Identifying genes from up-down properties of microarray expression series.
BACKGROUND
We consider any collection of microarrays that can be ordered to form a progression; for example, as a function of time, severity of disease or dose of a stimulant. By plotting the expression level of each gene as a function of time, or severity, or dose, we form an expression series, or curve, for each gene. While most of these curves will exhibit random fluctuations, some will contain a pattern, and these are the genes that are most likely associated with the quantity used to order them.


RESULTS
We introduce a method of identifying the pattern and hence genes in microarray expression curves without knowing what kind of pattern to look for. Key to our approach is the sequence of ups and downs formed by pairs of consecutive data points in each curve. As a benchmark, we blindly identified genes from yeast cell cycles without selecting for periodic or any other anticipated behaviour.


BACKGROUND
tmf20@cam.ac.uk


BACKGROUND
The complete versions of Table 2 and Figure 4, as well as other material, can be found at http://www.lps.ens.fr/~willbran/up-down/ or http://www.tcm.phy.cam.ac.uk/~tmf20/up-down/
Willbrand
Karen
K
Laboratoire de Physique Statistique, Ecole Normale Supérieure, Paris, France.
Radvanyi
Francois
F
Nadal
Jean-Pierre
JP
Thiery
Jean-Paul
JP
Fink
Thomas M A
TM
D000465:Algorithms; D020869:Gene Expression Profiling / Q000379:methods*; D005786:Gene Expression Regulation / Q000502:physiology*; D020411:Oligonucleotide Array Sequence Analysis / Q000379:methods*; D010363:Pattern Recognition, Automated / Q000379:methods*; D013997:Time Factors