease state. The statistical implications of these discrepancies in reference points have not yet been discussed.
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